基于贝叶斯网络的流域污染源综合管理体系研究

项目名称： 基于贝叶斯网络的流域污染源综合管理体系研究

项目编号： No.71203041

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 宏观管理与政策

项目作者： 赵英

作者单位： 哈尔滨工业大学

项目金额： 19万元

中文摘要： 深化主要污染物总量减排，努力改善环境质量，防范环境风险是国家"十二五"环境保护规划的主体目标。本项目拟围绕当前我国流域环境管理实践中存在问题,在对国内外流域污染源管理模式充分调研的基础上，以我国目前污染源复杂且污染严重的阿什河流域为研究对象,开展流域污染源综合管理方法体系研究。提出建立流域全局角度下污染源综合管理模式的贝叶斯网络（BN）普适性建模方法，应用计算智能方法研究可提高模型推理能力和可靠性的流域污染源综合管理致优因素和策略，利用多目标决策法和贝叶斯决策网（BDN）建立决策方案和考核指标的数据库和方法库，进而探讨污染源排放削减最优管理策略，最终基于WebGIS研究建立阿什河流域污染源综合管理数字化平台系统。从而提高我国水环境管理理论与技术水平，增强国家的宏观调控管理能力，为流域污染源综合管理决策和污染源排放削减策略提供科技支撑和方法保证。

中文关键词： 贝叶斯估计法；不确定性；污染源管理；季节模型；水质管理

英文摘要： The subject goal of The Twelfth Five-Year Guideline for National Environmental Protection is that reducing pollutant total amount, improving environment quality and preventing environment risk. Concentrating on these problems existing in the watershed pollution sources management，based on studying on the international management mode of pollution sources at present adequately，we choose the the watershed of Ashen river with complex pollution sources and serious pollution realities as our study object and begin the method system study of watershed pollution sources comprehensive management. This project will put forward a modeling method of Bayesian Network (BN) of comprehensive management of pollution sources from the view of overall watershed that can be generally used. By using computational intelligence to study the optimizing factors and strategies of watershed comprehensive management of pollution sources which can improve the reasoning ability and reliability of modeling, and combining Multi-objective Decision-making method and Bayesian Decision Network to establish the data base and method base of decision-making schemes and evaluation indexes, optimal management strategies for emission reduction of pollution sources will be further discussed and finally the digital platform system of pollution source comp

英文关键词： Bayesian；Uncertainty；Pollution source management；Seasonal model；Water quality management