Real-time Online Forecasting Model of Ship Rolling Motion Based on Chaotic Online LSSVM

摘要：

Considering the chaotic characteristics of ship rolling time series, the new real-time forecasting method is proposed to further enhance accuracy and real-time of the prediction model based on support vector machines in the prediction of ship rolling motion, which utilizes phase space reconstruction theory of chaotic systems and online LSSVM. Delay time and delay time window are estimated by C-C method, and then the chaotic online LSSVM real-time prediction model is established. The experiments of ship rolling time series prediction are done. The simulation results indicate the real-time prediction method can more effectively improve the convergence rate and the prediction precision and extend prediction time at the same time, which is compared to the combination prediction model based on support vector machine and neural network.

作者: Sheng LIU Zhen YANG

作者单位: College of Automation, Harbin Engineering University, Harbin, China

会议类型: 国际会议

会议名称: 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management(2011 IEEE 第十八届工业工程与工程管理国际会议 IEEM2011)

会议地点: 长春

会议语种:英文

页码: 1732-1736

在线出版日期: 2011-09-03（万方平台首次上网日期，不代表论文的发表时间）