Parameter Identification of RVM Runoff Forecasting Model Based on Improved Particle Swarm Optimization

摘要：

　　Runoff forecasting which subjects to model pattern and parameter optimization, has an important significance of reservoir scheduling and water resources management decision-makings.This paper proposed a new forecasting model coupled phase space reconstruction technology with relevance vector machine, and its model parameters is optimized by an improved PSO algorithm.The monthly runoff time series from 1953 to 2003 at Manwan station is selected as an example.The results show that the improved PSO has efficient optimization performance and the proposed forecasting model could obtain higher prediction accuracy.

关键词： Improved PSO algorithm Relevance vector machine Phase space reconstruction parameter identification Runoff forecasting

作者: Yuzhi Shi Haijiao Liu Mingyuan Fan Jiwen Huang

作者单位: Water Resources Research Institute of Shandong Province, Jinan 250013, China

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 160-167

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）