| 模糊概率神经网络水质评价模型及其应用 |
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| 引用本文： | 刘坤,刘贤赵,王巍,安聪沛.模糊概率神经网络水质评价模型及其应用[J].数学的实践与认识,2006,36(12):138-144. |
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| 作者姓名： | 刘坤 刘贤赵 王巍 安聪沛 |
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| 作者单位： | 1. 鲁东大学地理与资源管理学院,山东,烟台,264025
2. 中南大学数学科学与计算技术学院,湖南,长沙,410083 |
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| 摘 要： | 鉴于水质类型和分级标准存在模糊性,将模糊数学中的相对隶属度理论和概率神经网络和相结合,构建了模糊概率神经网络水质评价模型(FPNN).阐明了该模型的构建方法,提出了基于指标相对隶属度矩阵插值构建学习样本的方法,并将该模型应用于实际水质评价.通过与综合评判法、属性识别法和BP网络法的比较,验证了该模型操作简便,评价结果客观可靠.
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| 关 键 词： | 模糊数学 相对隶属度 概率神经网络 水质评价 |
| 修稿时间： | 2006年4月17日 |
Fuzzy Probabilistic Neural Network Water Quality Evaluation Model and Its Application |
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| LIU Kun,LIU Xian-zhao,WANG Wei,AN Cong-pei.Fuzzy Probabilistic Neural Network Water Quality Evaluation Model and Its Application[J].Mathematics in Practice and Theory,2006,36(12):138-144. |
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| Authors: | LIU Kun LIU Xian-zhao WANG Wei AN Cong-pei |
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| Abstract: | Considering the uncertainty of indexes for evaluating water quality and the standard of classification,Fuzzy Probabilistic Neural Network model(FPNN) is proposed by combining the relative membership grade in fuzzy mathematics and Probabilistic Neural Network(PNN).The process of this model is clarified,and the method of establishing studying data based on relative membership grade matrix is brought forward.Finally the model is applied to the actual water quality evaluation,the calculation result indicates that the proposed method is easy to operate and the outcomes is objective and credible compared with those by integrated evaluating method,attribute recognition model and BP network. |
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| Keywords: | fuzzy mathematics relative membership grade Probabilistic Neural Network water quality evaluation |
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