Particle swarm optimizer （PSO）, a new evolutionary computation algorithm, exhibits good performance for optimization problems, although PSO can not guarantee convergence of a global minimum, even a local minimum. Ho...Particle swarm optimizer （PSO）, a new evolutionary computation algorithm, exhibits good performance for optimization problems, although PSO can not guarantee convergence of a global minimum, even a local minimum. However, there are some adjustable parameters and restrictive conditions which can affect performance of the algorithm. In this paper, the algorithm are analyzed as a time-varying dynamic system, and the sufficient conditions for asymptotic stability of acceleration factors, increment of acceleration factors and inertia weight are deduced. The value of the inertia weight is enhanced to （-1, 1）. Based on the deduced principle of acceleration factors, a new adaptive PSO algorithm- harmonious PSO （HPSO） is proposed. Furthermore it is proved that HPSO is a global search algorithm. In the experiments, HPSO are used to the model identification of a linear motor driving servo system. An Akaike information criteria based fitness function is designed and the algorithms can not only estimate the parameters, but also determine the order of the model simultaneously. The results demonstrate the effectiveness of HPSO.展开更多
为了对我国城市水资源利用效率问题进行分析和评价,本文基于数据包络分析方法,从农业、工业、生活、社会等几个方面共选取了5个输入指标及6个输出指标,利用AIC信息准则(Akaike information criterion)进行了变量选择,构建了较为科学合...为了对我国城市水资源利用效率问题进行分析和评价,本文基于数据包络分析方法,从农业、工业、生活、社会等几个方面共选取了5个输入指标及6个输出指标,利用AIC信息准则(Akaike information criterion)进行了变量选择,构建了较为科学合理的用水效率评价指标体系.在此基础上,采用香农熵指数提升了传统CCR(由Charnes A,Cooper W W,Rhodes E提出)模型的识别能力,选取我国31个省会城市为研究对象,给出了省会城市水资源效率的完整排名。结果表明:①绝大部分城市综合效率得分(CES,Comprehensive efficiency score)普遍不高,投入产出比仍有较大的进步空间;②拉萨、北京、天津、银川、海口、上海等城市CES得分相对较高,这说明一个城市水资源利用效率的高低与经济发展水平可能没有必然的联系,其他城市应结合自身情况向CES得分靠前的城市进行学习;③重庆、南宁、南昌、长沙等水资源较丰富的城市CES得分反而较低,表明这些城市可能存在大量水资源被浪费,应建立起节水机制,同时优化产业结构。展开更多
Seismological Bureau of Sichuan Province, Chengdu 610041, China2) Center for Analysis and Prediction, State Seismological Bureau, Beijing 100036, China3) Observation Center for Prediction of Earthquakes and Volcanic E...Seismological Bureau of Sichuan Province, Chengdu 610041, China2) Center for Analysis and Prediction, State Seismological Bureau, Beijing 100036, China3) Observation Center for Prediction of Earthquakes and Volcanic Eruptions, Faculty of Sciences, Tohoku University, Sendai 98077, Japan展开更多
基金This work was supported by the Teaching and Research Award Program for Outstanding Young Teacher in Higher Education Institute of Ministry ofEducation of China (NO. 20010248).
文摘Particle swarm optimizer （PSO）, a new evolutionary computation algorithm, exhibits good performance for optimization problems, although PSO can not guarantee convergence of a global minimum, even a local minimum. However, there are some adjustable parameters and restrictive conditions which can affect performance of the algorithm. In this paper, the algorithm are analyzed as a time-varying dynamic system, and the sufficient conditions for asymptotic stability of acceleration factors, increment of acceleration factors and inertia weight are deduced. The value of the inertia weight is enhanced to （-1, 1）. Based on the deduced principle of acceleration factors, a new adaptive PSO algorithm- harmonious PSO （HPSO） is proposed. Furthermore it is proved that HPSO is a global search algorithm. In the experiments, HPSO are used to the model identification of a linear motor driving servo system. An Akaike information criteria based fitness function is designed and the algorithms can not only estimate the parameters, but also determine the order of the model simultaneously. The results demonstrate the effectiveness of HPSO.
文摘为了对我国城市水资源利用效率问题进行分析和评价,本文基于数据包络分析方法,从农业、工业、生活、社会等几个方面共选取了5个输入指标及6个输出指标,利用AIC信息准则(Akaike information criterion)进行了变量选择,构建了较为科学合理的用水效率评价指标体系.在此基础上,采用香农熵指数提升了传统CCR(由Charnes A,Cooper W W,Rhodes E提出)模型的识别能力,选取我国31个省会城市为研究对象,给出了省会城市水资源效率的完整排名。结果表明:①绝大部分城市综合效率得分(CES,Comprehensive efficiency score)普遍不高,投入产出比仍有较大的进步空间;②拉萨、北京、天津、银川、海口、上海等城市CES得分相对较高,这说明一个城市水资源利用效率的高低与经济发展水平可能没有必然的联系,其他城市应结合自身情况向CES得分靠前的城市进行学习;③重庆、南宁、南昌、长沙等水资源较丰富的城市CES得分反而较低,表明这些城市可能存在大量水资源被浪费,应建立起节水机制,同时优化产业结构。
文摘Seismological Bureau of Sichuan Province, Chengdu 610041, China2) Center for Analysis and Prediction, State Seismological Bureau, Beijing 100036, China3) Observation Center for Prediction of Earthquakes and Volcanic Eruptions, Faculty of Sciences, Tohoku University, Sendai 98077, Japan
