In this paper, the Chebyshev polynomial approximation is applied to the problem of stochastic period-doubling bifurcation of a stochastic Bonhoeffer-van der Pol （BVP for short） system with a bounded random parameter...In this paper, the Chebyshev polynomial approximation is applied to the problem of stochastic period-doubling bifurcation of a stochastic Bonhoeffer-van der Pol （BVP for short） system with a bounded random parameter. In the analysis, the stochastic BVP system is transformed by the Chebyshev polynomial approximation into an equivalent deterministic system, whose response can be readily obtained by conventional numerical methods. In this way we have explored plenty of stochastic period-doubling bifurcation phenomena of the stochastic BVP system. The numerical simulations show that the behaviour of the stochastic period-doubling bifurcation in the stochastic BVP system is by and large similar to that in the deterministic mean-parameter BVP system, but there are still some featured differences between them. For example, in the stochastic dynamic system the period-doubling bifurcation point diffuses into a critical interval and the location of the critical interval shifts with the variation of intensity of the random parameter. The obtained results show that Chebyshev polynomial approximation is an effective approach to dynamical problems in some typical nonlinear systems with a bounded random parameter of an arch-like probability density function.展开更多
In order to analyze the risky factors that affect vehicle-cyclist crash injury severity at the intersection area,especially the factors relating to the road users behaviors,an empirical study was conducted by collecti...In order to analyze the risky factors that affect vehicle-cyclist crash injury severity at the intersection area,especially the factors relating to the road users behaviors,an empirical study was conducted by collecting accident records from 2011 to 2015 from the General Estimates System.After preliminary screening,the variables were classified into 5 main categories including cyclists characteristic and behavior,drivers characteristic and behavior,vehicle characteristic,intersection condition,and time.The random parameter ordinal probit(RPOP)was used to study the significant influencing factors and corresponding heterogeneity.The results show that failing to obey traffic signals,failing to yield to right-of-way,dash and drinking before cycling can increase the injury severity for cyclists,and the corresponding fatal injury likelihoods increase by 53.2%,40.0%,86.3%,and 211.5%,respectively.Moreover,drivers inattention,speeding,going straight and left turning increase the risk of crashing for cyclists.The corresponding fatal injury likelihoods increase by 134.5%,186.5%,69.3%,and 22.7%,respectively.Other indicators such as age,gender,vehicle type,traffic signal and intersection type can also affect injury severity.展开更多
Despite the number of studies focusing on the financial analysis of production activities, conducting on technical solutions, and improving water quality, no study has been conducted on the application of economic ins...Despite the number of studies focusing on the financial analysis of production activities, conducting on technical solutions, and improving water quality, no study has been conducted on the application of economic instruments that apply to water quality management in craft villages, and several studies of WTP also. This study aimed to estimate the households’ willingness-to-pay for wastewater treatment in selected traditional agro-food processing villages in Nhue-Day River Basin, Vietnam. A pilot Choice Experiment (CE) technique in Choice Modelling (CM) approach was applied for this study with 267 selected agro-food processing households by using the conditional logit (CL) and random parameter logit (RPL) models. The results showed that total annual environmental fee for wastewater treatment from agro-food processing households is estimated as 1089 million VND (equal to US$47,868 per year) for the total of 902 agro-food processing households in three research sites in Nhue-Day River Basin. This estimated budget for wastewater treatment accounted for 55.85% of total annual operation and maintenance costs only. In addition, the technology is improved to enable 90% of treated wastewater. Overall, the results of this study suggest the new wastewater treatment plant construction and improved wastewater collection system by increasing the investment in order to improve the water quality in Nhue-Day River Basin that brings about the reducing environmental degradation, biodiversity loss and human health risks.展开更多
A Monte Carlo method was used to take thorough account of the influences of different reactivity ratios and initial feed compositions on copolymer microstructure.The model proves the lack of azeotropic behavior in sys...A Monte Carlo method was used to take thorough account of the influences of different reactivity ratios and initial feed compositions on copolymer microstructure.The model proves the lack of azeotropic behavior in systems in which r_A>1 and r_B<1 or vice versa;it is also able to calculate the drift in the copolymer properties:copolymer composition,and randomness parameter.Moreover,for each reactivity ratio pair given,there is a unique reaction conversion,at which macromolecules produced inherit their ...展开更多
This paper aims to study the stochastic period-doubling bifurcation of the three-dimensional Rossler system with an arch-like bounded random parameter. First, we transform the stochastic RSssler system into its equiva...This paper aims to study the stochastic period-doubling bifurcation of the three-dimensional Rossler system with an arch-like bounded random parameter. First, we transform the stochastic RSssler system into its equivalent deterministic one in the sense of minimal residual error by the Chebyshev polynomial approximation method. Then, we explore the dynamical behaviour of the stochastic RSssler system through its equivalent deterministic system by numerical simulations. The numerical results show that some stochastic period-doubling bifurcation, akin to the conventional one in the deterministic case, may also appear in the stochastic Rossler system. In addition, we also examine the influence of the random parameter intensity on bifurcation phenomena in the stochastic Rossler system.展开更多
The article mainly explores the Hopf bifurcation of a kind of nonlinear system with Gaussian white noise excitation and bounded random parameter.Firstly,the nonlinear system with multisource stochastic fac-tors is red...The article mainly explores the Hopf bifurcation of a kind of nonlinear system with Gaussian white noise excitation and bounded random parameter.Firstly,the nonlinear system with multisource stochastic fac-tors is reduced to an equivalent deterministic nonlinear system by the sequential orthogonal decomposi-tion method and the Karhunen-Loeve(K-L)decomposition theory.Secondly,the critical conditions about the Hopf bifurcation of the equivalent deterministic system are obtained.At the same time the influence of multisource stochastic factors on the Hopf bifurcation for the proposed system is explored.Finally,the theorical results are verified by the numerical simulations.展开更多
Stochastic period-doubling bifurcation is explored in a forced Duffing system with a bounded random parameter as an additional weak harmonic perturbation added to the system. Firstly, the biharmonic driven Duffing sys...Stochastic period-doubling bifurcation is explored in a forced Duffing system with a bounded random parameter as an additional weak harmonic perturbation added to the system. Firstly, the biharmonic driven Duffing system with a random parameter is reduced to its equivalent deterministic one, and then the responses of the stochastic system can be obtained by available effective numerical methods. Finally, numerical simulations show that the phase of the additional weak harmonic perturbation has great influence on the stochastic period-doubling bifurcation in the biharmonic driven Duffing system. It is emphasized that, different from the deterministic biharmonic driven Duffing system, the intensity of random parameter in the Duffing system can also be taken as a bifurcation parameter, which can lead to the stochastic period-doubling bifurcations.展开更多
Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite th...Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite the integral role this active transport mode plays,it is unfortunately associated with a high risk of fatalities in the event of a traffic crash as they are not protected.Many studies have been conducted in several jurisdictions to examine the factors contributing to crashes involving these vulnerable road users.In the case of Louisiana which is currently experiencing increased cases of severe and fatal bicycleinvolved crashes,less attention has been paid to investigating the critical factors influencing bicyclist injury severity outcomes using more detailed data and advanced econometric modeling frameworks to help propose adequate policies to improve the safety of riders.Against this background,this study examined the key contributing factors influencing bicyclist injuries by using more detailed roadway crash data spanning 2010-2016 obtained from the state of Louisiana.The study then applies an advanced random parameter logit modeling with heterogeneity in means and variances to address the unobserved heterogeneity issue associated with traffic crash data.To overcome the imbalanced data issue,three major crash injury levels were used instead of the conventional five crash injury levels.Besides,the data groups classified under each injury level were compared for the final variable selection.The study found that distracted drivers,elderly bicyclists,careless operations,and riding in dark conditions increase the probability of having severe injuries in vehicle-bicyclist crashes.Moreover,the variables for straight-level roadways and city streets decrease the odds of severe injuries.The straight-level roadway may provide better sight distance for both drivers and bicyclists,and complex environments like city streets discourage crashes with severe injuries.展开更多
The consequences of flight delay can significantly impact airports’ on‐time performance and airline operations, which have a strong positive correlation with passenger satisfaction. Thus, an accurate investigation o...The consequences of flight delay can significantly impact airports’ on‐time performance and airline operations, which have a strong positive correlation with passenger satisfaction. Thus, an accurate investigation of the variables that cause delays is of main importance in decision-making processes. Although statistical models have been traditionally used in flight delay analysis, the presence of unobserved heterogeneity in flight data has been less discussed. This study carried out an empirical analysis to investigate the potential unobserved heterogeneity and the impact of significant variables on flight delay using two modeling approaches. First, preliminary insight into potential significant variables was obtained through a random parameter logit model (also known as the mixed logit model). Then, a Support Vector Machines (SVM) model trained by the Artificial Bee Colony (ABC) algorithm, was employed to explore the non-linear relationship between flight delay outcomes and causal factors. The data-driven analysis was conducted using three-month flight arrival data from Miami International Airport (MIA). A variable impact analysis was also conducted considering the black-box characteristic of the SVM and compared to the effects of variables indented through the random parameter logit modeling framework. While a large unobserved heterogeneity was observed, the impacts of various explanatory variables were examined in terms of flight departure performance, geographical specification of the origin airport, day of month and day of week of the flight, cause of delay, and gate information. The comprehensive assessment of the contributing factors proposed in this study provides invaluable insights into flight delay modeling and analysis.展开更多
The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored.This study collected a four-year crash dataset(2015–2018)from South Australia to explore this issue.T...The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored.This study collected a four-year crash dataset(2015–2018)from South Australia to explore this issue.The data shows 3,812 and 1,086 crashes at sealed and unsealed pavement surfaces,respectively,during those years.This study examines the consequence of sealed and unsealed pavements on driver injury severity outcomes of motor vehicle crashes.A mixed logit model was developed by accounting for heterogeneity in means and variances of the random parameters.The variables were distributed among several categories:driver,temporal,spatial,roadway characteristics,crash type,vehicle type,and vehicle movement.Four random parameters were observed in the sealed model,whereas five parameters were in the unsealed one.Moreover,the sealed pavements model showed substantial heterogeneity in means of four of the random parameters,while the unsealed pavements model has some heterogeneity in both means and variances of some of the random parameters.Marginal effect results indicate that two indicator variables have enlarged the likelihood of driver severe injury consequences in sealed,alcohol involvement and posted speed limit>100 km/hr.Additionally,four other significant variables sustain the probability of severe injury outcomes at unsealed pavement like male drivers,middle-aged drivers,rollover crash types,and crashes at straight roads.Based on these variables,various countermeasures were recommended to enhance the safety of both types of pavements.展开更多
This research investigates the intricate relationship between the number of lanes on highways and injury severities sustained by commercial motor vehicle(CMV)drivers.Many studies have addressed crash determinants,but ...This research investigates the intricate relationship between the number of lanes on highways and injury severities sustained by commercial motor vehicle(CMV)drivers.Many studies have addressed crash determinants,but the safety implications of differing numbers of lanes remain insufficiently examined,especially during the highway planning stages.Our study fills this knowledge gap by analyzing injury severity crash factors for a varied number of lane scenarios.Employing a random parameter logit modeling framework,we differentiated injury levels for 2-4 lanes and 6-10 lanes.Key factors were identified for each number of lanes,with older,loss of vehicle control,non-collision crashes,and crashes,on locations where grade or hill existed,being more perilous and increasing the risk of sustaining severe injuries on 2-lane highways.For 4-lane highways,factors such as non-Oregonian drivers,older drivers,crashes that occurred during the spring season,and crashes that occurred beyond shoulders were associated with an elevated probability of being involved in severe injury crashes.Regarding highways with 6 lanes and higher,driving too fast for conditions and driver error(drowsy,fatigued,inattentive,or reckless)increases the odds of being involved in higher levels of injury crashes.To enhance truck driver safety,we recommend the implementation of electronic stability control in CMVs,with moderated speeds on graded sections,improved curve markers,and robust public safety campaigns.展开更多
It has been extensively recognized that the engineering structures are becoming increasingly precise and complex,which makes the requirements of design and analysis more and more rigorous.Therefore the uncertainty eff...It has been extensively recognized that the engineering structures are becoming increasingly precise and complex,which makes the requirements of design and analysis more and more rigorous.Therefore the uncertainty effects are indispensable during the process of product development.Besides,iterative calculations,which are usually unaffordable in calculative efforts,are unavoidable if we want to achieve the best design.Taking uncertainty effects into consideration,matrix perturbation methodpermits quick sensitivity analysis and structural dynamic re-analysis,it can also overcome the difficulties in computational costs.Owing to the situations above,matrix perturbation method has been investigated by researchers worldwide recently.However,in the existing matrix perturbation methods,correlation coefficient matrix of random structural parameters,which is barely achievable in engineering practice,has to be given or to be assumed during the computational process.This has become the bottleneck of application for matrix perturbation method.In this paper,we aim to develop an executable approach,which contributes to the application of matrix perturbation method.In the present research,the first-order perturbation of structural vibration eigenvalues and eigenvectors is derived on the basis of the matrix perturbation theory when structural parameters such as stiffness and mass have changed.Combining the first-order perturbation of structural vibration eigenvalues and eigenvectors with the probability theory,the variance of structural random eigenvalue is derived from the perturbation of stiffness matrix,the perturbation of mass matrix and the eigenvector of baseline-structure directly.Hence the Direct-VarianceAnalysis(DVA)method is developed to assess the variation range of the structural random eigenvalues without correlation coefficient matrix being involved.The feasibility of the DVA method is verified with two numerical examples(one is trusssystem and the other is wing structure of MA700 commercial aircraft),in which the DVA method also shows superiority in computational efficiency when compared to the Monte-Carlo method.展开更多
Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Desi...Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Design/methodology/approach–The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations.The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs,respectively,as well as accommodating the heterogeneity issue simultaneously.Findings–The findings show that day,location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.Originality/value–The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.展开更多
Interfacial transition zones （ITZs） between aggregates and mortar are the weakest parts in concrete. The random aggregate generation and packing algorithm was utilized to create a two-phase concrete model, and the z...Interfacial transition zones （ITZs） between aggregates and mortar are the weakest parts in concrete. The random aggregate generation and packing algorithm was utilized to create a two-phase concrete model, and the zero-thickness cohesive elements with different normal distribution parameters were used to model the ITZs with random mechanical properties. A number of uniaxial tension-induced fracture simulations were carried out, and the effects of the random parameters on the fracture behavior of concrete were statistically analyzed. The results show that, different from the dissipated fracture energy, the peak load of concrete does not always obey a normal distribution, when the elastic stiffness, tensile strength, or fracture energy of ITZs is normally distributed. The tensile strength of the ITZs has a significant effect on the fracture behavior of concrete, and its large standard deviation leads to obvious diversity of the fracture path in both location and shape.展开更多
Despite the importance of heavy vehicles in Australia’s transportation system,little is known on the factors influencing injury severity from accidents involving a single heavy vehicle.Heavy vehicular crashes have be...Despite the importance of heavy vehicles in Australia’s transportation system,little is known on the factors influencing injury severity from accidents involving a single heavy vehicle.Heavy vehicular crashes have been one of the main causes of fatal injuries in Australia,and this raises safety concerns for transport authorities,insurance companies,and emergency services.Although there have been several potential attempts to identify the factors contributing to heavy vehicle crashes and injury severity,it is still necessary to reduce the number of traffic crashes and lower the fatality rate involving heavy vehicles.The aims of this study were investigating the effects of heavy trucks’presence in accidents on the injury severity level sustained by the vehicle driver and detecting the contributing factors that lead to specific injury severity levels.Fixed-and random-parameter ordered probit and logit models were applied for predicting the likelihood of three injury severity categories severe,moderate,and no injury based on data from crashes caused by heavy trucks in Victoria,Australia in 2012-2017.The results showed that the random-parameter ordered probit model performed better than the other models did.Twenty variables(i.e.,factors)were found to be significant,and 12 of them were found to have random parameters that were normally distributed.Since some of the investigated factors had different effects on the type of injury severity in Australia,this paper does not recommend generalizing the findings from other case studies.Based on the findings,Victoria state authorities can have insight and enhanced understanding of the specific factors that lead to various types of injury severity involving heavy trucks.Consequently,the safety of all road users,including heavy vehicle drivers,can be enhanced.展开更多
With the increased frequency of extreme weather events and large-scale disasters, extensive societal and economic losses incur every year due to damage of infrastructure and private properties, business disruptions,fa...With the increased frequency of extreme weather events and large-scale disasters, extensive societal and economic losses incur every year due to damage of infrastructure and private properties, business disruptions,fatalities, homelessness, and severe health-related issues. In this article, we analyze the economic and disaster data from1970 through 2010 to investigate the impact of disasters on country/region-level economic growth. We leveraged a random parameter modeling approach to develop the growth-econometrics model that identifies risk factors significantly influencing the country/region-level economic growth in the face of natural hazard-induced disasters,while controlling for country/region-and time-specific unobserved heterogeneities. We found that disaster intensity in terms of fatalities and homelessness, and economic characteristics such as openness to trade and a government's consumption share of purchasing power parity(PPP), are the significant risk factors that randomly vary for different countries/regions. Other significant factors found to be significant include population, real gross domestic product(GDP), and investment share of PPP converted GDP per capita. We also found that flood is the most devastating disaster to affect country/region-level economic growth. This growth-econometrics model will help in the policy and decision making of governmentsrelated to the investment needs for pre-and post-disaster risk mitigation and response planning strategies, to better protect nations and minimize disaster-induced economic impacts.展开更多
The management of the coastal park environment is a major ecological and economic development issue. In developing effective policies, relevant information is essential, especially the economic valuation of various re...The management of the coastal park environment is a major ecological and economic development issue. In developing effective policies, relevant information is essential, especially the economic valuation of various recreation-related environmental attributes. This study used Dalian coastal parks as a pilot study area and estimated the willingness to pay(WTP) of tourists using three different discrete choice models. In this study, we analyzed the preference heterogeneity among the respondents regarding a combination of park attributes, and the individual respondent’s WTP values were estimated for each attribute. The results indicate that water quality amelioration and trash reduction had the highest economic values among the given attribute factors. In addition, the estimated tourist WTP varied considerably among different segments, such as among the visitors who preferred different recreational activities. These findings provide valuable information that will allow coastal park managers to develop policies which maintain a balance between tourism development and improvement of the coastal environment.展开更多
This study aimed to explore traffic safety climate by quantifying driving conditions and driving behaviour.To achieve the objective,the random parameter structural equation model was proposed so that driver action and...This study aimed to explore traffic safety climate by quantifying driving conditions and driving behaviour.To achieve the objective,the random parameter structural equation model was proposed so that driver action and driving condition can address the safety climate by integrating crash features,vehicle profiles,roadway conditions and environment conditions.The geo-localized crash open data of Las Vegas metropolitan area were collected from 2014 to 2016,including 27 arterials with 16827 injury samples.By quantifying the driving conditions and driving actions,the random parameter structural equation model was built up with measurement variables and latent variables.Results revealed that the random parameter structural equation model can address traffic safety climate quantitatively,while driving conditions and driving actions were quantified and reflected by vehicles,road environment and crash features correspondingly.The findings provide potential insights for practitioners and policy makers to improve the driving environment and traffic safety culture.展开更多
基金Project supported by the Major Program of the National Natural Science Foundation of China, China （Grant No 10332030）, the National Natural Science Foundation of China （Grant No 10472091）, and the Graduate Starting Seed Fund of Northwestern Polytechnical University, China （Grant No Z200655）.
文摘In this paper, the Chebyshev polynomial approximation is applied to the problem of stochastic period-doubling bifurcation of a stochastic Bonhoeffer-van der Pol （BVP for short） system with a bounded random parameter. In the analysis, the stochastic BVP system is transformed by the Chebyshev polynomial approximation into an equivalent deterministic system, whose response can be readily obtained by conventional numerical methods. In this way we have explored plenty of stochastic period-doubling bifurcation phenomena of the stochastic BVP system. The numerical simulations show that the behaviour of the stochastic period-doubling bifurcation in the stochastic BVP system is by and large similar to that in the deterministic mean-parameter BVP system, but there are still some featured differences between them. For example, in the stochastic dynamic system the period-doubling bifurcation point diffuses into a critical interval and the location of the critical interval shifts with the variation of intensity of the random parameter. The obtained results show that Chebyshev polynomial approximation is an effective approach to dynamical problems in some typical nonlinear systems with a bounded random parameter of an arch-like probability density function.
基金The National Key Research and Development Program of China(No.2017YFC0803902).
文摘In order to analyze the risky factors that affect vehicle-cyclist crash injury severity at the intersection area,especially the factors relating to the road users behaviors,an empirical study was conducted by collecting accident records from 2011 to 2015 from the General Estimates System.After preliminary screening,the variables were classified into 5 main categories including cyclists characteristic and behavior,drivers characteristic and behavior,vehicle characteristic,intersection condition,and time.The random parameter ordinal probit(RPOP)was used to study the significant influencing factors and corresponding heterogeneity.The results show that failing to obey traffic signals,failing to yield to right-of-way,dash and drinking before cycling can increase the injury severity for cyclists,and the corresponding fatal injury likelihoods increase by 53.2%,40.0%,86.3%,and 211.5%,respectively.Moreover,drivers inattention,speeding,going straight and left turning increase the risk of crashing for cyclists.The corresponding fatal injury likelihoods increase by 134.5%,186.5%,69.3%,and 22.7%,respectively.Other indicators such as age,gender,vehicle type,traffic signal and intersection type can also affect injury severity.
基金Southeast Asia Regional Center for Graduate Study and Research Agriculture(SEARCA)provide me the financial support to conduct this research.
文摘Despite the number of studies focusing on the financial analysis of production activities, conducting on technical solutions, and improving water quality, no study has been conducted on the application of economic instruments that apply to water quality management in craft villages, and several studies of WTP also. This study aimed to estimate the households’ willingness-to-pay for wastewater treatment in selected traditional agro-food processing villages in Nhue-Day River Basin, Vietnam. A pilot Choice Experiment (CE) technique in Choice Modelling (CM) approach was applied for this study with 267 selected agro-food processing households by using the conditional logit (CL) and random parameter logit (RPL) models. The results showed that total annual environmental fee for wastewater treatment from agro-food processing households is estimated as 1089 million VND (equal to US$47,868 per year) for the total of 902 agro-food processing households in three research sites in Nhue-Day River Basin. This estimated budget for wastewater treatment accounted for 55.85% of total annual operation and maintenance costs only. In addition, the technology is improved to enable 90% of treated wastewater. Overall, the results of this study suggest the new wastewater treatment plant construction and improved wastewater collection system by increasing the investment in order to improve the water quality in Nhue-Day River Basin that brings about the reducing environmental degradation, biodiversity loss and human health risks.
文摘A Monte Carlo method was used to take thorough account of the influences of different reactivity ratios and initial feed compositions on copolymer microstructure.The model proves the lack of azeotropic behavior in systems in which r_A>1 and r_B<1 or vice versa;it is also able to calculate the drift in the copolymer properties:copolymer composition,and randomness parameter.Moreover,for each reactivity ratio pair given,there is a unique reaction conversion,at which macromolecules produced inherit their ...
基金Project supported by the National Natural Science Foundation of China (Grant No. 10872165)
文摘This paper aims to study the stochastic period-doubling bifurcation of the three-dimensional Rossler system with an arch-like bounded random parameter. First, we transform the stochastic RSssler system into its equivalent deterministic one in the sense of minimal residual error by the Chebyshev polynomial approximation method. Then, we explore the dynamical behaviour of the stochastic RSssler system through its equivalent deterministic system by numerical simulations. The numerical results show that some stochastic period-doubling bifurcation, akin to the conventional one in the deterministic case, may also appear in the stochastic Rossler system. In addition, we also examine the influence of the random parameter intensity on bifurcation phenomena in the stochastic Rossler system.
基金This work was supported by the grants from the National Nat-ural Science Foundation of China(No.11772002)Ningxia higher education first-class discipline construction funding project(No.NXYLXK2017B09)+2 种基金Major Special project of North Minzu University(No.ZDZX201902)Open project of The Key Laboratory of In-telligent Information and Big Data Processing of NingXia Province(No.2019KLBD008)Postgraduate Innovation Project of North Minzu University(No.YCX22099).
文摘The article mainly explores the Hopf bifurcation of a kind of nonlinear system with Gaussian white noise excitation and bounded random parameter.Firstly,the nonlinear system with multisource stochastic fac-tors is reduced to an equivalent deterministic nonlinear system by the sequential orthogonal decomposi-tion method and the Karhunen-Loeve(K-L)decomposition theory.Secondly,the critical conditions about the Hopf bifurcation of the equivalent deterministic system are obtained.At the same time the influence of multisource stochastic factors on the Hopf bifurcation for the proposed system is explored.Finally,the theorical results are verified by the numerical simulations.
基金Project supported by the National Natural Science Foundation of China(Grant Nos10472091and10332030)
文摘Stochastic period-doubling bifurcation is explored in a forced Duffing system with a bounded random parameter as an additional weak harmonic perturbation added to the system. Firstly, the biharmonic driven Duffing system with a random parameter is reduced to its equivalent deterministic one, and then the responses of the stochastic system can be obtained by available effective numerical methods. Finally, numerical simulations show that the phase of the additional weak harmonic perturbation has great influence on the stochastic period-doubling bifurcation in the biharmonic driven Duffing system. It is emphasized that, different from the deterministic biharmonic driven Duffing system, the intensity of random parameter in the Duffing system can also be taken as a bifurcation parameter, which can lead to the stochastic period-doubling bifurcations.
文摘Bicycling has been actively promoted as a clean and efficient mode of commute.Besides,due to the personal and societal benefits it provides,it has been adopted by many city dwellers for short-distance trips.Despite the integral role this active transport mode plays,it is unfortunately associated with a high risk of fatalities in the event of a traffic crash as they are not protected.Many studies have been conducted in several jurisdictions to examine the factors contributing to crashes involving these vulnerable road users.In the case of Louisiana which is currently experiencing increased cases of severe and fatal bicycleinvolved crashes,less attention has been paid to investigating the critical factors influencing bicyclist injury severity outcomes using more detailed data and advanced econometric modeling frameworks to help propose adequate policies to improve the safety of riders.Against this background,this study examined the key contributing factors influencing bicyclist injuries by using more detailed roadway crash data spanning 2010-2016 obtained from the state of Louisiana.The study then applies an advanced random parameter logit modeling with heterogeneity in means and variances to address the unobserved heterogeneity issue associated with traffic crash data.To overcome the imbalanced data issue,three major crash injury levels were used instead of the conventional five crash injury levels.Besides,the data groups classified under each injury level were compared for the final variable selection.The study found that distracted drivers,elderly bicyclists,careless operations,and riding in dark conditions increase the probability of having severe injuries in vehicle-bicyclist crashes.Moreover,the variables for straight-level roadways and city streets decrease the odds of severe injuries.The straight-level roadway may provide better sight distance for both drivers and bicyclists,and complex environments like city streets discourage crashes with severe injuries.
文摘The consequences of flight delay can significantly impact airports’ on‐time performance and airline operations, which have a strong positive correlation with passenger satisfaction. Thus, an accurate investigation of the variables that cause delays is of main importance in decision-making processes. Although statistical models have been traditionally used in flight delay analysis, the presence of unobserved heterogeneity in flight data has been less discussed. This study carried out an empirical analysis to investigate the potential unobserved heterogeneity and the impact of significant variables on flight delay using two modeling approaches. First, preliminary insight into potential significant variables was obtained through a random parameter logit model (also known as the mixed logit model). Then, a Support Vector Machines (SVM) model trained by the Artificial Bee Colony (ABC) algorithm, was employed to explore the non-linear relationship between flight delay outcomes and causal factors. The data-driven analysis was conducted using three-month flight arrival data from Miami International Airport (MIA). A variable impact analysis was also conducted considering the black-box characteristic of the SVM and compared to the effects of variables indented through the random parameter logit modeling framework. While a large unobserved heterogeneity was observed, the impacts of various explanatory variables were examined in terms of flight departure performance, geographical specification of the origin airport, day of month and day of week of the flight, cause of delay, and gate information. The comprehensive assessment of the contributing factors proposed in this study provides invaluable insights into flight delay modeling and analysis.
文摘The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored.This study collected a four-year crash dataset(2015–2018)from South Australia to explore this issue.The data shows 3,812 and 1,086 crashes at sealed and unsealed pavement surfaces,respectively,during those years.This study examines the consequence of sealed and unsealed pavements on driver injury severity outcomes of motor vehicle crashes.A mixed logit model was developed by accounting for heterogeneity in means and variances of the random parameters.The variables were distributed among several categories:driver,temporal,spatial,roadway characteristics,crash type,vehicle type,and vehicle movement.Four random parameters were observed in the sealed model,whereas five parameters were in the unsealed one.Moreover,the sealed pavements model showed substantial heterogeneity in means of four of the random parameters,while the unsealed pavements model has some heterogeneity in both means and variances of some of the random parameters.Marginal effect results indicate that two indicator variables have enlarged the likelihood of driver severe injury consequences in sealed,alcohol involvement and posted speed limit>100 km/hr.Additionally,four other significant variables sustain the probability of severe injury outcomes at unsealed pavement like male drivers,middle-aged drivers,rollover crash types,and crashes at straight roads.Based on these variables,various countermeasures were recommended to enhance the safety of both types of pavements.
文摘This research investigates the intricate relationship between the number of lanes on highways and injury severities sustained by commercial motor vehicle(CMV)drivers.Many studies have addressed crash determinants,but the safety implications of differing numbers of lanes remain insufficiently examined,especially during the highway planning stages.Our study fills this knowledge gap by analyzing injury severity crash factors for a varied number of lane scenarios.Employing a random parameter logit modeling framework,we differentiated injury levels for 2-4 lanes and 6-10 lanes.Key factors were identified for each number of lanes,with older,loss of vehicle control,non-collision crashes,and crashes,on locations where grade or hill existed,being more perilous and increasing the risk of sustaining severe injuries on 2-lane highways.For 4-lane highways,factors such as non-Oregonian drivers,older drivers,crashes that occurred during the spring season,and crashes that occurred beyond shoulders were associated with an elevated probability of being involved in severe injury crashes.Regarding highways with 6 lanes and higher,driving too fast for conditions and driver error(drowsy,fatigued,inattentive,or reckless)increases the odds of being involved in higher levels of injury crashes.To enhance truck driver safety,we recommend the implementation of electronic stability control in CMVs,with moderated speeds on graded sections,improved curve markers,and robust public safety campaigns.
基金supported by the AVIC Research Project(Grant No.cxy2012BH07)the National Natural Science Foundation of China(Grant Nos.10872017,90816024,10876100)+1 种基金the Defense Industrial Technology Development Program(Grant Nos.A2120110001,B2120110011,A082013-2001)"111" Project(Grant No.B07009)
文摘It has been extensively recognized that the engineering structures are becoming increasingly precise and complex,which makes the requirements of design and analysis more and more rigorous.Therefore the uncertainty effects are indispensable during the process of product development.Besides,iterative calculations,which are usually unaffordable in calculative efforts,are unavoidable if we want to achieve the best design.Taking uncertainty effects into consideration,matrix perturbation methodpermits quick sensitivity analysis and structural dynamic re-analysis,it can also overcome the difficulties in computational costs.Owing to the situations above,matrix perturbation method has been investigated by researchers worldwide recently.However,in the existing matrix perturbation methods,correlation coefficient matrix of random structural parameters,which is barely achievable in engineering practice,has to be given or to be assumed during the computational process.This has become the bottleneck of application for matrix perturbation method.In this paper,we aim to develop an executable approach,which contributes to the application of matrix perturbation method.In the present research,the first-order perturbation of structural vibration eigenvalues and eigenvectors is derived on the basis of the matrix perturbation theory when structural parameters such as stiffness and mass have changed.Combining the first-order perturbation of structural vibration eigenvalues and eigenvectors with the probability theory,the variance of structural random eigenvalue is derived from the perturbation of stiffness matrix,the perturbation of mass matrix and the eigenvector of baseline-structure directly.Hence the Direct-VarianceAnalysis(DVA)method is developed to assess the variation range of the structural random eigenvalues without correlation coefficient matrix being involved.The feasibility of the DVA method is verified with two numerical examples(one is trusssystem and the other is wing structure of MA700 commercial aircraft),in which the DVA method also shows superiority in computational efficiency when compared to the Monte-Carlo method.
基金National Natural Science Foundation of China(No.52072214)the project of Tsinghua University-Toyota Joint Research Center for AI technology of Automated Vehicle(No.TTAD2021-10).
文摘Purpose–This study aims to investigate the safety and liability of autonomous vehicles(AVs),and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.Design/methodology/approach–The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations.The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs,respectively,as well as accommodating the heterogeneity issue simultaneously.Findings–The findings show that day,location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.Originality/value–The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.
基金supported by the National Basic Research Program of China (973 Program:2011CB013800)
文摘Interfacial transition zones （ITZs） between aggregates and mortar are the weakest parts in concrete. The random aggregate generation and packing algorithm was utilized to create a two-phase concrete model, and the zero-thickness cohesive elements with different normal distribution parameters were used to model the ITZs with random mechanical properties. A number of uniaxial tension-induced fracture simulations were carried out, and the effects of the random parameters on the fracture behavior of concrete were statistically analyzed. The results show that, different from the dissipated fracture energy, the peak load of concrete does not always obey a normal distribution, when the elastic stiffness, tensile strength, or fracture energy of ITZs is normally distributed. The tensile strength of the ITZs has a significant effect on the fracture behavior of concrete, and its large standard deviation leads to obvious diversity of the fracture path in both location and shape.
文摘Despite the importance of heavy vehicles in Australia’s transportation system,little is known on the factors influencing injury severity from accidents involving a single heavy vehicle.Heavy vehicular crashes have been one of the main causes of fatal injuries in Australia,and this raises safety concerns for transport authorities,insurance companies,and emergency services.Although there have been several potential attempts to identify the factors contributing to heavy vehicle crashes and injury severity,it is still necessary to reduce the number of traffic crashes and lower the fatality rate involving heavy vehicles.The aims of this study were investigating the effects of heavy trucks’presence in accidents on the injury severity level sustained by the vehicle driver and detecting the contributing factors that lead to specific injury severity levels.Fixed-and random-parameter ordered probit and logit models were applied for predicting the likelihood of three injury severity categories severe,moderate,and no injury based on data from crashes caused by heavy trucks in Victoria,Australia in 2012-2017.The results showed that the random-parameter ordered probit model performed better than the other models did.Twenty variables(i.e.,factors)were found to be significant,and 12 of them were found to have random parameters that were normally distributed.Since some of the investigated factors had different effects on the type of injury severity in Australia,this paper does not recommend generalizing the findings from other case studies.Based on the findings,Victoria state authorities can have insight and enhanced understanding of the specific factors that lead to various types of injury severity involving heavy trucks.Consequently,the safety of all road users,including heavy vehicle drivers,can be enhanced.
文摘With the increased frequency of extreme weather events and large-scale disasters, extensive societal and economic losses incur every year due to damage of infrastructure and private properties, business disruptions,fatalities, homelessness, and severe health-related issues. In this article, we analyze the economic and disaster data from1970 through 2010 to investigate the impact of disasters on country/region-level economic growth. We leveraged a random parameter modeling approach to develop the growth-econometrics model that identifies risk factors significantly influencing the country/region-level economic growth in the face of natural hazard-induced disasters,while controlling for country/region-and time-specific unobserved heterogeneities. We found that disaster intensity in terms of fatalities and homelessness, and economic characteristics such as openness to trade and a government's consumption share of purchasing power parity(PPP), are the significant risk factors that randomly vary for different countries/regions. Other significant factors found to be significant include population, real gross domestic product(GDP), and investment share of PPP converted GDP per capita. We also found that flood is the most devastating disaster to affect country/region-level economic growth. This growth-econometrics model will help in the policy and decision making of governmentsrelated to the investment needs for pre-and post-disaster risk mitigation and response planning strategies, to better protect nations and minimize disaster-induced economic impacts.
基金The National Natural Science Foundation of China (71640023)。
文摘The management of the coastal park environment is a major ecological and economic development issue. In developing effective policies, relevant information is essential, especially the economic valuation of various recreation-related environmental attributes. This study used Dalian coastal parks as a pilot study area and estimated the willingness to pay(WTP) of tourists using three different discrete choice models. In this study, we analyzed the preference heterogeneity among the respondents regarding a combination of park attributes, and the individual respondent’s WTP values were estimated for each attribute. The results indicate that water quality amelioration and trash reduction had the highest economic values among the given attribute factors. In addition, the estimated tourist WTP varied considerably among different segments, such as among the visitors who preferred different recreational activities. These findings provide valuable information that will allow coastal park managers to develop policies which maintain a balance between tourism development and improvement of the coastal environment.
基金supported by National Natural Science Foundation of China(No.52072214).
文摘This study aimed to explore traffic safety climate by quantifying driving conditions and driving behaviour.To achieve the objective,the random parameter structural equation model was proposed so that driver action and driving condition can address the safety climate by integrating crash features,vehicle profiles,roadway conditions and environment conditions.The geo-localized crash open data of Las Vegas metropolitan area were collected from 2014 to 2016,including 27 arterials with 16827 injury samples.By quantifying the driving conditions and driving actions,the random parameter structural equation model was built up with measurement variables and latent variables.Results revealed that the random parameter structural equation model can address traffic safety climate quantitatively,while driving conditions and driving actions were quantified and reflected by vehicles,road environment and crash features correspondingly.The findings provide potential insights for practitioners and policy makers to improve the driving environment and traffic safety culture.
