计算机与现代化

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基于MEC-BP神经网络在水产养殖水质预测中的应用

  

  1. (1.太原科技大学电子信息工程学院,山西太原030024;2.浙江大学宁波理工学院信息科学与工程学院,浙江宁波315100)
  • 收稿日期:2015-01-26 出版日期:2015-06-16 发布日期:2015-06-18
  • 作者简介:杨争光(1989-),男,河南安阳人,太原科技大学电子信息工程学院硕士研究生,研究方向:智能信息处理与识别; 范良忠(1980-),男,浙江丽水人,浙江大学宁波理工学院信息科学与工程学院副教授,博士,研究方向:农业物联网技术。
  • 基金资助:
    国家自然科学基金资助项目(31302231); 浙江省教育厅科研项目(Y201226043); 宁波市自然科学基金资助项目(2012A610110)

Application of Water Quality Prediction Based on MEC-BP Neural Network in Aquaculture

  1.  (1. Institute of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;2. School of Information Science and Engineering, Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, China)
  • Received:2015-01-26 Online:2015-06-16 Published:2015-06-18

摘要: 溶解氧作为水产养殖中最为重要且最容易控制的水质参数,其关系到养殖的成败,如果能精确掌握溶解氧的变化规律,可大大降低养殖风险,增加养殖成功率。本文综合考虑相关水质参数,建立BP神经网络水质预测模型,并在此基础上,构建基于思维进化算法(Mind Evolutionary Computation,MEC)的BP神经网络水质预测模型,通过对广西茅尾海海域的水质历史数据进行仿真实验,结果表明,思维进化BP神经网络预测值的精确度和准确度要高于BP神经网络。因此,将该算法应用于水产养殖水质预测是可行的。

关键词: 溶解氧, 水质预测, BP神经网络, 思维进化算法

Abstract: Dissolved oxygen as the most important and the most easily control water quality parameter of aquaculture relates to the success or failure of aquaculture. If we can accurately grasp the change rule of dissolved oxygen, the risk of breeding will greatly reduce and the breeding success rate will increase. In this paper, considering the related water quality parameters, we established the BP neural network model of water quality prediction. And on this basis, the BP neural network model based on mind evolutionary algorithm (MEC) of water quality prediction was established. Through the simulation of historical data of water quality of Maowei Sea, Guangxi, the results show that the precision and accuracy of predicted value of MECBP neural network is higher than that of the BP neural network. Therefore, it is feasible to apply this algorithm to predict water quality of aquaculture.

Key words: dissolved oxygen, water quality prediction, BP neural network, Mind Evolutionary Computation

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