"Crop Prediction Under Disease (grass grub insect) Condition Using Hybrid Approach of Weighted K-Mean and Evolutionary Techniques."

Authors

Manpreet Kaur, Research Scholar, Department of Computer Applications, Guru Kashi University, Talwandi Sabo, PB, India.

Dr. Dinesh Kumar, Associate Professor
Department of CSE, Guru Kashi University, Talwandi Sabo, PB, India.

Abstract

Data analytics is the main focusing point for different fields. Agriculture field is the new entrant to the data analytics. It specifically picks the data related to agriculture different parameters and evaluates the parameters with different machine learning algorithms. In proposed technique the agriculture disease prediction based on different parameters has been evaluated. These parameters are related to patient different aspects like previous years produce, diseases etc. The proposed technique for the prediction is weighted k-mean and logistic regression. The proposed technique is showing better results in terms of accuracy, precision and recall. The accuracy improvement is around 1.67%, Recall is improved by 1.15% and precision is improved by 3.15%.