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| 灰色理论与神经网络在水华预测中的应用 | |
| 引用本文： | 朱世平,刘载文,王小艺,戴军. 灰色理论与神经网络在水华预测中的应用[J]. 计算机工程与应用, 2011, 47(13): 231-233. DOI: 10.3778/j.issn.1002-8331.2011.13.065 |
| 作者姓名： | 朱世平 刘载文 王小艺 戴军 |
| 作者单位： | 北京工商大学 计算机与信息工程学院，北京 100048 |
| 摘 要： | 在综合考虑生态系统中水华发生的机理特点基础上，采用改进的BP神经网络实现了对叶绿素最高点的非线性预测；利用灰色WPGM（1，1）模型的累加生成运算（AGO）对叶绿素最高值对应的时刻进行推算，从而预测水华的爆发时间点。经检验，神经网络预测结合灰色WPGM（1，1）预测模型相对误差在10%左右，能够对水华的发生进行判断和预报，有利于综合整治方案的优化和统筹。 |
| 关 键 词： | 水华预测 叶绿素尖点 BP神经网络 灰色拓扑预测 |
| 修稿时间： | |
Gray theory and neural network prediction for water bloom |
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| ZHU Shiping,LIU Zaiwen,WANG Xiaoyi,DAI Jun. Gray theory and neural network prediction for water bloom[J]. Computer Engineering and Applications, 2011, 47(13): 231-233. DOI: 10.3778/j.issn.1002-8331.2011.13.065 | |
| Authors: | ZHU Shiping LIU Zaiwen WANG Xiaoyi DAI Jun |
| Affiliation: | School of Computer Science and Information Engineering，Beijing Technology and Business University，Beijing 100048，China |
| Abstract: | Considering comprehensively the characteristics of water bloom occurrence mechanism in ecological system,the nonlinear prediction of the chlorophyll highest point is implemented based on improved BP neural network;and the time of maximum chlorophyll value is calculated based on the Accumulated Generating Operation（AGO） of WPGM（1,1） model.By inspection,the relative error of chlorophyll highest point model is controlled about 10%.The model is able to judge and predict the water bloom outbreak,and is beneficial to optimize and orchestrate the comprehensive regulation scheme |
| Keywords: | water bloom prediction the highest point of chlorophyll Back Propagation（BP） neural network grey topologicalprediction |
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