Nonlinear Ship Motion Prediction Via a Novel High Precision RBF Neural Network | |
Jiehua, Zhou ; Xiafu, Peng ; Lisang, Liu ; Dongwei, He ; Peng XF(彭侠夫) | |
刊名 | http://dx.doi.org/10.4156/AISS.vol3.issue10.6 |
2011 | |
关键词 | Forecasting Fuzzy clustering Radial basis function networks Ships Time series |
英文摘要 | The ship swing motion has strong nonlinear and stochastic characteristics, so the ship swing motion prediction is very difficult. The paper designed a novel high precision RBF (radial basis function) neural network to predict the ship swing motion. In order to optimize the neural network structure, it used the embed dimension of time series to determine the number of input node and fuzzy clustering method to determine the initial number of hidden node for RBF neural network at first. Then it used the grey correlation analysis method to analyze the correlation degree between hidden node output and network output, and according to the size of correlation degree to delete the redundant hidden nodes. Meanwhile, in order to improve the prediction accuracy, it increased the direct connection between input layer and output layer in RBF neural network. Finally, the proposed model was tested with data from a real-world ship swing motion. Results show that the model maximum absolute error and mean squared error are respectively 0.2739 degree and 0.0110, so the proposed model is capable of prediction. |
语种 | 英语 |
出版者 | Advanced Institute of Convergence Information Technology |
内容类型 | 期刊论文 |
源URL | [http://dspace.xmu.edu.cn/handle/2288/93014] |
专题 | 信息技术-已发表论文 |
推荐引用方式 GB/T 7714 | Jiehua, Zhou,Xiafu, Peng,Lisang, Liu,et al. Nonlinear Ship Motion Prediction Via a Novel High Precision RBF Neural Network[J]. http://dx.doi.org/10.4156/AISS.vol3.issue10.6,2011. |
APA | Jiehua, Zhou,Xiafu, Peng,Lisang, Liu,Dongwei, He,&彭侠夫.(2011).Nonlinear Ship Motion Prediction Via a Novel High Precision RBF Neural Network.http://dx.doi.org/10.4156/AISS.vol3.issue10.6. |
MLA | Jiehua, Zhou,et al."Nonlinear Ship Motion Prediction Via a Novel High Precision RBF Neural Network".http://dx.doi.org/10.4156/AISS.vol3.issue10.6 (2011). |
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