| 基于模糊神经网络的葡萄病害诊断系统研究 |
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| 引用本文： | 刘树文,王庆伟,何东健,李华,武苏里.基于模糊神经网络的葡萄病害诊断系统研究[J].农业工程学报,2006,22(9):144-147. |
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| 作者姓名： | 刘树文 王庆伟 何东健 李华 武苏里 |
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| 作者单位： | 1. 西北农林科技大学葡萄酒学院,杨凌,712100
2. 西北农林科技大学信息工程学院,杨凌,712100 |
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| 摘 要： | 针对传统专家系统自学能力差的特点，以实现基于Web的智能葡萄病害诊断系统为目标，研究了26种葡萄常见病害模糊隶属度的表示方法及模糊BP神经网络模型，采用Java与Matlab混合编程方法实现了该系统的葡萄病害诊断功能。试验结果表明，该系统病害诊断正确率达90.9％，且能在Web上运行，便于推广和使用。
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| 关 键 词： | 葡萄病害 模糊神经网络 诊断 模糊隶属度 |
| 文章编号： | 1002-6819(2006)09-0144-04 |
| 收稿时间： | 2005-10-20 |
| 修稿时间： | 2006-07-16 |
Grape disease diagnosis system based on fuzzy neural network |
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| Liu Shuwen,Wang Qingwei,He Dongjian,Li Hua and Wu Suli.Grape disease diagnosis system based on fuzzy neural network[J].Transactions of the Chinese Society of Agricultural Engineering,2006,22(9):144-147. |
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| Authors: | Liu Shuwen Wang Qingwei He Dongjian Li Hua and Wu Suli |
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| Institution: | College of Enology, Northwest Agriculture and Forestry University, Yangling 712100, China;College of Enology, Northwest Agriculture and Forestry University, Yangling 712100, China;College of Information Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China;College of Enology, Northwest Agriculture and Forestry University, Yangling 712100, China;College of Information Engineering, Northwest Agriculture and Forestry University, Yangling 712100, China |
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| Abstract: | Aimed at the weak self-learning ability of traditional expert system, the expression method for fuzzy subordination and the mode of fuzzy back-propagation artificial neural network for 26 kinds of common grape diseases was studied, so as to realize a web based intelligent grape disease diagnosis system, which was implemented by JAVA and MATLAB. The system can be popularized easily as it is designed to be run online, and experimental results show that the system can diagnose grape diseases with the accuracy of 90.9%. The analyses of the diagnosis results of typical examples indicate that this system has stable reliability, can simulate the expert diagnosis process adequately, and can improve the diagnosis efficiency greatly. |
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| Keywords: | grape diseases fuzzy neural network diagnosis fuzzy subordination |
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