计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (13): 231-233.

• 工程与应用 • 上一篇    下一篇

灰色理论与神经网络在水华预测中的应用

朱世平,刘载文,王小艺,戴 军   

  1. 北京工商大学 计算机与信息工程学院,北京 100048
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-05-01 发布日期:2011-05-01

Gray theory and neural network prediction for water bloom

ZHU Shiping,LIU Zaiwen,WANG Xiaoyi,DAI Jun   

  1. School of Computer Science and Information Engineering,Beijing Technology and Business University,Beijing 100048,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-05-01 Published:2011-05-01

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

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.

Key words: water bloom prediction, the highest point of chlorophyll, Back Propagation(BP) neural network, grey topological prediction