Bayesian networks modeling for crop diseases

Abstract

Severe large-scale diseases in agricultural regions have caused significant economic damage. In order to improve crop yields, we develop a framework to predict the occurrence of crop diseases. In the presence of risk and uncertainty, this paper focuses on finding out the best pest control decision-making program which is based on the Bayesian network. The paper describes the flowchart of a Bayesian network and the principles used to calculate the conditional probabilities required in it. The practice proves that BN is an effective tool for crop disease. © 2011 IFIP International Federation for Information Processing.