Ship motion prediction using dynamic seasonal RvSVR with phase space reconstruction and the chaos adaptive efficient FOA

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Ship motion prediction using dynamic seasonal RvSVR with phase space reconstruction and the chaos adaptive efficient FOA

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作者：Ming-We Li ^{mingweili2014@gmail.com" class="auth_mail" title="E-mail the corresponding author} ^{limingwei@hrbeu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Jing Geng ^{gengjing@hrbeu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Duan-Feng Han ; ^{dfhan163@163.com" class="auth_mail" title="E-mail the corresponding author} ; ^{handuanfeng@hrbeu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Tian-Ju Zheng ^{zhengtianju@hrbeu.edu.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae
关键词：Ship motion forecasting ; Support vector regression ; Chaos system ; Seasonal adjustment mechanism ; Fruit fly optimization algorithm ; Chaos mapping
刊名：Neurocomputing
出版年：2016
出版时间：22 January 2016
年：2016
卷：174
期：part_PB
页码：661-680
全文大小：1217 K

文摘

•: A new chaos system reconstructing method for ship motion prediction is established.
•: A new dynamic seasonal robust v-support vector regression model is proposed.
•: A novel chaos adaptive efficient fruit fly optimization algorithm is proposed.

•: A new hybrid forecasting approach for ship motion forecasting is established.

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