| 引用本文: | 刘 威，李小平，毛慧欧，柴天佑.基于实数编码遗传算法的神经网络成本预测模型及其应用[J].控制理论与应用,2004,21(3):423~426.[点击复制] |
| LIU Wei, LI Xiao-ping, MAO Hui-ou, CHAI Tian-you.Neural network cost prediction model based on real-coded genetic algorithm and its application[J].Control Theory and Technology,2004,21(3):423~426.[点击复制] |
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| 基于实数编码遗传算法的神经网络成本预测模型及其应用 |
| Neural network cost prediction model based on real-coded genetic algorithm and its application |
| 摘要点击 1261 全文点击 1456 投稿时间：2003-01-15 修订日期：2003-06-23 |
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| DOI编号 |
| 2004,21(3):423-426 |
| 中文关键词 成本预测 遗传算法 神经网络 实数编码 |
| 英文关键词 cost prediction genetic algorithm neural network real-coded |
| 基金项目 国家自然科学资金项目(60074019); 国家863计划项目(2001AA413510); 国家科技攻关计划项目(2001BA201A03-KHKZ0002). |
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| 中文摘要 |
| 在生产过程中,影响产品成本的因素多而复杂,因素之间相互影响,存在耦合现象,因此准确预测成本是一个重要又难以解决的问题.通过遗传算法(Genetic Algorithm)与误差反向传播(Error Back Propagation)神经网络相结合,提出了用实数编码的自适应变异遗传算法训练神经网络权重的混合算法,避免了传统神经网络易陷入局部极小的缺点.以矩阵形式表示产品成本组成,建立了产品成本组成模型,以此为基础建立了考虑成本因素之间互相影响的神经网络产品成本预测模型,并成功应用于某钢铁企业产品成本的预测,提高了预测精度. |
| 英文摘要 |
| In production process,many complex factors which influence cost affect each other and the coupling phenomenon exists,so it is important and difficult to predict the cost.By combining genetic algorithm with error back propagation neural network,a hybrid algorithm that trained neural network weight by real-coded adaptive mutation genetic algorithm is presented,and it overcomes the disadvantage that traditional neural network is easy to fall into local minima.The product cost composition is expressed by matrix,the product cost composition model is established,on the basis of the model,the product cost prediction model based on neural network is established,and the interactions among cost factors are taken into account.Furthermore,the model is successfully applied to cost prediction in some iron and steel enterprise,and the prediction precision is improved. |
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