| 改进遗传神经网络的大坝渗流监测模型 |
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| 引用本文： | 付拥军,李明理,张霞.改进遗传神经网络的大坝渗流监测模型[J].山西建筑,2014(8):243-244. |
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| 作者姓名： | 付拥军 李明理 张霞 |
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| 作者单位： | [1]中国葛洲坝集团国际工程有限公司,北京100022 [2]大连理工大学远程与继续教育学院,辽宁大连116011 |
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| 摘 要： | 在对遗传算法的适应度函数改进并修改选择方法的基础上,用改进的遗传算法优化BP神经网络权值,提出一种改进遗传神经网络的大坝渗流监测模型。结合实例分析表明:预测模型合理,训练精度与检测性能得到提高。
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| 关 键 词： | 改进遗传算法 BP神经网络 大坝渗流监测 |
Dam seepage monitoring model based on improved genetic algorithm of neural network |
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| Affiliation: | FU Yong-jun1 LI Ming-li2 ZI-IANG Xia ( 1. China Gezhouba Group International Engineering Limited Company, Beijing 100022, China ; 2. Long-Distance and Continuing Education College, Dalian University of Technology, Dalian 116011, China) |
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| Abstract: | This essay put forward the dam seepage monitoring model improving genetic algorithm of neural network on the basis of the fitness func- tion of genetic algorithm and the selection method for improvement with using the improved genetic algorithm to optimize the weights of BP neural network. Combining the living example analysis we will state clearly that the reasonable prediction model, the training accuracy and detection per- formance can be improved. |
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| Keywords: | improved genetic algorithm BP neural network dam seepage monitoring model |
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