| 一种新的神经树网络模型优化方法 |
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| 引用本文： | 向来生,齐峰,刘希玉.一种新的神经树网络模型优化方法[J].控制与决策,2013,28(1):73-77. |
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| 作者姓名： | 向来生 齐峰 刘希玉 |
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| 作者单位： | 山东师范大学 管理科学与工程学院,济南 250014 |
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| 基金项目： | 国家自然科学基金项目(61170038,60873058);山东省自然科学基金项目(ZR2011FM001);山东省软科学重大项目(2010RKMA2005) |
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| 摘 要： | 神经树网络模型已成功应用于解决各类复杂的非线性问题,并且神经树网络模型的优化过程一般是先拓扑结构优化再参数优化,这种无参数信息的结构优化策略的缺点是干扰适应度的评价.鉴于此,提出一种改进的遗传规划(BGP)算法来综合神经树网络模型的两个优化过程.在两个时间序列预测问题上的仿真实验结果表明,所提出算法是一种有潜力且具备较好效能的方法.
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| 关 键 词： | 神经树网络模型 适应度评价 改进的 BGP 算法 指数变异 时间序列 |
| 收稿时间： | 2011/9/1 0:00:00 |
| 修稿时间： | 2011/12/4 0:00:00 |
A new optimization method for the neural tree network model |
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| XIANG Lai-sheng,QI Feng,LIU Xi-yu.A new optimization method for the neural tree network model[J].Control and Decision,2013,28(1):73-77. |
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| Authors: | XIANG Lai-sheng QI Feng LIU Xi-yu |
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| Affiliation: | (School of Management Science and Engineering,Shandong Normal University,Ji’nan 250014,China.) |
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| Abstract: | Neural tree network model has been successfully applied to solving a variety of complex nonlinear problems. The
optimization of the neural tree model is divided into two steps in general: first structure optimization, and then parameter
optimization. One major problem in the evolution of structure without parameter information is noisy fitness evaluation, so
an improved breeder genetic programming algorithm is proposed to the synthesis of the optimization in neural tree network
model. Simulation results on two time series prediction problems show that the proposed optimization strategy is a potential
method with better performance and effectiveness. |
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| Keywords: | neural tree network model fitness evaluation improved breeder genetic programming algorithm exponential mutation time series |
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