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不完全信息综合评价方法与应用—基于证据理论和有序加权算子的研究

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Jingdong book

不完全信息综合评价方法与应用—基于证据理论和有序加权算子的研究

Name: 不完全信息综合评价方法与应用—基于证据理论和有序加权算子的研究
Brand: Jingdong book
SKU: 3110104161
Price: 41.66 USD
Availability: OutOfStock

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Content Description

综合评价问题广泛存在于社会、经济、管理等各个领域中，其理论与方法的研究有着广阔的应用前景。由于客观事物的复杂性，以及人们思维能力、知识结构和知识水平的局限性，在评价活动的实践中经常会遇到评价信息不完全的问题，如评价参数的评价信息缺失、残缺判断矩阵、基于分布式结构的不完全综合评价信息及基于被评价对象子集的偏好信息等形式的不完全信息综合评价问题。传统的完全信息综合评价方法对不完全信息综合评价问题难以直接发挥作用，因此有必要对不完全信息下的综合评价方法及其应用进行研究。
Dempster-Shafer（D-S）证据理论是处理不完全信息综合评价问题的重要理论方法。那么，D-S证据理论处理不完全信息综合评价问题需要哪些步骤，D-S证据理论都可以处理什么形式的不完全信息综合评价问题，已有的基于D-S证据理论的不完全信息综合评价处理方法是否完善等，都是值得思考的问题。有序加权平均（OWA）算子是美国著名学者Yager于1988年提出的，此后在管理决策、人工智能、模糊系统等多个领域得到广泛应用。OWA算子及其拓展算子的特点之一就是引入了位置权向量，通过对位置权向量的不同定义体现了其非凡的活力。本书将D-S证据理论与OWA算子理论的信息融合思想结合，对不完全信息综合评价问题进行研究，提出一系列不完全信息综合评价的理论方法。全书共分七章，第一章为绪论。第二章基本理论，介绍本文研究的理论支撑工具：DS证据理论和OWA算子。第三章为考虑信息形式的不完全信息综合评价证据推理方法，研究了几种不同信息形式的不完全信息综合评价问题的证据理论解决方法。第四章为基于诱导有序加权思想的不完全信息综合评价方法，对OWA算子进行了拓展研究，提出了相对优势诱导和绝对优势诱导的不完全信息综合评价方法，以及局部偏离度诱导和整体偏离度诱导的不完全信息综合评价方法。第五章为不完全信息综合评价的诱导有序加权证据推理方法，提出了期望效用诱导的不完全信息综合评价ER方法，以及证据距离诱导的部分属性偏好信息群体赋权方法。第六章为不完全信息综合评价的应用研究，分别探讨了不完全信息多属性综合评价在科技企业孵化器绩效评价中的应用，以及不完全信息动态综合评价在公共支出绩效评价中的应用。第七章为结论与展望。

Author Description

姚爽，1982年5月生，辽宁盖州人，2004年获东北大学金融学专业经济学学士学位，2007年获东北大学数量经济学专业经济学硕士学位，2010年获东北大学管理科学与工程专业管理学博士学位。2010年至今任教于沈阳化工大学经济与管理学院，讲师，硕士生指导教师。主要研究领域为系统评价与决策支持。近年来，在”International Journal of Intelligent Systems”、《管理科学学报》、《系统工程学报》、《系统管理学报》、《控制与决策》、《管理学报》等国内外重要期刊及国际学术会议上发表学术论文20余篇，其中SCI收录2篇，EI收录10篇。主持国家自然科学基金1项，参与国家自然科学基金、国家社会科学基金、教育部人文社会科学研究项目等6项。黄玮强，1982年4月生，福建长汀人，管理学博士，东北大学工商管理学院副教授，博士生指导教师。主要研究领域为金融工程、投资决策。近年来，在“Physica A: Statistical Mechanics and its Applications”、《管理科学学报》、《管理科学》等国内外期刊及国际学术会议上发表学术论文近40篇。主持国家自然科学基金、教育部人文社会科学研究项目、中国博士后科学基金特别资助项目等省部级以上课题5项。现为国家自然科学基金管理科学部同行评议专家，“ Physica A”、《管理科学学报》等杂志审稿专家。

Catalogue

第一章绪论
1．1 综合评价概述
1．1．1 综合评价的概念
1．1．2 综合评价与多属性决策
1．1．3 综合评价研究方法
1．2 不完全信息综合评价
1．2．1 不完全信息综合评价问题的现实意义
1．2．2 不完全信息综合评价问题的一般描述
1．2．3 不完全信息综合评价问题的研究进展
1．2．4 不完全信息综合评价问题的研究述评
1．3 本书论题的提出
1．4 本书的研究目的、研究内容
1．5 本书主要章节安排
1．6 本书数学符号及用语的说明

第二章基本理论
2．1 D-S证据理论
2．1．1 概率的四种解释及其性质
2．1．2 D-S证据理论的基本概念
2．1．3 D-S证据理论的决策规则
2．1．4 基于D-S证据理论的综合评价流程图
2．2 有序加权算子及位置权重
2．2．1 有序加权平均算子
2．2．2 拓展的OWA算子
2．2．3 位置权向量的确定方法
2．3 本章小结

第三章不同信息形式的不完全信息综合评价证据推理方法
3．1 属性值信息缺失形式的DS-AHP方法
3．1．1 问题的背景及描述
3．1．2 问题的解决思路
3．1．3 DS-AHP的分析
3．1．4 DS-AHP方法的改进
3．1．5 DS-AHP方法改进效果
3．2 有限方案子集偏好信息形式的DS/AHP方法
3．2．1 问题的提出
3．2．2 DS/AHP方法及改进
3．2．3 应用例
3．3 基于分布式结构信息形式的ER方法
3．3．1 问题的提出
3．3．2 基本模型
3．3．3 应用例
3．4 本章小结

第四章基于诱导有序加权思想的不完全信息综合评价方法
4．1 基于多维诱导分量的拓展有序加权算子
4．1．1 问题的提出
……
第五章不完全信息综合评价的诱导有序加权证据推理方法
第六章不完全信息综合评价的应用研究
第七章结论与展望
附录
参考文献

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