Ebook: Rough Sets: Selected Methods and Applications in Management and Engineering
- Tags: Artificial Intelligence (incl. Robotics), Computer Appl. in Administrative Data Processing
- Series: Advanced Information and Knowledge Processing
- Year: 2012
- Publisher: Springer-Verlag London
- Edition: 1
- Language: English
- pdf
Rough Set Theory, introduced by Pawlak in the early 1980s, has become an important part of soft computing within the last 25 years. However, much of the focus has been on the theoretical understanding of Rough Sets, with a survey of Rough Sets and their applications within business and industry much desired. Rough Sets: Selected Methods and Applications in Management and Engineering provides context to Rough Set theory, with each chapter exploring a real-world application of Rough Sets.
Rough Sets is relevant to managers striving to improve their businesses, industry researchers looking to improve the efficiency of their solutions, and university researchers wanting to apply Rough Sets to real-world problems.
Rough Set Theory was introduced in the early 1980's. In the last quarter century it has become an important part of soft computing and has proved its relevance in many real-world applications.
Initially most articles on Rough Sets were centered on theory, currently though the focus of the research has shifted to practical usage of mathematical advances. With this in mind this book is written for researchers at universities wanting to use Rough Sets to solve real-world problems and needing guidance on how best to describe their ideas in ways not only understandable to industry readers, but also for managers looking for methods to improve their businesses, and researchers in industrial laboratories and think-tanks investigating new methods to enhance the efficiency of their solutions.
Rough Sets: Selected Methods and Applications in Management and Engineering is unique in its focus on use cases backed by sound theory in contrast to the presentation of a theory applied to a problem. A diverse range of applications, including coverage of methods in data analysis, decision support as well as management and engineering, demonstrates the great potential of Rough Sets in almost any domain.
Rough Set Theory was introduced in the early 1980's. In the last quarter century it has become an important part of soft computing and has proved its relevance in many real-world applications.
Initially most articles on Rough Sets were centered on theory, currently though the focus of the research has shifted to practical usage of mathematical advances. With this in mind this book is written for researchers at universities wanting to use Rough Sets to solve real-world problems and needing guidance on how best to describe their ideas in ways not only understandable to industry readers, but also for managers looking for methods to improve their businesses, and researchers in industrial laboratories and think-tanks investigating new methods to enhance the efficiency of their solutions.
Rough Sets: Selected Methods and Applications in Management and Engineering is unique in its focus on use cases backed by sound theory in contrast to the presentation of a theory applied to a problem. A diverse range of applications, including coverage of methods in data analysis, decision support as well as management and engineering, demonstrates the great potential of Rough Sets in almost any domain.
Content:
Front Matter....Pages I-X
Front Matter....Pages 1-1
An Introduction to Rough Sets....Pages 3-20
Front Matter....Pages 21-21
Applying Rough Set Concepts to Clustering....Pages 23-37
Rough Clustering Approaches for Dynamic Environments....Pages 39-50
Feature Selection, Classification and Rule Generation Using Rough Sets....Pages 51-76
Front Matter....Pages 77-77
Three-Way Decisions Using Rough Sets....Pages 79-93
Rough Set Based Decision Support—Models Easy to Interpret....Pages 95-112
Front Matter....Pages 113-113
Financial Series Forecasting Using Dual Rough Support Vector Regression....Pages 115-127
Grounding Information Technology Project Critical Success Factors Within the Organization....Pages 129-142
Workflow Management Supported by Rough Set Concepts....Pages 143-160
Front Matter....Pages 161-161
Rough Natural Hazards Monitoring....Pages 163-179
Nearness of Associated Rough Sets....Pages 181-205
Back Matter....Pages 207-214
Rough Set Theory was introduced in the early 1980's. In the last quarter century it has become an important part of soft computing and has proved its relevance in many real-world applications.
Initially most articles on Rough Sets were centered on theory, currently though the focus of the research has shifted to practical usage of mathematical advances. With this in mind this book is written for researchers at universities wanting to use Rough Sets to solve real-world problems and needing guidance on how best to describe their ideas in ways not only understandable to industry readers, but also for managers looking for methods to improve their businesses, and researchers in industrial laboratories and think-tanks investigating new methods to enhance the efficiency of their solutions.
Rough Sets: Selected Methods and Applications in Management and Engineering is unique in its focus on use cases backed by sound theory in contrast to the presentation of a theory applied to a problem. A diverse range of applications, including coverage of methods in data analysis, decision support as well as management and engineering, demonstrates the great potential of Rough Sets in almost any domain.
Content:
Front Matter....Pages I-X
Front Matter....Pages 1-1
An Introduction to Rough Sets....Pages 3-20
Front Matter....Pages 21-21
Applying Rough Set Concepts to Clustering....Pages 23-37
Rough Clustering Approaches for Dynamic Environments....Pages 39-50
Feature Selection, Classification and Rule Generation Using Rough Sets....Pages 51-76
Front Matter....Pages 77-77
Three-Way Decisions Using Rough Sets....Pages 79-93
Rough Set Based Decision Support—Models Easy to Interpret....Pages 95-112
Front Matter....Pages 113-113
Financial Series Forecasting Using Dual Rough Support Vector Regression....Pages 115-127
Grounding Information Technology Project Critical Success Factors Within the Organization....Pages 129-142
Workflow Management Supported by Rough Set Concepts....Pages 143-160
Front Matter....Pages 161-161
Rough Natural Hazards Monitoring....Pages 163-179
Nearness of Associated Rough Sets....Pages 181-205
Back Matter....Pages 207-214
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