Uncertain Data Envelopment Analysis
Language: English
Published by Springer Berlin Heidelberg, 2014
- Hardcover
- New
Condition: New
£ 41.70
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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The first book comprehensively introduces uncertain DEAA comprehensive coverage of models, sensitivity, ranking criteria and congestion in uncertain DEAThe book is classified by measures rather than modelsThis book is intended to.
Seller Inventory # 5227510
- Title
- Uncertain Data Envelopment Analysis
- Author
- Meilin Wen
- Publisher
- Springer Berlin Heidelberg
- Publication year
- 2014
- Condition
- New
- Binding
- Gebunden
- Language
- English
- ISBN 10
- 3662438011
- ISBN 13
- 9783662438015
- Seller catalogs
- Sozialwissenschaften/Recht/Wirtschaft
This book is intended to present the milestones in the progression of uncertain Data envelopment analysis (DEA). Chapter 1 gives some basic introduction to uncertain theories, including probability theory, credibility theory, uncertainty theory and chance theory. Chapter 2 presents a comprehensive review and discussion of basic DEA models. The stochastic DEA is introduced in Chapter 3, in which the inputs and outputs are assumed to be random variables. To obtain the probability distribution of a random variable, a lot of samples are needed to apply the statistics inference approach. Chapter 4 and 5 provide two uncertain DEA methods to evaluate the DMUs with limited or insufficient statistical data, named fuzzy DEA and uncertain DEA. In order to evaluate the DMUs in which uncertainty and randomness appear simultaneously, the hybrid DEA based on chance theory is presented in Chapter 6.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This book is intended to present the milestones in the progression of uncertain Data envelopment analysis (DEA). Chapter 1 gives some basic introduction to uncertain theories, including probability theory, credibility theory, uncertainty theory and chance theory. Chapter 2 presents a comprehensive review and discussion of basic DEA models. The stochastic DEA is introduced in Chapter 3, in which the inputs and outputs are assumed to be random variables. To obtain the probability distribution of a random variable, a lot of samples are needed to apply the statistics inference approach. Chapter 4 and 5 provide two uncertain DEA methods to evaluate the DMUs with limited or insufficient statistical data, named fuzzy DEA and uncertain DEA. In order to evaluate the DMUs in which uncertainty and randomness appear simultaneously, the hybrid DEA based on chance theory is presented in Chapter 6.
"About the title" may belong to another edition of this title.
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