文章基本信息

标题：A Survey on Crop Yield Prediction Models
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作者：K. Menaka ; N. Yuvaraj
期刊名称：Indian Journal of Innovations and Developments
印刷版ISSN：2277-5382
电子版ISSN：2277-5390
出版年度：2016
卷号：5
期号：12
页码：1-7
语种：English
出版社：Indian Society for Education and Environment
摘要：Objectives : To analysis various models to improve the prediction of crop yield production. Methods : In this paper, there are different methods has been analyzed to predict the crop yield. The methods such as artificial neural network, Adaptive Neuro-Fuzzy inference System, Fuzzy Logic and Multi Linear Regression are analyzed to know the best methods for crop yield prediction. The prediction of crop yield varied by internal factors and external factors of crop an environment. The internal factors such as pesticides, water level, spacing and fertilizers and the external factors such as temperature, humidity, and rainfall. There are various models were developed to predict the crop yield prediction. This paper provides detailed information about the different models for crop yield prediction. Findings : In this paper various models for crop yield prediction are compared through their parameters such as Root Mean Square Error (RMSE), R 2 ,correlation coefficient and Mean Square Error (MSE) to prove Adaptive NeuroFuzzy Inference System (ANFIS)prediction model is better than other techniques. Application/improvements : The findings of this work prove that the Adaptive Neuro Fuzzy Inference System (ANFIS) prediction model provides better result than other approaches.
其他摘要：Objectives : To analysis various models to improve the prediction of crop yield production. Methods : In this paper, there are different methods has been analyzed to predict the crop yield. The methods such as artificial neural network, Adaptive Neuro-Fuzzy inference System, Fuzzy Logic and Multi Linear Regression are analyzed to know the best methods for crop yield prediction. The prediction of crop yield varied by internal factors and external factors of crop an environment. The internal factors such as pesticides, water level, spacing and fertilizers and the external factors such as temperature, humidity, and rainfall. There are various models were developed to predict the crop yield prediction. This paper provides detailed information about the different models for crop yield prediction. Findings : In this paper various models for crop yield prediction are compared through their parameters such as Root Mean Square Error (RMSE), R 2 ,correlation coefficient and Mean Square Error (MSE) to prove Adaptive NeuroFuzzy Inference System (ANFIS)prediction model is better than other techniques. Application/improvements : The findings of this work prove that the Adaptive Neuro Fuzzy Inference System (ANFIS) prediction model provides better result than other approaches.
关键词：Crop Yield Prediction; Adaptive Neurofuzzy Inference System; Data Mining; Agriculture.