AN EFFICIENT METHOD F OR ASSESSING WATER QUALITY BASED ON BAYESIAN BELIEF N ETWORKS
AN EFFICIENT METHOD F OR ASSESSING WATER QUALITY BASED ON BAYESIAN BELIEF N ETWORKS
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一种基于贝叶斯信念网络的高效水质评估方法
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Nida Al
中科院分区：
文献类型：
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作者：
K. Shihab;Nida Al
提出了一种新的水质监测网络分析方法。这种方法结合了监测的不同方面，包括脆弱性/概率评估、环境健康风险、信息价值和冗余度减少。这项工作首先制定了一个概念框架，地下水水质监测代表的方法的背景。这项工作提出了贝叶斯技术的发展，地下水水质评价。主要目的是开发一个预测模型和一个计算机系统，以评估和预测污染物对水体的影响。分析过程首先根据从相关现象中获得的所有可用知识假设一个模型。由模型参数的先验分布表示的先前知识然后通过贝叶斯定理与新数据组合以产生由模型参数的后验分布表示的当前知识。然后，随着越来越多的新信息变得可用，以顺序的方式重复更新关于未知模型参数的信息的过程。
A new methodology is developed to analyse existingwater quality monitoring networks. This methodology incorporates different aspects ofmonitoring, including vulnerability/probability assessment, environmental health risk, the value of information, and redundancy redu ction. The work starts with a formulation of a conceptual framework for groundwater quality monitoringto represent the methodology’s context. This work presents the development of Bayesian techniques for the assessment of groundwater quality. The primary aim is to develop a predictive model and a computer system to assess and predict the impact of pollutants on the water column. The process of the analysis begins by postulating a model in light of al available knowledge taken from relevant phenomenon. The previous knowledge as represented by the prior distribution of the model parameters is then combined with the new data through Bayes’ theorem to yield the current knowledge represented by the posterior distribution of model parameters. This process of updating information about the unknown model parameters is then repeated in a sequential manner as more and more new information becomes available.