Development of an intelligent system based on ANFIS for predicting wheat grain yield on the basis of energy inputs

作     者：Benyamin Khoshnevisan Shahin Rafiee Mahmoud Omid Hossein Mousazadeh 

作者机构：Department of Agricultural Machinery EngineeringFaculty of Agricultural Engineering and TechnologyUniversity of TehranKarajIran 

出 版 物：《Information Processing in Agriculture》 (农业信息处理（英文）)

年 卷 期：2014年第1卷第1期

页      面：14-22页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 08[工学] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

主　　题：Wheat yield Energy consumption Prediction ANFIS ANN 

摘      要：Energy is regarded as one of the most important elements in agricultural *** the last decades energy consumption in agriculture has increased,so finding the relationship between energy consumption and crop yields in agricultural production can help to achieve sustainable *** this study several adaptive neuro-fuzzy inference system(ANFIS)models were evaluated to predict wheat grain yield on the basis of energy ***,artificial neural networks(ANNs)were developed and the obtained results were compared with ANFIS *** the best ANFIS structure gained in this study,R,RMSE and MAPE were calculated as 0.976,0.046 and 0.4,*** developed ANN was a multilayer perceptron(MLP)with eleven neurons in the input layer,two hidden layers with 32 and 10 neurons and one neuron(wheat grain yield)in the output *** the best ANN model,R,RMSE and MAPE were computed as 0.92,0.9 and 0.1,*** results illustrated that ANFIS model can predict the yield more precisely than ANN.