Data Mining Techniques for Detection and Prediction of Crop Diseases and Pests

Data Mining Techniques for Detection and Prediction of Crop Diseases and Pests

Simrandeep Kaur, M.Tech CSE

Dr.Gurpreet Singh, Professor in CSE

Er. Kajal, Assistant Professor in CSE

St. Soldier Institute of Engg. & Technology, Near NIT, Jalandhar

Abstract: Agriculture research is rapidly growing, due to advancement of technologies and upcoming challenges. It has been proven to be leading role in improving the overall growth rate of any country. Especially in India, there is a dire need to do extensive research for better productivity in agriculture. To improve the growth rate of agriculture, researchers of this domain used different data mining techniques to solve agriculture related problems. Data mining approaches such as classification helps to predict the crops diseases, production and loss. It supports farmer while taking right decisions. This research focuses on prediction of loss due to various insect. We analyze the damages by using well-known classifiers such as AdaBoostM1, Proposed Technique AdvC4.5, PART, Ridor and design Ensemble Models of above mentioned classifiers which gave better results as compared to classifiers.

Keywords: AdvC4.5, PART, DM