文章基本信息

标题：An Efficient Method for Assessing Water Quality Based on Bayesian Belief Networks
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作者：Khalil Shihab ; Nida Al-Chalabi
期刊名称：International Journal on Soft Computing
电子版ISSN：2229-7103
出版年度：2014
卷号：5
期号：2
页码：21
DOI：10.5121/ijsc.2014.5203
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：A new methodology is developed to analyse existing water quality monitoring networks. This methodologyincorporates different aspects of monitoring, including vulnerability/probability assessment, environmentalhealth risk, the value of information, and redundancy reduction. The work starts with a formulation of aconceptual framework for groundwater quality monitoring to represent the methodology’s context. Thiswork presents the development of Bayesian techniques for the assessment of groundwater quality. Theprimary aim is to develop a predictive model and a computer system to assess and predict the impact ofpollutants on the water column. The process of the analysis begins by postulating a model in light of allavailable knowledge taken from relevant phenomenon. The previous knowledge as represented by the priordistribution of the model parameters is then combined with the new data through Bayes’ theorem to yieldthe current knowledge represented by the posterior distribution of model parameters. This process ofupdating information about the unknown model parameters is then repeated in a sequential manner asmore and more new information becomes available.
关键词：Bayesian Belief Networks; Water Quality Assessment; Data Mining