In this paper, some experimental studies on the impact of effluent from an exhaust tower of an underground tunnel with special construction are reported. By measuring the flow field downstream of the tower in NJU mete...In this paper, some experimental studies on the impact of effluent from an exhaust tower of an underground tunnel with special construction are reported. By measuring the flow field downstream of the tower in NJU meteorological wind tunnel, some flow characteristics in the make area were established. Based on these, an advanced random\|walk dispersion model was set up and applied successfully to the simulation of dispersion in the wake area. The modelling results were in accordance with wind tunnel measurements. The computed maximum of ground surface concentration in the building case was a factor of 3-4 higher than that in the flat case and appeared much closer to the source. The simulation indicated that random walk modelling is an effective and practical tool for the wake stream impact assessment.展开更多
Very recently, we have applied the random walk model to fit the global temperature anomaly, CRUTEM3. With encouraging results, we apply the random walk model to fit the temperature walk that is the conversion of recor...Very recently, we have applied the random walk model to fit the global temperature anomaly, CRUTEM3. With encouraging results, we apply the random walk model to fit the temperature walk that is the conversion of recorded tem-perature and real recorded temperature in 46 gamma world cities from 1901 to 1998 in this study. The results show that the random walk model can fit both temperature walk and real recorded temperature although the fitted results from other climate models are unavailable for comparison in these 46 cities. Therefore, the random walk model can fit not only the global temperature anomaly, but also the real recorded temperatures in various cities around the world.展开更多
To simulate the pollutant transport with seif-purification in inland waters,the widely used random walk model(RWM)is modified to include a source term for the degradation and to consider the impact of land boundaries....To simulate the pollutant transport with seif-purification in inland waters,the widely used random walk model(RWM)is modified to include a source term for the degradation and to consider the impact of land boundaries.The source term for the degradation is derived from the assumption of the first-order reaction kinetics.Parameters for the new model are determined by a comparison to the analytical results.The proposed model is then applied to simulate and analyze the transport of a test pollutant and its spatial distribution in a large reservoir in northeast China.Reasonable results are obtained,and the effects of the runoff,the flow structure,and the wind on the pollutant transport are analyzed.The results may help the risk assessment and the management of the water pollution in inland waters.展开更多
A numerical model has been developed to simulate the transport and fate of oil spilled at sea. The model combines the transport and fate processes of spilled oil with the random walk technique. Oil movement under th...A numerical model has been developed to simulate the transport and fate of oil spilled at sea. The model combines the transport and fate processes of spilled oil with the random walk technique. Oil movement under the influence of tidal currents, wind driven currents, and turbulent eddies is simulated by the PLUME RW dispersion model developed by HR Wallingford. The weathering processes in the model represent physical and chemical changes of soil slicks with time, and comprise mechanical spreading, dispersion, evaporation and emulsification. Shoreline stranding is determined approximately using a capacity method for different shoreline types. This paper presents details of the model, and describe the results of various sensitivity tests. The model is suitable for oil spill contingency planning.展开更多
According to random walk, in this paper, we propose a new traffic model for scheduling trains on a railway network. In the proposed method, using some iteration rules for walkers, the departure and the arrival times o...According to random walk, in this paper, we propose a new traffic model for scheduling trains on a railway network. In the proposed method, using some iteration rules for walkers, the departure and the arrival times of trains at each station are determined. We test the proposed method on an assumed railway network. The numerical simulations and the analytical results demonstrate that the proposed method provides an effective tool for scheduling trains. Some characteristic behaviours of train movement can be reproduced, such as train delay.展开更多
A novel immunization strategy called the random walk immunization strategy on scale-free networks is proposed. Different from other known immunization strategies, this strategy works as follows： a node is randomly ch...A novel immunization strategy called the random walk immunization strategy on scale-free networks is proposed. Different from other known immunization strategies, this strategy works as follows： a node is randomly chosen from the network. Starting from this node, randomly walk to one of its neighbor node; if the present node is not immunized, then immunize it and continue the random walk; otherwise go back to the previous node and randomly walk again. This process is repeated until a certain fraction of nodes is immunized. By theoretical analysis and numerical simulations, we found that this strategy is very effective in comparison with the other known immunization strategies.展开更多
It is presented here a continuous time random walk model for diffusion mediated reactions with both species mobile. The random walk is carried out over an infinite homogeneouos lattice. They are calculated the probabi...It is presented here a continuous time random walk model for diffusion mediated reactions with both species mobile. The random walk is carried out over an infinite homogeneouos lattice. They are calculated the probability density for the time of reaction of a pair, the reaction rate and the time evolution of the concentration of the majority species. Analytical results are obtained in the Fourier-Laplace transform representation. Known results for a fixed trap are reobtained with appropriate marginal probabilities. It is thus justified Smoluchowski’s original approximation considering the trap at a fixed position and the majority species diffusing with a coefficient sum of the individual coefficients. The results obtained are illustrated by a one dimensional model with bias.展开更多
社交网络中,节点间存在多种关系类型,节点数量会随着时间的推移而变化,这种异质性和动态性给链路预测任务带来极大的挑战。因此,本文提出一种基于增量学习的社交网络链路预测方法(incremental learning social networks link prediction...社交网络中,节点间存在多种关系类型,节点数量会随着时间的推移而变化,这种异质性和动态性给链路预测任务带来极大的挑战。因此,本文提出一种基于增量学习的社交网络链路预测方法(incremental learning social networks link prediction,IL-SNLP)。通过对网络进行分层,使每一层网络只包含一种关系类型,以更好地获取节点在每种关系类型下的语义信息;针对网络的动态性,利用时序随机游走捕获社交网络中的局部结构信息和时序信息;针对增量数据,采用增量式更新随机游走策略对历史随机游走序列进行更新。通过增量式skip-gram模型从随机游走序列中提取新出现节点的特征,并进一步更新历史节点的特征;针对网络的异质性,采用概率模型提取不同关系类型之间的因果关系关联程度,并将其作用于每一层的节点特征,以改善不同关系层下节点特征表现能力;利用多层感知机构建节点相互感知器,挖掘节点间建立连接时的相互贡献,实现更高的链路预测准确率。实验结果表明,在3个真实的社交网络数据集上,IL-SNLP方法的ROC曲线下的面积(AUC)和F1分数比基线方法分别提高了10.08%~67.60%和1.76%~64.67%,提升了预测性能;对于增量数据,只需要少次迭代就能保持预测模型的性能,提高了模型训练的速度;与未采用增量学习技术的IL-SNLP−方法相比,IL-SNLP方法在时间效率上提升了30.78%~257.58%,显著缩短了模型的运行时长。展开更多
This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random ...This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation （FFPE） with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior.展开更多
Stock market trading is an activity in which investors need fast and accurate information to make effective decisions.But the fact is that forecasting stock prices by using various models has been suffering from low a...Stock market trading is an activity in which investors need fast and accurate information to make effective decisions.But the fact is that forecasting stock prices by using various models has been suffering from low accuracy,slow convergence,and complex parameters.This study aims to employ a mixed model to improve the accuracy of stock price prediction.We present how to use a random walk based on jump-diffusion,to obtain stock predictions with a good-fitting degree by adjusting different parameters.Aimed at getting better parameters and then using the time series model to predict the data,we employed the time series model to smooth the sequence utilizing logarithm and difference,which successfully resulted in drawing the auto-correlation figure and partial the auto-correlation figure.According to the comparative analysis,which focuses on checking the mean absolute error,including root mean square error and R square evaluation index,we have drawn a clear conclusion that our mixed model prediction effect is relatively good.In the context of Chinese stocks,the hybrid random walk model is very suitable for predicting stocks.It can“interpret”the randomness of stocks very well,and it also has an unparalleled prediction effect compared with other models.Based on the time series model’s application in this paper,the abovementioned series is more suitable for predicting trends.展开更多
针对股价预测中存在的不确定性、间断性、随机性和非线性等问题,提出一种TRSSA-ELM(Tent Random Walk Sparrow Optimization Algorithm-Extreme Learning Machine)股价预测模型。首先,采用自适应Tent混沌映射和随机游走策略对算法进行改...针对股价预测中存在的不确定性、间断性、随机性和非线性等问题,提出一种TRSSA-ELM(Tent Random Walk Sparrow Optimization Algorithm-Extreme Learning Machine)股价预测模型。首先,采用自适应Tent混沌映射和随机游走策略对算法进行改进,增强种群多样性和随机性,提高算法局部和全局的寻优能力。其次,使用单峰、多峰和固定维多峰测试函数对TRSSA(Tent Random Walk Sparrow Optimization Algorithm)性能进行了验证,相比于SSA(Sparrow Optimization Algorithm)、AO(Aquila Optimizer)、POA(Pelican Optimization Algorithm)和GWO(Grey Wolf Optimizer),TRSSA算法具有更好的收敛速度、精度和统计性质。最后,由于ELM(Extreme Learning Machine)模型随机生成权重和阈值,降低了预测精度和泛化能力,应用TRSSA算法优化ELM模型的权重和阈值,并用三安光电股票数据集对TRSSA-ELM模型进行了测试。实验结果表明,TRSSA-ELM模型相比于SSA-ELM、ELM、SVR(Support Vector Regression)和GBDT(Gradient Boosting Decision Tree),具有更好的预测精度和稳定性。展开更多
The suitability of models for describing the clonal growth of Trifolium repens population was discussed. The results showed that deterministic models were inadequate for describing its clonal growth, but the diffusion...The suitability of models for describing the clonal growth of Trifolium repens population was discussed. The results showed that deterministic models were inadequate for describing its clonal growth, but the diffusion models and the randomwalk models suited for the clonal growth characteristics of the population. And it was found that random-walk models were better than diffusion models for describing a population in an environment with rich natural resources, and the latter was better in a poor environment.展开更多
The aim of the paper is to investigate in detail the sensitivity of particles displacement based on method of Lagrangian particle tracking in combination with a 3D Eulerian numerical model that was developed by the fi...The aim of the paper is to investigate in detail the sensitivity of particles displacement based on method of Lagrangian particle tracking in combination with a 3D Eulerian numerical model that was developed by the first author, namely FSUM. The characteristic parameters used for this research include the possibilities of random movement, settling velocity of solid particle, horizontal and vertical diffusion coefficients and condition of particle fixed with a constant distance under water surface. The first part is on the fluid flow model. It includes 3D Navier-Stokes equations together with the initial and boundary conditions that were numerically solved with the finite difference method and coded with FORTRAN 90/95 using parallel technique with OpenMP. A semi-Lagrangian treatment of the advective terms was used. The second part is related to Lagrangian particle tracking model and was solved with the fourth Runge-Kutta method. Model was applied for Strait of Johor and has been calibrated by using measured data on water level and velocity at one station. Eight cases of simulations with many different options were carried out. Through computed cases it shows that random term and settling velocity are very important factors for the behavior of particle trajectory. Although the random diffusion is minor in comparison with flow velocity, but it can rearrange the initial distribution of particles then the cluster of particles become more dispersive during the process of movement. In addition, introducing settling velocity of particle makes a big change on the trajectory of particle that becomes more suitable to sediment transport. The study gave a comprehensive picture on particle movement. The model also showed its possibilities of multiform applications in simulation and prediction for the different problems in practice.展开更多
A random walk Metropolis-Hastings algorithm has been widely used in sampling the parameter of spatial interaction in spatial autoregressive model from a Bayesian point of view. In addition, as an alternative approach,...A random walk Metropolis-Hastings algorithm has been widely used in sampling the parameter of spatial interaction in spatial autoregressive model from a Bayesian point of view. In addition, as an alternative approach, the griddy Gibbs sampler is proposed by [1] and utilized by [2]. This paper proposes an acceptance-rejection Metropolis-Hastings algorithm as a third approach, and compares these three algorithms through Monte Carlo experiments. The experimental results show that the griddy Gibbs sampler is the most efficient algorithm among the algorithms whether the number of observations is small or not in terms of the computation time and the inefficiency factors. Moreover, it seems to work well when the size of grid is 100.展开更多
文摘In this paper, some experimental studies on the impact of effluent from an exhaust tower of an underground tunnel with special construction are reported. By measuring the flow field downstream of the tower in NJU meteorological wind tunnel, some flow characteristics in the make area were established. Based on these, an advanced random\|walk dispersion model was set up and applied successfully to the simulation of dispersion in the wake area. The modelling results were in accordance with wind tunnel measurements. The computed maximum of ground surface concentration in the building case was a factor of 3-4 higher than that in the flat case and appeared much closer to the source. The simulation indicated that random walk modelling is an effective and practical tool for the wake stream impact assessment.
文摘Very recently, we have applied the random walk model to fit the global temperature anomaly, CRUTEM3. With encouraging results, we apply the random walk model to fit the temperature walk that is the conversion of recorded tem-perature and real recorded temperature in 46 gamma world cities from 1901 to 1998 in this study. The results show that the random walk model can fit both temperature walk and real recorded temperature although the fitted results from other climate models are unavailable for comparison in these 46 cities. Therefore, the random walk model can fit not only the global temperature anomaly, but also the real recorded temperatures in various cities around the world.
基金Supported by the National Key Research and Development Program of China(Grant No.2018 YFC0407803)the National Natural Science Foundation of China(Grant No.51679009).
文摘To simulate the pollutant transport with seif-purification in inland waters,the widely used random walk model(RWM)is modified to include a source term for the degradation and to consider the impact of land boundaries.The source term for the degradation is derived from the assumption of the first-order reaction kinetics.Parameters for the new model are determined by a comparison to the analytical results.The proposed model is then applied to simulate and analyze the transport of a test pollutant and its spatial distribution in a large reservoir in northeast China.Reasonable results are obtained,and the effects of the runoff,the flow structure,and the wind on the pollutant transport are analyzed.The results may help the risk assessment and the management of the water pollution in inland waters.
文摘A numerical model has been developed to simulate the transport and fate of oil spilled at sea. The model combines the transport and fate processes of spilled oil with the random walk technique. Oil movement under the influence of tidal currents, wind driven currents, and turbulent eddies is simulated by the PLUME RW dispersion model developed by HR Wallingford. The weathering processes in the model represent physical and chemical changes of soil slicks with time, and comprise mechanical spreading, dispersion, evaporation and emulsification. Shoreline stranding is determined approximately using a capacity method for different shoreline types. This paper presents details of the model, and describe the results of various sensitivity tests. The model is suitable for oil spill contingency planning.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 60634010 and 60776829)the New Century Excellent Talents in University (Grant No. NCET-06-0074)the State Key Laboratory of Rail Traffic Control and Safety,Beijing Jiaotong University (Grant No. RCS2008ZZ001)
文摘According to random walk, in this paper, we propose a new traffic model for scheduling trains on a railway network. In the proposed method, using some iteration rules for walkers, the departure and the arrival times of trains at each station are determined. We test the proposed method on an assumed railway network. The numerical simulations and the analytical results demonstrate that the proposed method provides an effective tool for scheduling trains. Some characteristic behaviours of train movement can be reproduced, such as train delay.
基金supported by the National Natural Science Foundation of China (No.60774088)the Program for New Century Excellent Talents in University of China (No.NCET-2005-229)the Science and Technology Research Key Project of Education Ministry of China (No.107024)
文摘A novel immunization strategy called the random walk immunization strategy on scale-free networks is proposed. Different from other known immunization strategies, this strategy works as follows： a node is randomly chosen from the network. Starting from this node, randomly walk to one of its neighbor node; if the present node is not immunized, then immunize it and continue the random walk; otherwise go back to the previous node and randomly walk again. This process is repeated until a certain fraction of nodes is immunized. By theoretical analysis and numerical simulations, we found that this strategy is very effective in comparison with the other known immunization strategies.
文摘It is presented here a continuous time random walk model for diffusion mediated reactions with both species mobile. The random walk is carried out over an infinite homogeneouos lattice. They are calculated the probability density for the time of reaction of a pair, the reaction rate and the time evolution of the concentration of the majority species. Analytical results are obtained in the Fourier-Laplace transform representation. Known results for a fixed trap are reobtained with appropriate marginal probabilities. It is thus justified Smoluchowski’s original approximation considering the trap at a fixed position and the majority species diffusing with a coefficient sum of the individual coefficients. The results obtained are illustrated by a one dimensional model with bias.
文摘社交网络中,节点间存在多种关系类型,节点数量会随着时间的推移而变化,这种异质性和动态性给链路预测任务带来极大的挑战。因此,本文提出一种基于增量学习的社交网络链路预测方法(incremental learning social networks link prediction,IL-SNLP)。通过对网络进行分层,使每一层网络只包含一种关系类型,以更好地获取节点在每种关系类型下的语义信息;针对网络的动态性,利用时序随机游走捕获社交网络中的局部结构信息和时序信息;针对增量数据,采用增量式更新随机游走策略对历史随机游走序列进行更新。通过增量式skip-gram模型从随机游走序列中提取新出现节点的特征,并进一步更新历史节点的特征;针对网络的异质性,采用概率模型提取不同关系类型之间的因果关系关联程度,并将其作用于每一层的节点特征,以改善不同关系层下节点特征表现能力;利用多层感知机构建节点相互感知器,挖掘节点间建立连接时的相互贡献,实现更高的链路预测准确率。实验结果表明,在3个真实的社交网络数据集上,IL-SNLP方法的ROC曲线下的面积(AUC)和F1分数比基线方法分别提高了10.08%~67.60%和1.76%~64.67%,提升了预测性能;对于增量数据,只需要少次迭代就能保持预测模型的性能,提高了模型训练的速度;与未采用增量学习技术的IL-SNLP−方法相比,IL-SNLP方法在时间效率上提升了30.78%~257.58%,显著缩短了模型的运行时长。
文摘This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation （FFPE） with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior.
基金supported by the 2020 Hunan Natural Science Foundation Project"Research on the Key Technologies of a Personalized Learning Platform for Higher Vocational Students Based on Self-Expanding Knowledge Base and Multimodal Portraits"(2020JJ7041)partly supported by the National Natural Science Foundation of China(No.72073041).
文摘Stock market trading is an activity in which investors need fast and accurate information to make effective decisions.But the fact is that forecasting stock prices by using various models has been suffering from low accuracy,slow convergence,and complex parameters.This study aims to employ a mixed model to improve the accuracy of stock price prediction.We present how to use a random walk based on jump-diffusion,to obtain stock predictions with a good-fitting degree by adjusting different parameters.Aimed at getting better parameters and then using the time series model to predict the data,we employed the time series model to smooth the sequence utilizing logarithm and difference,which successfully resulted in drawing the auto-correlation figure and partial the auto-correlation figure.According to the comparative analysis,which focuses on checking the mean absolute error,including root mean square error and R square evaluation index,we have drawn a clear conclusion that our mixed model prediction effect is relatively good.In the context of Chinese stocks,the hybrid random walk model is very suitable for predicting stocks.It can“interpret”the randomness of stocks very well,and it also has an unparalleled prediction effect compared with other models.Based on the time series model’s application in this paper,the abovementioned series is more suitable for predicting trends.
文摘The suitability of models for describing the clonal growth of Trifolium repens population was discussed. The results showed that deterministic models were inadequate for describing its clonal growth, but the diffusion models and the randomwalk models suited for the clonal growth characteristics of the population. And it was found that random-walk models were better than diffusion models for describing a population in an environment with rich natural resources, and the latter was better in a poor environment.
文摘The aim of the paper is to investigate in detail the sensitivity of particles displacement based on method of Lagrangian particle tracking in combination with a 3D Eulerian numerical model that was developed by the first author, namely FSUM. The characteristic parameters used for this research include the possibilities of random movement, settling velocity of solid particle, horizontal and vertical diffusion coefficients and condition of particle fixed with a constant distance under water surface. The first part is on the fluid flow model. It includes 3D Navier-Stokes equations together with the initial and boundary conditions that were numerically solved with the finite difference method and coded with FORTRAN 90/95 using parallel technique with OpenMP. A semi-Lagrangian treatment of the advective terms was used. The second part is related to Lagrangian particle tracking model and was solved with the fourth Runge-Kutta method. Model was applied for Strait of Johor and has been calibrated by using measured data on water level and velocity at one station. Eight cases of simulations with many different options were carried out. Through computed cases it shows that random term and settling velocity are very important factors for the behavior of particle trajectory. Although the random diffusion is minor in comparison with flow velocity, but it can rearrange the initial distribution of particles then the cluster of particles become more dispersive during the process of movement. In addition, introducing settling velocity of particle makes a big change on the trajectory of particle that becomes more suitable to sediment transport. The study gave a comprehensive picture on particle movement. The model also showed its possibilities of multiform applications in simulation and prediction for the different problems in practice.
文摘A random walk Metropolis-Hastings algorithm has been widely used in sampling the parameter of spatial interaction in spatial autoregressive model from a Bayesian point of view. In addition, as an alternative approach, the griddy Gibbs sampler is proposed by [1] and utilized by [2]. This paper proposes an acceptance-rejection Metropolis-Hastings algorithm as a third approach, and compares these three algorithms through Monte Carlo experiments. The experimental results show that the griddy Gibbs sampler is the most efficient algorithm among the algorithms whether the number of observations is small or not in terms of the computation time and the inefficiency factors. Moreover, it seems to work well when the size of grid is 100.
