信息粒的构建及其在系统建模中的应用
发布时间：2021-07-05 09:56
随着信息技术的不断进步,日常生活和工业环境中的数据持续增长,如何理解这些数据的含义从而帮助用户做出决策成为一项严峻而具有挑战性的难题。数值型数据在表述不确定信息时,往往无法达到对数据的完整性和准确性的要求,信息粒为解决这类不确定问题提供了更有效的解决方案。信息粒是基于数据的特征性和近似性精心设计并抽象化的数据集合,它可以完整并准确地表达数据的含义。通过信息粒化,复杂问题被分解为一系列易于处理的子问题,从而降低问题总体成本。在粒计算中,如何构建信息粒以及如何将信息粒应用于生产建模中成为当前亟待解决的问题之一。本文旨在通过对信息粒构建方法的研究,建立一种通用的信息粒构建模型,并在此基础上,进一步研究信息粒的优化以及应用。本文从不同方面对信息粒进行概念和算法上的研究,例如高阶信息粒,尤其是粒区间信息粒的构建（即信息粒的分层结构）、信息粒的优化（粒度数据聚合）以及信息粒在模糊规则模型中的应用等。针对Ⅰ型信息粒描述数据时存在的局限性（比如无法满足实际问题中对描述数据的完整性和准确性的要求）,本文提出一种应用合理粒度准则构建高阶信息粒（即粒区间信息粒）的方法。以往的研究对应用合理粒度准则构建I型信...
【文章来源】：西安电子科技大学陕西省 211工程院校 教育部直属院校
【文章页数】：143 页
【学位级别】：博士
【文章目录】：
ABSTRACT
摘要
List of Symbols
List of Abbrevations
Chapter 1 Introduction
1.1 Backgroud
1.2 Granular Computing:A Literature Review
1.3 Contributions
1.3.1 Organization
1.3.2 Significiance
Chapter 2 Information Granularity:Basic Concepts
2.1 Formalisms of Information Granules
2.1.1 Sets and Intervals
2.1.2 Fuzzy Sets
2.1.3 Rough Sets
2.1.4 Shadowed Sets
2.1.5 Other Formalisms
2.2 Information Granules of Higher Type
2.3 Design Methods of Information Granules
2.3.1 The Principle of Justifiable Granularity
2.3.2 Clustering Algorithms
2.4 Conclusions
Chapter 3 Design of Information Granules of Higher Type and Their Applications to System Modeling
3.1 Granular Computing:Representing and Describing Data with Information Granules
3.2 The Principle of Justifiable Granularity:Conceptual Developments and Underlying Generic Algorithm
3.2.1 Coverage
3.2.2 Specificity
3.2.3 Performance Index
3.3 Development of a Granular Interval
3.4 Application Studies
3.5 Granular Characterization of Numeric Models
3.6 Construction of Multidimentsional Information Granules
3.7 Conclusions
Chapter 4 Granular Data Aggregation:An Adaptive Principle of Justifiable Granularity Approach
4.1 A Framework of Data Aggregation
4.2 Aggregation Mechanisms— A Focused Review
4.3 Adaptive Principle of Justifiable Granularity
4.3.1 Formation of A Numeric Representative
4.3.2 Formation of Information Granules Around Numeric Representative.
4.3.3 Optimization Process
4.4 Experimental Studies
4.4.1 Prediction of Time Series
4.4.2 Prediction in Spatially Distributed Data
4.5 Conclusions
Chapter 5 A Two-Phase Design of Fuzzy Rule-Based Model and Its Applications
5.1 Fuzzy Rule-Based Architecture
5.2 Prerequisites
5.2.1 Formation of Fuzzy Sets of Condition and Conclusion
5.2.2 The Principle of Justifiable Granularity in Developing Information Granules
5.3 Characterization of the Quality of the Rules
5.4 Processing in Granular Rule-Based Model
5.4.1 Formation of Granular Rule-Based Model
5.4.2 Evaluation of Performance of Granular Rule-Based Model
5.5 Experimetal Studies
5.5.1 Synthetic Experiments
5.5.2 Analysis of Fuzzy Rule-Based Model
5.6 Conclusions
Chapter 6 Conclusions and Future Research
6.1 Conclusions
6.2 Future Research
References
Aknowledgement
Biography
本文编号：3265856
【文章来源】：西安电子科技大学陕西省 211工程院校 教育部直属院校
【文章页数】：143 页
【学位级别】：博士
【文章目录】：
ABSTRACT
摘要
List of Symbols
List of Abbrevations
Chapter 1 Introduction
1.1 Backgroud
1.2 Granular Computing:A Literature Review
1.3 Contributions
1.3.1 Organization
1.3.2 Significiance
Chapter 2 Information Granularity:Basic Concepts
2.1 Formalisms of Information Granules
2.1.1 Sets and Intervals
2.1.2 Fuzzy Sets
2.1.3 Rough Sets
2.1.4 Shadowed Sets
2.1.5 Other Formalisms
2.2 Information Granules of Higher Type
2.3 Design Methods of Information Granules
2.3.1 The Principle of Justifiable Granularity
2.3.2 Clustering Algorithms
2.4 Conclusions
Chapter 3 Design of Information Granules of Higher Type and Their Applications to System Modeling
3.1 Granular Computing:Representing and Describing Data with Information Granules
3.2 The Principle of Justifiable Granularity:Conceptual Developments and Underlying Generic Algorithm
3.2.1 Coverage
3.2.2 Specificity
3.2.3 Performance Index
3.3 Development of a Granular Interval
3.4 Application Studies
3.5 Granular Characterization of Numeric Models
3.6 Construction of Multidimentsional Information Granules
3.7 Conclusions
Chapter 4 Granular Data Aggregation:An Adaptive Principle of Justifiable Granularity Approach
4.1 A Framework of Data Aggregation
4.2 Aggregation Mechanisms— A Focused Review
4.3 Adaptive Principle of Justifiable Granularity
4.3.1 Formation of A Numeric Representative
4.3.2 Formation of Information Granules Around Numeric Representative.
4.3.3 Optimization Process
4.4 Experimental Studies
4.4.1 Prediction of Time Series
4.4.2 Prediction in Spatially Distributed Data
4.5 Conclusions
Chapter 5 A Two-Phase Design of Fuzzy Rule-Based Model and Its Applications
5.1 Fuzzy Rule-Based Architecture
5.2 Prerequisites
5.2.1 Formation of Fuzzy Sets of Condition and Conclusion
5.2.2 The Principle of Justifiable Granularity in Developing Information Granules
5.3 Characterization of the Quality of the Rules
5.4 Processing in Granular Rule-Based Model
5.4.1 Formation of Granular Rule-Based Model
5.4.2 Evaluation of Performance of Granular Rule-Based Model
5.5 Experimetal Studies
5.5.1 Synthetic Experiments
5.5.2 Analysis of Fuzzy Rule-Based Model
5.6 Conclusions
Chapter 6 Conclusions and Future Research
6.1 Conclusions
6.2 Future Research
References
Aknowledgement
Biography
本文编号：3265856
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