基于自适应变异PSO-BP算法的船舶横摇运动预测
发布时间：2019-04-28 08:42
【摘要】：为了准确高效预测船舶在海上的航行状态,以保证人员、货物和船舶的安全,提出一种自适应变异的粒子群优化算法(self-adapting particle swarm optimization algorithm,SAPSO),将该算法与误差反传(back propagation,BP)神经网络结合。SAPSO-BP预测模型使用SAPSO算法优化BP网络的网络参数。克服传统BP神经网络对初始权值阈值敏感,容易陷入局部极小值的缺点,同时也克服了传统PSO算法早熟收敛、搜索准确度低及迭代效率低等缺点。运用该模型对科研教学船"育鲲"轮在海上航行的横摇情况进行实时预测实验,验证该方法的可行性与有效性具有较高的预测精度。
[Abstract]:In order to accurately and efficiently predict the navigation state of ships at sea to ensure the safety of personnel, cargo and ships, an adaptive mutation particle swarm optimization (self-adapting particle swarm optimization algorithm,SAPSO) algorithm is proposed, which is used to reverse transmit errors to (back propagation,. The SAPSO-BP prediction model uses SAPSO algorithm to optimize the network parameters of BP network. The traditional BP neural network is sensitive to the initial weight threshold and easy to fall into the local minimum. At the same time, it also overcomes the shortcomings of the traditional PSO algorithm, such as premature convergence, low search accuracy and low iterative efficiency. The model is used to predict the roll of the ship "Yukun" in the sea, and the feasibility and effectiveness of the method is proved to have high prediction accuracy.
【作者单位】： 大连海事大学航海学院;
【基金】：国家自然科学基金资助项目(51279106,51009017,51379002) 中央高校基本科研业务经费资助项目(3132016116,3132016314) 交通部应用基础研究项目(2014329225010) 辽宁省自然科学基金资助项目(2014025008)
【分类号】：U661.321
，
本文编号：2467498
[Abstract]:In order to accurately and efficiently predict the navigation state of ships at sea to ensure the safety of personnel, cargo and ships, an adaptive mutation particle swarm optimization (self-adapting particle swarm optimization algorithm,SAPSO) algorithm is proposed, which is used to reverse transmit errors to (back propagation,. The SAPSO-BP prediction model uses SAPSO algorithm to optimize the network parameters of BP network. The traditional BP neural network is sensitive to the initial weight threshold and easy to fall into the local minimum. At the same time, it also overcomes the shortcomings of the traditional PSO algorithm, such as premature convergence, low search accuracy and low iterative efficiency. The model is used to predict the roll of the ship "Yukun" in the sea, and the feasibility and effectiveness of the method is proved to have high prediction accuracy.
【作者单位】： 大连海事大学航海学院;
【基金】：国家自然科学基金资助项目(51279106,51009017,51379002) 中央高校基本科研业务经费资助项目(3132016116,3132016314) 交通部应用基础研究项目(2014329225010) 辽宁省自然科学基金资助项目(2014025008)
【分类号】：U661.321
，
本文编号：2467498
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