| 基于PCNN的农业水资源利用状况评价方法研究 |
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| 引用本文： | 冯艳,付强,冯登超,李伟业,李国良,刘仁涛.基于PCNN的农业水资源利用状况评价方法研究[J].农业工程学报,2007,23(8):80-83. |
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| 作者姓名： | 冯艳 付强 冯登超 李伟业 李国良 刘仁涛 |
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| 作者单位： | 1. 东北农业大学水利与建筑学院,哈尔滨,150030
2. 天津大学电子信息工程学院,天津,300072 |
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| 基金项目： | 国家自然科学基金;黑龙江省杰出青年科学基金;黑龙江省教育厅科学技术研究项目;中国博士后科学基金 |
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| 摘 要： | 脉冲耦合神经网络(PCNN)模型以其耦合机制、脉冲输出两大基本特性广泛应用于图像处理领域。该文在两大基本特性的基础上对PCNN进行了改进：连接输入部分等于上一次点火时的脉冲，直接体现了前后神经元之间的联系；动态阈值等于水资源评价标准的等级范围，使调节阈值更容易对样本进行分类；省略了一些不必要的参数，减少了模型的复杂度。将改进后的PCNN用于三江平原农业水资源供需状况评价中，得到了满意结果。证明PCNN应用于水资源评价中是可行的，既拓宽了PCNN的应用领域，又为解决水资源的评价问题提供了新思路。
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| 关 键 词： | 脉冲耦合神经网络 水资源评价 动态阈值 |
| 文章编号： | 1002-6819（2007）8-0080-04 |
| 收稿时间： | 2006/8/30 0:00:00 |
| 修稿时间： | 2/4/2007 12:00:00 AM |
Evaluation method for agricultural water resource utilization based on PCNN |
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| Feng Yan,Fu Qiang,Feng Dengchao,Li Weiye,Li Guoliang and Liu Rentao.Evaluation method for agricultural water resource utilization based on PCNN[J].Transactions of the Chinese Society of Agricultural Engineering,2007,23(8):80-83. |
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| Authors: | Feng Yan Fu Qiang Feng Dengchao Li Weiye Li Guoliang and Liu Rentao |
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| Institution: | College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China;College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China;College of Electronics and Information Engineering, Tianjin University, Tianjin 300072, China;College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China;College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China;College of Water Conservancy and Architecture, Northeast Agricultural University, Harbin 150030, China |
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| Abstract: | Pulse Coupled Neural Network(PCNN), with the basic characteristics of coupling and pulse output, is widely implemented on image processing. PCNN model was improved as follows: the value of link load part equaled to the pulse in the last ignition action in order to reflect directly the relationship between the before and after neural cell, dynamic threshold equaled to the classification range of water resource evaluation criterion to classify the samples easily and unnecessary parameter was omitted to reduce the complexity of PCNN model. The improved PCNN model was used to evaluate agricultural water resources supply and demand in Sanjiang Plain and obtained the better results. Results show that PCNN model is feasible for evaluating agricultural water resource utilization, expanding the application areas of PCNN model and providing a new way for water resource evaluation. |
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| Keywords: | pulse coupled neural networks water resource evaluation dynamic threshold |
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