東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Analytical decision making and data envelopment analysis = advances and challenges /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analytical decision making and data envelopment analysis/ edited by S.A Edalatpanah ... [et al.].
Reminder of title:	advances and challenges /
other author:	Edalatpanah, S. A.
Published:	Singapore :Springer Nature Singapore : : 2024.,
Description:	xi, 489 p. :ill. (chiefly color), digital ;24 cm.
[NT 15003449]:	Chapter 1 Merging Data Envelopment Analysis and Atructural Risk Minimization: Some Examples of Use of Multi-Output Machine Learning Techniques on Real-World Data -- Chapter 2 A New Network Data Envelopment Analysis Model for Efficacy Evaluation of Decision-Making Units -- Chapter 3 Possibilistic Network DEA Approach for Performance Evaluation of Two-Stage Decision-Making Units under Uncertainty.
Contained By:	Springer Nature eBook
Subject:	Data envelopment analysis. -
Online resource:	https://doi.org/10.1007/978-981-97-6972-8
ISBN:	9789819769728

Analytical decision making and data envelopment analysis = advances and challenges /
Analytical decision making and data envelopment analysisadvances and challenges /[electronic resource] :edited by S.A Edalatpanah ... [et al.]. - Singapore :Springer Nature Singapore :2024. - xi, 489 p. :ill. (chiefly color), digital ;24 cm. - Infosys science foundation series in mathematical sciences,2364-4044. - Infosys science foundation series in mathematical sciences..

Chapter 1 Merging Data Envelopment Analysis and Atructural Risk Minimization: Some Examples of Use of Multi-Output Machine Learning Techniques on Real-World Data -- Chapter 2 A New Network Data Envelopment Analysis Model for Efficacy Evaluation of Decision-Making Units -- Chapter 3 Possibilistic Network DEA Approach for Performance Evaluation of Two-Stage Decision-Making Units under Uncertainty.

This book explores the intersection of data envelopment analysis (DEA) and various analytical decision-making methodologies. Featuring contributions from experts in the field from across the world, each chapter delves into different aspects of DEA and its applications in real-world scenarios. The book covers a wide range of topics, including integrating DEA with machine learning techniques, performance evaluation in diverse sectors like banking and civil engineering, and using DEA in managerial decision-making. It also examines data mining during the Covid-19 pandemic and the application of blockchain and IoT in supply chain management. The book offers a deep dive into the evolution of nonparametric frontier methods and the development of new optimization algorithms, addressing the complexities of modern analytical decision-making tools. A few chapters delve into futuristic topics like fuzzy sets and their extensions in decision-making and exploring e-learning platforms for education. This book is an invaluable resource for researchers, practitioners and students interested in the latest DEA advancements and practical applications in various fields. Its multidisciplinary approach makes it a useful addition to the libraries of those seeking to understand the complexities and potentials of modern analytical decision-making tools.

ISBN: 9789819769728

Standard No.: 10.1007/978-981-97-6972-8doiSubjects--Topical Terms:

630049
Data envelopment analysis.

LC Class. No.: HA31.38

Dewey Class. No.: 519.72

Analytical decision making and data envelopment analysis = advances and challenges /
LDR:02933nmm a2200361 a 4500 001 2380379
003 DE-He213
005 20241029115555.0
006 m d
007 cr nn 008maaau
008 250418s2024 si s 0 eng d
020 $a 9789819769728 $q (electronic bk.)
020 $a 9789819769711 $q (paper)
024 7 $a 10.1007/978-981-97-6972-8 $2 doi
035 $a 978-981-97-6972-8
040 $a GP $c GP
041 0 $a eng
050 4 $a HA31.38
072 7 $a KJT $2 bicssc
072 7 $a KJMD $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJMD $2 thema
082 0 4 $a 519.72 $2 23
090 $a HA31.38 $b .A532 2024
245 0 0 $a Analytical decision making and data envelopment analysis $h [electronic resource] : $b advances and challenges / $c edited by S.A Edalatpanah ... [et al.].
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2024.
300 $a xi, 489 p. : $b ill. (chiefly color), digital ; $c 24 cm.
490 1 $a Infosys science foundation series in mathematical sciences, $x 2364-4044
505 0 $a Chapter 1 Merging Data Envelopment Analysis and Atructural Risk Minimization: Some Examples of Use of Multi-Output Machine Learning Techniques on Real-World Data -- Chapter 2 A New Network Data Envelopment Analysis Model for Efficacy Evaluation of Decision-Making Units -- Chapter 3 Possibilistic Network DEA Approach for Performance Evaluation of Two-Stage Decision-Making Units under Uncertainty.
520 $a This book explores the intersection of data envelopment analysis (DEA) and various analytical decision-making methodologies. Featuring contributions from experts in the field from across the world, each chapter delves into different aspects of DEA and its applications in real-world scenarios. The book covers a wide range of topics, including integrating DEA with machine learning techniques, performance evaluation in diverse sectors like banking and civil engineering, and using DEA in managerial decision-making. It also examines data mining during the Covid-19 pandemic and the application of blockchain and IoT in supply chain management. The book offers a deep dive into the evolution of nonparametric frontier methods and the development of new optimization algorithms, addressing the complexities of modern analytical decision-making tools. A few chapters delve into futuristic topics like fuzzy sets and their extensions in decision-making and exploring e-learning platforms for education. This book is an invaluable resource for researchers, practitioners and students interested in the latest DEA advancements and practical applications in various fields. Its multidisciplinary approach makes it a useful addition to the libraries of those seeking to understand the complexities and potentials of modern analytical decision-making tools.
650 0 $a Data envelopment analysis. $3 630049
650 0 $a Decision making. $3 517204
650 1 4 $a Operations Research and Decision Theory. $3 3591727
650 2 4 $a Computational Complexity. $3 3538876
700 1 $a Edalatpanah, S. A. $3 3733793
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Infosys science foundation series in mathematical sciences. $3 3518533
856 4 0 $u https://doi.org/10.1007/978-981-97-6972-8
950 $a Mathematics and Statistics (SpringerNature-11649)