Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer su...Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.展开更多
Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a...Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient l, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with l using the Soil Conservation Service curve number （SCS-CN） method, with r = 1/（1 ＋ λ）. The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r = 0.833 with λ = 0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.展开更多
Understanding the interaction between canopy structure and the parameters of interception loss is essential in predicting the variations in partitioning rainfall and water resources as affected by changes in canopy st...Understanding the interaction between canopy structure and the parameters of interception loss is essential in predicting the variations in partitioning rainfall and water resources as affected by changes in canopy structure and in implementing water-based management in semiarid forest plantations.In this study,seasonal variations in rainfall interception loss and canopy storage capacity as driven by canopy structure were predicted and the linkages were tested using seasonal filed measurements.The study was conducted in nine 50 m×50 m Robinia pseudoacacia plots in the semiarid region of China’s Loess Plateau.Gross rain-fall,throughfall and stemflow were measured in seasons with and without leaves in 2015 and 2016.Results show that measured average interception loss for the nine plots were 17.9% and 9.4% of gross rainfall during periods with leaves (the growing season) and without leaves, respectively. Average canopy storage capacity estimated using an indirect method was 1.3 mm in the growing season and 0.2 mm in the leafless season. Correlations of relative interception loss and canopy storage capacity to canopy variables were highest for leaf/wood area index (LAI/WAI) and canopy cover, fol-lowed by bark area, basal area, tree height and stand density. Combined canopy cover, leaf/wood area index and bark area multiple regression models of interception loss and canopy storage capacity were established for the growing season and in the leafless season in 2015. It explained 97% and 96% of the variations in relative interception loss during seasons with and without leaves, respectively. It also explained 98% and 99% of the variations in canopy storage capacity during seasons with and without leaves, respectively. The empiri-cal regression models were validated using field data col-lected in 2016. The models satisfactorily predicted relative interception loss and canopy storage capacity during seasons with and without leaves. This study provides greater under-standing about the effects of changes in tree canopy structure (e.g., dieback or mortality) on hydrological processes.展开更多
Minimizing parameter uncertainty is crucial in the application of hydrologic models.Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in th...Minimizing parameter uncertainty is crucial in the application of hydrologic models.Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in the system,provide additional information for parameter estimation,and improve parameter identifiability.This study combined the Philip infiltration model with an isotopic mixing model using an isotopic mass balance approach for estimating parameters in the Philip infiltration model.Two approaches to parameter estimation were compared:(a) using isotopic information to determine the soil water transmission and then hydrologic information to estimate the soil sorptivity,and(b) using hydrologic information to determine the soil water transmission and the soil sorptivity.Results of parameter estimation were verified through a rainfall infiltration experiment in a laboratory under rainfall with constant isotopic compositions and uniform initial soil water content conditions.Experimental results showed that approach(a),using isotopic and hydrologic information,estimated the soil water transmission in the Philip infiltration model in a manner that matched measured values well.The results of parameter estimation of approach(a) were better than those of approach(b).It was also found that the analytical precision of hydrogen and oxygen stable isotopes had a significant effect on parameter estimation using isotopic information.展开更多
Changing coordinates using appropriate mathematical models from one reference system to another may be influenced if the operation requires the change of datum. A set of transformation parameters has been adopted for ...Changing coordinates using appropriate mathematical models from one reference system to another may be influenced if the operation requires the change of datum. A set of transformation parameters has been adopted for Nigeria. However, the critical concern usually associated with the problem of transformation of coordinates is the issue of recoverability of the original values of transformed coordinates. The recursive effect of variables associated with spatial problems can be aptly modelled with an appropriate algorithm that set out a process to achieve a definite output. Consequently, the main thrust of this paper is to highlight the critical elements of the mathematical algorithm associated with the National Transformation Version 2 (NTv2) model adapted for the Nigerian Datum Transformation process. The adapted NTv2 model adopts the bi-linear interpolation approach and the covariance function obtained were used to generate transformation elements in latitude (Δ<em>φp</em>) and longitude (Δ<em>λp</em>) and corresponding accuracies at the lattice nodes. The mathematical algorithm of this adapted NTv2 model underscores the likely attainment of better and significant values and statistical indicator of the improved accuracy as the average shift values for latitude and longitude for any transformed points in Nigeria. This capability makes the mathematical algorithm to be adaptable and fit for the purpose of the transformation process. The improvement in the positional accuracy is directly attributable to the application of the NTv2 model which provides a flexible and robust system of modelling any inherent systematic error in the national network.展开更多
This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（H...This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（HOSVD） approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product（TP） model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities（LMIs） constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach.展开更多
The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed paramete...The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed parameters model can depict the winding characteristics accurately,but it requires complex calculations.Lumped parameter model requires less calculations,but its applicable frequency range is not wide.This paper studies the amplitude-frequency characteristics of the lightning wave,compares the transformer modelling methods and finally proposes a modified lumped parameter model,based on the above comparison.The proposed model minimizes the errors provoked by the lumped parameter approximation,and the hyperbolic functions of the distributed parameter model.By this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage response.The proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.展开更多
Multirate systems are abundant in industry; for example, many soft-sensor design problems are related to modeling, parameter identification, or state estimation involving multirate systems. The study of multirate syst...Multirate systems are abundant in industry; for example, many soft-sensor design problems are related to modeling, parameter identification, or state estimation involving multirate systems. The study of multirate systems goes back to the early 1950's, and has become an active research area in systems and control. This paper briefly surveys the history of development in the area of multirate systems, and introduces some basic concepts and latest results on multirate systems, including a polynomial transformation technique and the lifting technique as tools for handling multirate systems, lifted state space models, parameter identification of dual-rate systems, how to determine fast single-rate models from dual-rate models and directly from dual-rate data, and a hierarchical identification method for general multirate systems. Finally, some further research topics for multirate systems are given.展开更多
A model of monolithic transformers is presented, which is analyzed with characteristic functions. A closed- form analytical approach to extract all the model parameters for the equivalent circuit of Si-based on-chip t...A model of monolithic transformers is presented, which is analyzed with characteristic functions. A closed- form analytical approach to extract all the model parameters for the equivalent circuit of Si-based on-chip transformers is proposed. A novel de-coupling technique is first developed to reduce the complexity in the Y parameters for the transformer, and the model parameters can then be extracted analytically by a set of characteristic functions. Simulation based on the extracted parameters has been carried out for transformers with different structures, and good accuracy is obtained compared to a 3-demensional full-wave numerical electro- magnetic field solver. The presented approach will be very useful to provide a scalable and wide-band compact circuit model for Si-based RF transformers.展开更多
This paper calculates the parameters of image position and orientation,proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection.Every step of the model...This paper calculates the parameters of image position and orientation,proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection.Every step of the model is strict,and the map function of each transformation is the first order polynomials and other simple function.The final calculation of the parameters is for the linear equations with good status.As a result,the problem of the relativity of image parameter calculation is solved completely.Some experiments are carried out.展开更多
Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance,medicine,science,engineering,and so on.Statistical data mining(SDM)is an interdisciplinary dom...Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance,medicine,science,engineering,and so on.Statistical data mining(SDM)is an interdisciplinary domain that examines huge existing databases to discover patterns and connections from the data.It varies in classical statistics on the size of datasets and on the detail that the data could not primarily be gathered based on some experimental strategy but conversely for other resolves.Thus,this paper introduces an effective statistical Data Mining for Intelligent Rainfall Prediction using Slime Mould Optimization with Deep Learning(SDMIRPSMODL)model.In the presented SDMIRP-SMODL model,the feature subset selection process is performed by the SMO algorithm,which in turn minimizes the computation complexity.For rainfall prediction.Convolution neural network with long short-term memory(CNN-LSTM)technique is exploited.At last,this study involves the pelican optimization algorithm(POA)as a hyperparameter optimizer.The experimental evaluation of the SDMIRP-SMODL approach is tested utilizing a rainfall dataset comprising 23682 samples in the negative class and 1865 samples in the positive class.The comparative outcomes reported the supremacy of the SDMIRP-SMODL model compared to existing techniques.展开更多
The two-layered (0 - 50 and 50 - 250 mm) surface horizon hydraulic parameters of three dryland floodplain soil-types under aquafer water management in Postmasburg, Northern Cape Province of South Africa were estimated...The two-layered (0 - 50 and 50 - 250 mm) surface horizon hydraulic parameters of three dryland floodplain soil-types under aquafer water management in Postmasburg, Northern Cape Province of South Africa were estimated with HYDRUS-1D model. Time dependent water infiltration measurements at 30 and 230 mm depths from simulated rainfalls on undisturbed 1 m2 small plots with intensities of 1.61 (high), 0.52 (medium) and 0.27 (low) mm·min-1, were minimised using a two-step inversion. Firstly, separate optimisation of the van Genuchten-Mualem model parameters for the two surface-horizon layers and secondly, simultaneous optimisation for the joint two-layered horizon with first step optimal parameters entered as initial values. The model reproduced transient water-infiltration data very well with the Nash-Sutcliffe model efficiency coefficient (NSE) of 0.99 and overestimated runoff (NSE;0.27 to 0.98). The upper surface horizon had highly optimised and variable parameters especially θs and Ks. Optimal Ks values from higher soil surface bulk-density (≥1.69 g·cm-3) were lower by at least one order of magnitude to double ring infiltrometers and water infiltration properties were different (P < 0.05) for the high rainstorm due to raindrop impact and surface crusting. Optimal α and n parameter values corresponded well with texture of the Addo (Greysols), Augrabies (Ferralsols) and Brandvlei (Cambisols) soil types. However, θs and Ksshowed greater sensitivity to model output and exerted greater influence on dryland floodplain water-infiltration and runoff characteristics. Increasing rainfall simulation period to attain near-surface saturated conditions and inclusion of surface ponding data in the inverse problem could considerable improve model prediction of hydro-physical parameters controlling surface-subsurface water distribution in fluvial environments.展开更多
An AMT-model,consisting of a trajectory model and a one-dimensional boundary layer model,is tested for trajectories arriving in Taiyuan to study the possibility of using it in Taiyuan.The sensitivity of the model to t...An AMT-model,consisting of a trajectory model and a one-dimensional boundary layer model,is tested for trajectories arriving in Taiyuan to study the possibility of using it in Taiyuan.The sensitivity of the model to the different processes was studied.Some parameters of the model were modified for the purpose of forecast- ing in specific mountainous terrain and dry climate conditions.Results of examples which we have worked out for Taiyuan circumstances for the periods of July(summer)1985 and January(winter)1986,show that the 12h runs of the AMT-model are able to reproduce(on historical data)the sounding of Taiyuan.The AMT-model contributes fruitfully to short-range weather forecasts(12—36h ahead)during periods of severe air pollution and when cold waves occur.展开更多
文摘Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.
基金supported by the National Natural Science Foundation of China(Grants No.41271048 and 41330529)
文摘Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient l, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with l using the Soil Conservation Service curve number （SCS-CN） method, with r = 1/（1 ＋ λ）. The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r = 0.833 with λ = 0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.
基金This study is supported by National Key Research and Development Program(2016YFC0501603).
文摘Understanding the interaction between canopy structure and the parameters of interception loss is essential in predicting the variations in partitioning rainfall and water resources as affected by changes in canopy structure and in implementing water-based management in semiarid forest plantations.In this study,seasonal variations in rainfall interception loss and canopy storage capacity as driven by canopy structure were predicted and the linkages were tested using seasonal filed measurements.The study was conducted in nine 50 m×50 m Robinia pseudoacacia plots in the semiarid region of China’s Loess Plateau.Gross rain-fall,throughfall and stemflow were measured in seasons with and without leaves in 2015 and 2016.Results show that measured average interception loss for the nine plots were 17.9% and 9.4% of gross rainfall during periods with leaves (the growing season) and without leaves, respectively. Average canopy storage capacity estimated using an indirect method was 1.3 mm in the growing season and 0.2 mm in the leafless season. Correlations of relative interception loss and canopy storage capacity to canopy variables were highest for leaf/wood area index (LAI/WAI) and canopy cover, fol-lowed by bark area, basal area, tree height and stand density. Combined canopy cover, leaf/wood area index and bark area multiple regression models of interception loss and canopy storage capacity were established for the growing season and in the leafless season in 2015. It explained 97% and 96% of the variations in relative interception loss during seasons with and without leaves, respectively. It also explained 98% and 99% of the variations in canopy storage capacity during seasons with and without leaves, respectively. The empiri-cal regression models were validated using field data col-lected in 2016. The models satisfactorily predicted relative interception loss and canopy storage capacity during seasons with and without leaves. This study provides greater under-standing about the effects of changes in tree canopy structure (e.g., dieback or mortality) on hydrological processes.
基金supported by the National Natural Science Foundation of China(Grant No.51279057)
文摘Minimizing parameter uncertainty is crucial in the application of hydrologic models.Isotopic information in various hydrologic components of the water cycle can expand our knowledge of the dynamics of water flow in the system,provide additional information for parameter estimation,and improve parameter identifiability.This study combined the Philip infiltration model with an isotopic mixing model using an isotopic mass balance approach for estimating parameters in the Philip infiltration model.Two approaches to parameter estimation were compared:(a) using isotopic information to determine the soil water transmission and then hydrologic information to estimate the soil sorptivity,and(b) using hydrologic information to determine the soil water transmission and the soil sorptivity.Results of parameter estimation were verified through a rainfall infiltration experiment in a laboratory under rainfall with constant isotopic compositions and uniform initial soil water content conditions.Experimental results showed that approach(a),using isotopic and hydrologic information,estimated the soil water transmission in the Philip infiltration model in a manner that matched measured values well.The results of parameter estimation of approach(a) were better than those of approach(b).It was also found that the analytical precision of hydrogen and oxygen stable isotopes had a significant effect on parameter estimation using isotopic information.
文摘Changing coordinates using appropriate mathematical models from one reference system to another may be influenced if the operation requires the change of datum. A set of transformation parameters has been adopted for Nigeria. However, the critical concern usually associated with the problem of transformation of coordinates is the issue of recoverability of the original values of transformed coordinates. The recursive effect of variables associated with spatial problems can be aptly modelled with an appropriate algorithm that set out a process to achieve a definite output. Consequently, the main thrust of this paper is to highlight the critical elements of the mathematical algorithm associated with the National Transformation Version 2 (NTv2) model adapted for the Nigerian Datum Transformation process. The adapted NTv2 model adopts the bi-linear interpolation approach and the covariance function obtained were used to generate transformation elements in latitude (Δ<em>φp</em>) and longitude (Δ<em>λp</em>) and corresponding accuracies at the lattice nodes. The mathematical algorithm of this adapted NTv2 model underscores the likely attainment of better and significant values and statistical indicator of the improved accuracy as the average shift values for latitude and longitude for any transformed points in Nigeria. This capability makes the mathematical algorithm to be adaptable and fit for the purpose of the transformation process. The improvement in the positional accuracy is directly attributable to the application of the NTv2 model which provides a flexible and robust system of modelling any inherent systematic error in the national network.
基金supported by the National Natural Science Foundation of China(6120300761304239+1 种基金61503392)the Natural Science Foundation of Shaanxi Province(2015JQ6213)
文摘This paper focuses on synthesizing a mixed robust H_2/H_∞ linear parameter varying（LPV） controller for the longitudinal motion of an air-breathing hypersonic vehicle via a high order singular value decomposition（HOSVD） approach.The design of hypersonic flight control systems is highly challenging due to the enormous complexity of the vehicle dynamics and the presence of significant uncertainties.Motivated by recent results on both LPV control and tensor-product（TP） model transformation approach,the velocity and altitude tracking control problems for the air-breathing hypersonic vehicle is reduced to that of a state feedback stabilizing controller design for a polytopic LPV system with guaranteed performances.The controller implementation is converted into a convex optimization problem with parameterdependent linear matrix inequalities（LMIs） constraints,which is intuitively tractable using LMI control toolbox.Finally,numerical simulation results demonstrate the effectiveness of the proposed approach.
基金supported by the National Key Research and Development Plan of China under Grant(2016YFB0900600XXX)
文摘The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed parameters model can depict the winding characteristics accurately,but it requires complex calculations.Lumped parameter model requires less calculations,but its applicable frequency range is not wide.This paper studies the amplitude-frequency characteristics of the lightning wave,compares the transformer modelling methods and finally proposes a modified lumped parameter model,based on the above comparison.The proposed model minimizes the errors provoked by the lumped parameter approximation,and the hyperbolic functions of the distributed parameter model.By this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage response.The proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.
基金Supported by the Natural Sciences and Engineering Research Council of Canada and National Natural Science Foundation of P.R.China
文摘Multirate systems are abundant in industry; for example, many soft-sensor design problems are related to modeling, parameter identification, or state estimation involving multirate systems. The study of multirate systems goes back to the early 1950's, and has become an active research area in systems and control. This paper briefly surveys the history of development in the area of multirate systems, and introduces some basic concepts and latest results on multirate systems, including a polynomial transformation technique and the lifting technique as tools for handling multirate systems, lifted state space models, parameter identification of dual-rate systems, how to determine fast single-rate models from dual-rate models and directly from dual-rate data, and a hierarchical identification method for general multirate systems. Finally, some further research topics for multirate systems are given.
文摘A model of monolithic transformers is presented, which is analyzed with characteristic functions. A closed- form analytical approach to extract all the model parameters for the equivalent circuit of Si-based on-chip transformers is proposed. A novel de-coupling technique is first developed to reduce the complexity in the Y parameters for the transformer, and the model parameters can then be extracted analytically by a set of characteristic functions. Simulation based on the extracted parameters has been carried out for transformers with different structures, and good accuracy is obtained compared to a 3-demensional full-wave numerical electro- magnetic field solver. The presented approach will be very useful to provide a scalable and wide-band compact circuit model for Si-based RF transformers.
文摘This paper calculates the parameters of image position and orientation,proposes a mathematical model and adopts a new method with three steps of transformations based on parallel ray projection.Every step of the model is strict,and the map function of each transformation is the first order polynomials and other simple function.The final calculation of the parameters is for the linear equations with good status.As a result,the problem of the relativity of image parameter calculation is solved completely.Some experiments are carried out.
基金This research was partly supported by the Technology Development Program of MSS[No.S3033853]by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.2021R1A4A1031509).
文摘Statistics are most crucial than ever due to the accessibility of huge counts of data from several domains such as finance,medicine,science,engineering,and so on.Statistical data mining(SDM)is an interdisciplinary domain that examines huge existing databases to discover patterns and connections from the data.It varies in classical statistics on the size of datasets and on the detail that the data could not primarily be gathered based on some experimental strategy but conversely for other resolves.Thus,this paper introduces an effective statistical Data Mining for Intelligent Rainfall Prediction using Slime Mould Optimization with Deep Learning(SDMIRPSMODL)model.In the presented SDMIRP-SMODL model,the feature subset selection process is performed by the SMO algorithm,which in turn minimizes the computation complexity.For rainfall prediction.Convolution neural network with long short-term memory(CNN-LSTM)technique is exploited.At last,this study involves the pelican optimization algorithm(POA)as a hyperparameter optimizer.The experimental evaluation of the SDMIRP-SMODL approach is tested utilizing a rainfall dataset comprising 23682 samples in the negative class and 1865 samples in the positive class.The comparative outcomes reported the supremacy of the SDMIRP-SMODL model compared to existing techniques.
文摘The two-layered (0 - 50 and 50 - 250 mm) surface horizon hydraulic parameters of three dryland floodplain soil-types under aquafer water management in Postmasburg, Northern Cape Province of South Africa were estimated with HYDRUS-1D model. Time dependent water infiltration measurements at 30 and 230 mm depths from simulated rainfalls on undisturbed 1 m2 small plots with intensities of 1.61 (high), 0.52 (medium) and 0.27 (low) mm·min-1, were minimised using a two-step inversion. Firstly, separate optimisation of the van Genuchten-Mualem model parameters for the two surface-horizon layers and secondly, simultaneous optimisation for the joint two-layered horizon with first step optimal parameters entered as initial values. The model reproduced transient water-infiltration data very well with the Nash-Sutcliffe model efficiency coefficient (NSE) of 0.99 and overestimated runoff (NSE;0.27 to 0.98). The upper surface horizon had highly optimised and variable parameters especially θs and Ks. Optimal Ks values from higher soil surface bulk-density (≥1.69 g·cm-3) were lower by at least one order of magnitude to double ring infiltrometers and water infiltration properties were different (P < 0.05) for the high rainstorm due to raindrop impact and surface crusting. Optimal α and n parameter values corresponded well with texture of the Addo (Greysols), Augrabies (Ferralsols) and Brandvlei (Cambisols) soil types. However, θs and Ksshowed greater sensitivity to model output and exerted greater influence on dryland floodplain water-infiltration and runoff characteristics. Increasing rainfall simulation period to attain near-surface saturated conditions and inclusion of surface ponding data in the inverse problem could considerable improve model prediction of hydro-physical parameters controlling surface-subsurface water distribution in fluvial environments.
文摘An AMT-model,consisting of a trajectory model and a one-dimensional boundary layer model,is tested for trajectories arriving in Taiyuan to study the possibility of using it in Taiyuan.The sensitivity of the model to the different processes was studied.Some parameters of the model were modified for the purpose of forecast- ing in specific mountainous terrain and dry climate conditions.Results of examples which we have worked out for Taiyuan circumstances for the periods of July(summer)1985 and January(winter)1986,show that the 12h runs of the AMT-model are able to reproduce(on historical data)the sounding of Taiyuan.The AMT-model contributes fruitfully to short-range weather forecasts(12—36h ahead)during periods of severe air pollution and when cold waves occur.
