WHEAT YIELD PREDICTION USING NEURAL NETWORK AND INTEGRATED SVM-NN WITH REGRESSION

Abstract

The production of wheat plays an important role in Pakistan’s economy. Wheat yield forecasting is significant farming problem as it’s the most important crop of Pakistan. Prediction of the wheat yield has been determined by data mining techniques with different environmental factors. Data mining techniques have been developed for analysing and implementation on wheat yield dataset to predict the yield which is very helpful to produce wheat. In this study, Neural Network and a Novel Integrated approach of Neural Network, Support Vector Machine and Regression are used to analyze and estimates the wheat yield production. We have used these predictive techniques with area, yield, production, soil pH, temperature, air pressure, rainfall, water availability, humidity, pesticides and fertilizer parameter for wheat yield prediction