| 基于模糊神经网络的水质评价模型研究 |
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| 引用本文： | 杨华芬,魏延.基于模糊神经网络的水质评价模型研究[J].云南民族大学学报(自然科学版),2007,16(3):255-258. |
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| 作者姓名： | 杨华芬 魏延 |
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| 作者单位： | 1. 重庆师范大学数学与计算机科学学院,重庆,400047;曲靖师范学院计科系,云南曲靖,655000
2. 重庆师范大学数学与计算机科学学院,重庆,400047 |
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| 基金项目： | 重庆市教委科学研究项目（KJ050809）. |
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| 摘 要： | 将模糊系统与神经网络结合,提出了一种水质评价模型.根据水质评价过程,采用5层结构的FNN,且使用自适应学习步长以加速网络收敛速度.该模型具有推理过程清晰,泛化能力强的特点.为了验证该算法的性能,进行了仿真试验,结果表明:和常见的方法相比,该模型的评价结果更为准确.
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| 关 键 词： | 模糊 神经网络 富营养化 水质评价 |
| 文章编号： | 1672-8513（2007）03-0255-04 |
| 收稿时间： | 2007-02-01 |
| 修稿时间： | 2007-02-01 |
Research on Water Quality Assessment Model Based on Fuzzy Neural Network |
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| Yang Huafen,Wei Yan.Research on Water Quality Assessment Model Based on Fuzzy Neural Network[J].Journal of Yunnan Nationalities University:Natural Sciences Edition,2007,16(3):255-258. |
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| Authors: | Yang Huafen Wei Yan |
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| Institution: | 1. School of Mathematics and Computer Science, Chongqing Normal University, Chongqing 400047, China; 2. Department of Computer Science, Qujing Normal University, Qujing 655000, China |
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| Abstract: | The eutrophication of Taihu Lake affects local environment directly.It is important to control and assess the eutrophication precisely.In this paper neural network and fuzzy system are united together and we put forward a neural model for assessment of eutrophication.There are 5 layers in this model,which is based on the process of assessment for eutrophication.The model has many characteristics,such as clear reasoning,better generalization capabilities and so on.In order to prove the performance of the algorithm we carry out a simulation experiment.The results of experiment show that the model can get more precise results compared with common methods. |
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| Keywords: | fuzzy neural network eutrophication water quality assessment |
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