A partition of unity finite element method for numerical simulation of short wave propagation in solids is presented. The finite element spaces were constructed by multiplying the standard isoparametric finite element...A partition of unity finite element method for numerical simulation of short wave propagation in solids is presented. The finite element spaces were constructed by multiplying the standard isoparametric finite element shape functions, which form a partition of unity, with the local subspaces defined on the corresponding shape functions, which include a priori knowledge about the wave motion equation in trial spaces and approximately reproduce the highly oscillatory properties within a single element. Numerical examples demonstrate the performance of the proposed partition of unity finite element in both computational accuracy and efficiency.展开更多
The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier ...The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier partitioning behavior(log BB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method(ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R^2, between experimental results and predicted log BB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the log BB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.展开更多
The space partitioning algorithm based on the rounding and addressing operations has been proved to be an efficient space partitioning algorithm with the potential for real-time calculation.An improvement on this kind...The space partitioning algorithm based on the rounding and addressing operations has been proved to be an efficient space partitioning algorithm with the potential for real-time calculation.An improvement on this kind of space partitioning algorithms for solving complex 3D models is presented.Numerical examples show that the efficiency of the improved algorithm is better than that of the original method.When the size of most target elements is smaller than the size of spatial grids,the efficiency of the improved method can be more than four times of that of the original method.An adaptive method of space partitioning based on the improved algorithm is developed by taking the surface element density or the curvature as the threshold for deep partitioning and conducting the deep partitioning using the octree method.A computer program implementation for applying the method in some typical applications is discussed,and the performance in terms of the efficiency,reliability,and resource use is evaluated.Application testing shows that the results of the adaptive spacing partitioning are more convenient for the follow-up use than that of the basic uniform space partitioning.Furthermore,when it is used to calculate the electromagnetic scattering of complex targets by the ray tracing(RT)method,the adaptive space partitioning algorithm can reduce the calculation time of the RT process by more than 40%compared with the uniform space segmentation algorithm.展开更多
聚类技术是数据挖掘中的一个重要方法,PAM(Partitioning Around Medoids)是基于分区的聚类算法的一种,它试图将n个数据对象分成k个部分。在并行粒子群PSO(Particle Swarm Optimization)算法中,需要划分整个种群为几个相互不重叠的子种...聚类技术是数据挖掘中的一个重要方法,PAM(Partitioning Around Medoids)是基于分区的聚类算法的一种,它试图将n个数据对象分成k个部分。在并行粒子群PSO(Particle Swarm Optimization)算法中,需要划分整个种群为几个相互不重叠的子种群。因此,引入PAM来划分整个种群。通过聚类,相同子种群的粒子相对集中,从而能够较容易地相互学习。这使得有限的时间能够花费在最有效的搜索上,以便提高算法的搜索效率。为了均匀地探测整个解空间,引入均匀设计来产生初始种群,使种群成员均匀地分散在可行解空间中。进化过程中,均匀设计也被引入来替换种群中的较差个体。提出基于PAM和均匀设计的并行粒子群算法,它结合并充分利用了二者的优点。对几个测试问题的实验结果证明,提出的算法比传统的并行粒子群算法具有更高的性能和更好的收敛准确性。展开更多
随着高比例、大规模分布式光伏并网以及电动汽车的普及,如何发挥电动汽车灵活性、实现配电网分布式光伏与本地电动汽车负荷灵活性资源的友好协调是当前需要解决的重要问题。为此,提出了考虑电动汽车与分布式光伏协同的配电网集群划分与...随着高比例、大规模分布式光伏并网以及电动汽车的普及,如何发挥电动汽车灵活性、实现配电网分布式光伏与本地电动汽车负荷灵活性资源的友好协调是当前需要解决的重要问题。为此,提出了考虑电动汽车与分布式光伏协同的配电网集群划分与运行策略。首先,建立电动汽车可调充电功率灵活性聚合模型,提出基于Louvain算法的改进模块度指标配电网分布式集群划分方法;其次,基于历史数据信息生成电动汽车多时间尺度充电场景,提出考虑电动汽车充电灵活性的分布式集群协同优化模型;最后,采用同步交替方向乘子法(synchronous alternating direction multiplier method,SADMM)实现各集群优化模型的分布式求解。仿真结果表明,利用电动汽车充电灵活性参与配电网协同运行可有效提高分布式光伏利用率,并且在满足电动汽车用户充电需求的同时保证了配电网电压运行安全。展开更多
随着电动汽车的高速发展,越来越多的电动汽车接入配电网并与配电网进行互动。针对大规模电动汽车接入配电网带来的线路重过载现象,且考虑调度大规模电动汽车对配电网调控中心产生的通信压力,提出一种基于主从博弈的电动汽车参与城市电...随着电动汽车的高速发展,越来越多的电动汽车接入配电网并与配电网进行互动。针对大规模电动汽车接入配电网带来的线路重过载现象,且考虑调度大规模电动汽车对配电网调控中心产生的通信压力,提出一种基于主从博弈的电动汽车参与城市电网分层分区调控策略。首先提出了一种基于改进分区组合性的城市配电网分区方法,将负荷相似系数以及源荷匹配系数引入到分区参数中。基于分区结果,提出了分区控制下电动汽车双层博弈调度模型,上层模型为配电网调控中心在满足精细化削峰需求约束下的自身收益最大化,并制定了与下层电动汽车聚合商的交易电价;下层模型以聚合商内电动汽车用户用电成本最低为目标,合理安排电动汽车充放电计划,两者之间形成互动博弈并达到均衡解。最后,利用同步型交替方向乘子法(synchronous alternating direction methodofmultipliers,S-ADMM)算法实现了多区域的分布式并行求解,并基于南方某市266节点配电网进行仿真计算,验证了所提模型和方法的有效性。展开更多
基金Project supported by the National Basic Research Program of China (973Project) (No.2002CB412709) and the National Natural Science Foundation of China (Nos.50278012,10272027,19832010)
文摘A partition of unity finite element method for numerical simulation of short wave propagation in solids is presented. The finite element spaces were constructed by multiplying the standard isoparametric finite element shape functions, which form a partition of unity, with the local subspaces defined on the corresponding shape functions, which include a priori knowledge about the wave motion equation in trial spaces and approximately reproduce the highly oscillatory properties within a single element. Numerical examples demonstrate the performance of the proposed partition of unity finite element in both computational accuracy and efficiency.
文摘The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier partitioning behavior(log BB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method(ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R^2, between experimental results and predicted log BB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the log BB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.
基金This work was supported by the National Natural Science Foundation of China(61601015,91538204).
文摘The space partitioning algorithm based on the rounding and addressing operations has been proved to be an efficient space partitioning algorithm with the potential for real-time calculation.An improvement on this kind of space partitioning algorithms for solving complex 3D models is presented.Numerical examples show that the efficiency of the improved algorithm is better than that of the original method.When the size of most target elements is smaller than the size of spatial grids,the efficiency of the improved method can be more than four times of that of the original method.An adaptive method of space partitioning based on the improved algorithm is developed by taking the surface element density or the curvature as the threshold for deep partitioning and conducting the deep partitioning using the octree method.A computer program implementation for applying the method in some typical applications is discussed,and the performance in terms of the efficiency,reliability,and resource use is evaluated.Application testing shows that the results of the adaptive spacing partitioning are more convenient for the follow-up use than that of the basic uniform space partitioning.Furthermore,when it is used to calculate the electromagnetic scattering of complex targets by the ray tracing(RT)method,the adaptive space partitioning algorithm can reduce the calculation time of the RT process by more than 40%compared with the uniform space segmentation algorithm.
文摘聚类技术是数据挖掘中的一个重要方法,PAM(Partitioning Around Medoids)是基于分区的聚类算法的一种,它试图将n个数据对象分成k个部分。在并行粒子群PSO(Particle Swarm Optimization)算法中,需要划分整个种群为几个相互不重叠的子种群。因此,引入PAM来划分整个种群。通过聚类,相同子种群的粒子相对集中,从而能够较容易地相互学习。这使得有限的时间能够花费在最有效的搜索上,以便提高算法的搜索效率。为了均匀地探测整个解空间,引入均匀设计来产生初始种群,使种群成员均匀地分散在可行解空间中。进化过程中,均匀设计也被引入来替换种群中的较差个体。提出基于PAM和均匀设计的并行粒子群算法,它结合并充分利用了二者的优点。对几个测试问题的实验结果证明,提出的算法比传统的并行粒子群算法具有更高的性能和更好的收敛准确性。
文摘随着高比例、大规模分布式光伏并网以及电动汽车的普及,如何发挥电动汽车灵活性、实现配电网分布式光伏与本地电动汽车负荷灵活性资源的友好协调是当前需要解决的重要问题。为此,提出了考虑电动汽车与分布式光伏协同的配电网集群划分与运行策略。首先,建立电动汽车可调充电功率灵活性聚合模型,提出基于Louvain算法的改进模块度指标配电网分布式集群划分方法;其次,基于历史数据信息生成电动汽车多时间尺度充电场景,提出考虑电动汽车充电灵活性的分布式集群协同优化模型;最后,采用同步交替方向乘子法(synchronous alternating direction multiplier method,SADMM)实现各集群优化模型的分布式求解。仿真结果表明,利用电动汽车充电灵活性参与配电网协同运行可有效提高分布式光伏利用率,并且在满足电动汽车用户充电需求的同时保证了配电网电压运行安全。
文摘随着电动汽车的高速发展,越来越多的电动汽车接入配电网并与配电网进行互动。针对大规模电动汽车接入配电网带来的线路重过载现象,且考虑调度大规模电动汽车对配电网调控中心产生的通信压力,提出一种基于主从博弈的电动汽车参与城市电网分层分区调控策略。首先提出了一种基于改进分区组合性的城市配电网分区方法,将负荷相似系数以及源荷匹配系数引入到分区参数中。基于分区结果,提出了分区控制下电动汽车双层博弈调度模型,上层模型为配电网调控中心在满足精细化削峰需求约束下的自身收益最大化,并制定了与下层电动汽车聚合商的交易电价;下层模型以聚合商内电动汽车用户用电成本最低为目标,合理安排电动汽车充放电计划,两者之间形成互动博弈并达到均衡解。最后,利用同步型交替方向乘子法(synchronous alternating direction methodofmultipliers,S-ADMM)算法实现了多区域的分布式并行求解,并基于南方某市266节点配电网进行仿真计算,验证了所提模型和方法的有效性。
