| ES-SOFM混合模型及其在水环境评价中的应用 |
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| 引用本文： | 许世刚,高新陵.ES-SOFM混合模型及其在水环境评价中的应用[J].河海大学学报(自然科学版),2002,30(5):53-55. |
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| 作者姓名： | 许世刚 高新陵 |
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| 作者单位： | 1. 淮阴师范学院经济与法律系,江苏,淮安,223001
2. 河海大学水利水电工程学院,江苏,南京,210098 |
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| 摘 要： | 提出一种基于进化策略（Evolutionary Strategy,ES)和自组织特征映射（Self-Organizing Feature Map,SOFM)神经网络的混合模型进行水环境评价的新方法。把SOFM网络嵌入到ES中，根据SOFM网络的运行状态构造ES的适应性函数，利用ES的强搜索能力克服SOFM网络对初始权向量和样本输入次序敏感的弱点。在水环境评价中的应用效果表明，此方法比模糊聚类法分类更合理。
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| 关 键 词： | ES－SOFM混合模型 水环境评价 自组织特征映射 适应性 聚类 水质评价 |
| 文章编号： | 1000-1980(2002)05-0053-03 |
| 修稿时间： | 2001年8月15日 |
ES-SOFM hybrid model and its application to water quality assessment |
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| XU Shi gang ,GAO Xin ling.ES-SOFM hybrid model and its application to water quality assessment[J].Journal of Hohai University (Natural Sciences ),2002,30(5):53-55. |
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| Authors: | XU Shi gang GAO Xin ling |
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| Institution: | XU Shi gang 1,GAO Xin ling 2 |
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| Abstract: | A new method for water quality assessment is put forward based on Evolutionary Strategy(ES) and Self Organizing Feature Map (SOFM) neural networks. With SOFM neural networks embedded into ES, the adaptability function of ES is constructed based on the state of SOFM neural networks. The sensitivity of SOFM neural networks to the initial weight matrix and sequence of exemplar input is overcome by the global optimization of ES. The application of the model to water quality assessment shows that the method is superior to the fuzzy cluster method. |
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| Keywords: | Self Organizing Feature Map (SOFM) Evolutionary Strategy(ES) adaptability cluster water environment assessment |
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