| 基于遗传BP算法的日径流预测 |
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| 引用本文： | 龚传利,康玲,姜铁兵.基于遗传BP算法的日径流预测[J].西北水电,2003(4):1-3,21. |
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| 作者姓名： | 龚传利 康玲 姜铁兵 |
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| 作者单位： | 华中科技大学,水电与数字化工程学院,武汉,430074 |
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| 基金项目： | 武汉市晨光计划项目(20005004028)资助. |
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| 摘 要： | 用遗传算法和BP算法相结合的混合算法来训练日径流神经网络预测模型的权值，即先通过遗传学习算法进行全局训练，再用权重调整BP算法进行精确训练，这一算法克服了BP算法收敛速度慢、易陷入局部极小等缺陷，实例证明提高了预测精度。
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| 关 键 词： | 遗传算法 日径流预测 神经网络 BP算法 |
| 文章编号： | 1006-2610(2003)04-0001-03 |
Daily runoff prediction based on integration of genetic and back-propagation algorithms |
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| GONG Chuan-li,KANG Ling,JIANG Tie-bing.Daily runoff prediction based on integration of genetic and back-propagation algorithms[J].Northwest Water Power,2003(4):1-3,21. |
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| Authors: | GONG Chuan-li KANG Ling JIANG Tie-bing |
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| Abstract: | A new method for training Artificial Neural Network(ANN) based daily runoff prediction model is presented. In this method, the genetic algorithm(GA), a general-purpose global search algorithm is used to train the neural network prediction model by updating the weights to minimize the error between the network output and the desired output. It overcomes the limitations of the back-propagation algorithm in slow convergent rate and getting into local optima. The example demonstrates that this method improves the prediction precision. |
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| Keywords: | Genetic Algorithm Artificial Neural Network runoff prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
