Forecasting the Crop Yield Production in Trichy District Using Fuzzy C-Means Algorithm and Multilayer Perceptron (MLP)

Geetha M. C. S. and Elizabeth Shanthi I.
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Geetha M. C. S.: Kumaraguru College of Technology, India
Elizabeth Shanthi I.: Avinashilingam Institution for Home Science and Higher Education for Women, India

International Journal of Knowledge and Systems Science (IJKSS), 2020, vol. 11, issue 3, 83-98

Abstract: The agricultural stock depends upon several factors like biological, seasonal, and economic determinants. The growers sustain a vital loss if they are not capable of predicting the variations in these circumstances. The uncertainty on crop yield can be predicted in a logical and mathematical way. The forecast is made based on the previous archives of yield data secured from that area. Data mining is one such procedure practised to predict the crop yield. The systems examine the data, and on mining, several patterns based on numerous parameters predict the return. This article directs on crop yield forecast in Trichy district by adopting data mining techniques for rule formation on classifying the training data and implementing prediction for test data. The suggested method employs fuzzy C means algorithm for clustering and multilayer perceptron design for prediction. The results of accuracy and execution time of the proposed system correlated with the regression algorithm of prediction.

Date: 2020
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