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.
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Bi, C., Chen, G. (2011). Bayesian Networks Modeling for Crop Diseases. In: Li, D., Liu, Y., Chen, Y. (eds) Computer and Computing Technologies in Agriculture IV. CCTA 2010. IFIP Advances in Information and Communication Technology, vol 344. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18333-1_37
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DOI: https://doi.org/10.1007/978-3-642-18333-1_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18332-4
Online ISBN: 978-3-642-18333-1
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