Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
London, United Kingdom San Diego, CA
Academic Press
[2023]
|
| Series: | Uncertainty, computational techniques, and decision intelligence
|
| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9780323994453/?ar |
| Summary: | Classical data envelopment analysis (DEA) models use crisp data to measure the inputs and outputs of a given system. In cases such as manufacturing systems, production processes, service systems, etc., the inputs and outputs may be complex and difficult to measure with classical DEA models. Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex uncertain data, then they will become more important and practical for decision makers.Uncertainty in Data Envelopment Analysis introduces methods to investigate uncertain data in DEA models, providing a deeper look into two types of uncertain DEA methods, fuzzy DEA and belief degree-based uncertainty DEA, which are based on uncertain measures. These models aim to solve problems encountered by classical data analysis in cases where the inputs and outputs of systems and processes are volatile and complex, making measurement difficult. Introduces methods to deal with uncertain data in DEA models, as a source of information and a reference book for researchers and engineers Presents DEA models that can be used for evaluating the outputs of many reallife systems in social and engineering subjects Provides fresh DEA models for efficiency evaluation from the perspective of imprecise data Applies the fuzzy set and uncertainty theories to DEA to produce a new method of dealing with the empirical data. |
| Item Description: | Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on September 21, 2023) |
| Physical Description: | 1 Online-Ressource. |
| ISBN: | 9780323994453 0323994458 |
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| 650 | 4 | |a Incertitude | |
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| id | ZDB-30-ORH-104367458 |
| illustrated | Not Illustrated |
| indexdate | 2025-06-25T12:16:15Z |
| institution | BVB |
| isbn | 9780323994453 0323994458 |
| language | English |
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| series2 | Uncertainty, computational techniques, and decision intelligence |
| spelling | Hosseinzadeh Lotfi, Farhad 1967- VerfasserIn aut Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties Farhad Hosseinzadeh Lotfi, Masoud Sanei, Ali Asghar Hosseinzadeh, Sadegh Niroomand, Ali Mahmoodirad London, United Kingdom San Diego, CA Academic Press [2023] 1 Online-Ressource. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Uncertainty, computational techniques, and decision intelligence Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on September 21, 2023) Classical data envelopment analysis (DEA) models use crisp data to measure the inputs and outputs of a given system. In cases such as manufacturing systems, production processes, service systems, etc., the inputs and outputs may be complex and difficult to measure with classical DEA models. Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex uncertain data, then they will become more important and practical for decision makers.Uncertainty in Data Envelopment Analysis introduces methods to investigate uncertain data in DEA models, providing a deeper look into two types of uncertain DEA methods, fuzzy DEA and belief degree-based uncertainty DEA, which are based on uncertain measures. These models aim to solve problems encountered by classical data analysis in cases where the inputs and outputs of systems and processes are volatile and complex, making measurement difficult. Introduces methods to deal with uncertain data in DEA models, as a source of information and a reference book for researchers and engineers Presents DEA models that can be used for evaluating the outputs of many reallife systems in social and engineering subjects Provides fresh DEA models for efficiency evaluation from the perspective of imprecise data Applies the fuzzy set and uncertainty theories to DEA to produce a new method of dealing with the empirical data. Data envelopment analysis Uncertainty Incertitude Sanei, Masoud VerfasserIn aut Hosseinzadeh, Ali Asghar VerfasserIn aut Niroomand, Sadegh VerfasserIn aut Mahmoodirad, Ali. VerfasserIn aut 032399444X Erscheint auch als Druck-Ausgabe 032399444X |
| spellingShingle | Hosseinzadeh Lotfi, Farhad 1967- Sanei, Masoud Hosseinzadeh, Ali Asghar Niroomand, Sadegh Mahmoodirad, Ali Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties Data envelopment analysis Uncertainty Incertitude |
| title | Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties |
| title_auth | Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties |
| title_exact_search | Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties |
| title_full | Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties Farhad Hosseinzadeh Lotfi, Masoud Sanei, Ali Asghar Hosseinzadeh, Sadegh Niroomand, Ali Mahmoodirad |
| title_fullStr | Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties Farhad Hosseinzadeh Lotfi, Masoud Sanei, Ali Asghar Hosseinzadeh, Sadegh Niroomand, Ali Mahmoodirad |
| title_full_unstemmed | Uncertainty in data envelopment analysis fuzzy and belief degree-based uncertainties Farhad Hosseinzadeh Lotfi, Masoud Sanei, Ali Asghar Hosseinzadeh, Sadegh Niroomand, Ali Mahmoodirad |
| title_short | Uncertainty in data envelopment analysis |
| title_sort | uncertainty in data envelopment analysis fuzzy and belief degree based uncertainties |
| title_sub | fuzzy and belief degree-based uncertainties |
| topic | Data envelopment analysis Uncertainty Incertitude |
| topic_facet | Data envelopment analysis Uncertainty Incertitude |
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