array(2) { ["lab"]=> string(3) "868" ["publication"]=> string(4) "6357" } An Improved Gray Model For Aquaculture Water Quality Prediction - Computer Vision Research Group（计算机视觉实验室） | LabXing

Computer Vision Research Group（计算机视觉实验室）

简介 计算机视觉与图像处理

大学 中国农业大学 / 信息与电气工程学院
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An Improved Gray Model For Aquaculture Water Quality Prediction

2012
期刊 Intelligent Automation & Soft Computing
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Water quality management is one of the key problems for intensive aquaculture.In order to predict the aquaculture water quality accurately,the paper proposes an Improved Gray Model for aquaculture water quality prediction.The Gray Model is improved and combined with the BP Neural Networks to implement the prediction.The Improved Gray Model serves as the main body for prediction and BP Neural Networks are used to judge the prediction results.Experiments using the temperature and DO data collected from the aquatic factories of Yixing,Dongying in China proved that the prediction accuracy improved 15% than the traditional prediction method.

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