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《Modern Agricultural Science and Technology》 2016-19
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Study on Prediction Model of Soil Heavy Metal Based on Artificial Neural Network

QIN Xi-chun;YUAN Qi;ZHOU Bao-xuan;College of Mechanical and Electrical Engineering ,Hainan University;  
Changes of heavy metal content in the soil have the characteristics of nonlinear,large time delay,and it is difficult to set up the precise model of soil heavy metal in a traditional way. Artificial neural network has the advantage of approximating the nonlinear function,it is an ideal method for dealing with the complex problems such as prediction of soil heavy metal. A prediction model of soil heavy metal based on artificial neural network was established by applying a dynamic self-adaptive learning method and model optimization.This model was completed by programming with neural network toolbox of MATLAB.The results showed that the average relative error was less than 1% between the value of prediction and the measured value when the trained network was applied in prediction.Prediction model of soil heavy metal which constructed based on artificial neural network has good precision and accuracy,and it can effectively predict the status of heavy metals in soil.
【Fund】: 海南省自然科学基金项目(614223)
【CateGory Index】: S153;TP183
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