Bayesian Network and Factor Analysis for Modeling Pine Wilt Disease Prevalence

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ISSN Print: 1945-3116
ISSN Online: 1945-3124
www.scirp.org/journal/jsea
E-mail: jsea@scirp.org

"Bayesian Network and Factor Analysis for Modeling Pine Wilt Disease Prevalence"
written by Mingxiang Huang, Liang Guo, Jianhua Gong, Weijun Yang,
published by Journal of Software Engineering and Applications, Vol.6 No.3B, 2013

has been cited by the following article(s):

[1]	基于加权信息量模型的油松毛虫灾害发生危险性评价
	2019

[2]	Using an evapo-transpiration model (ETpN) to predict the risk and expression of symptoms of pine wilt disease (PWD) across Europe
	Biological Invasions, 2016

[3]	Spatial analysis of invasive alien plant distribution patterns and processes using bayesian network-based data mining techniques
	2016

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[1]	Impact of stand‐ and landscape‐level variables on pine wilt disease‐caused tree mortality in pine forests Pest Management Science, 2023 DOI:10.1002/ps.7357

[2]	Using an evapo-transpiration model (ETpN) to predict the risk and expression of symptoms of pine wilt disease (PWD) across Europe Biological Invasions, 2016 DOI:10.1007/s10530-016-1173-7