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Titlebook: Handbook on Data Envelopment Analysis; William W. Cooper,Lawrence M. Seiford,Joe Zhu Book 2011Latest edition Springer Science+Business Med

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發(fā)表于 2025-3-21 16:51:43 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Handbook on Data Envelopment Analysis
編輯William W. Cooper,Lawrence M. Seiford,Joe Zhu
視頻videohttp://file.papertrans.cn/423/422477/422477.mp4
概述Editors are the three of most prominent researchers in the field.Prestigious group of contributors.Brings entire field up to date with new chapters on DEA models for supply chain, DMU’s with internal
叢書(shū)名稱International Series in Operations Research & Management Science
圖書(shū)封面Titlebook: Handbook on Data Envelopment Analysis;  William W. Cooper,Lawrence M. Seiford,Joe Zhu Book 2011Latest edition Springer Science+Business Med
描述.This handbook covers DEA topics that are extensively used and solidly based. The purpose of the handbook is to (1) describe and elucidate the state of the field and (2), where appropriate, extend the frontier of DEA research. It defines the state-of-the-art of DEA methodology and its uses. This handbook is intended to represent a milestone in the progression of DEA. Written by experts, who are generally major contributors to the topics to be covered, it includes a comprehensive review and discussion of basic DEA models, which, in the present issue extensions to the basic DEA methods, and a collection of DEA applications in the areas of banking, engineering, health care, and services. The handbook‘s chapters are organized into two categories: (i) basic DEA models, concepts, and their extensions, and (ii) DEA applications. First edition contributors have returned to update their work..The second edition includes updated versions of selected first edition chapters. New chapters have been added on: different approaches with no need for a priori choices of weights (called “multipliers) that reflect meaningful trade-offs, construction of static and dynamic DEA technologies, slacks-based
出版日期Book 2011Latest edition
關(guān)鍵詞DEA; Data Envelopment Analysis; Econometrics; Operations Research; Production and Operations Management;
版次2
doihttps://doi.org/10.1007/978-1-4419-6151-8
isbn_softcover978-1-4614-2999-9
isbn_ebook978-1-4419-6151-8Series ISSN 0884-8289 Series E-ISSN 2214-7934
issn_series 0884-8289
copyrightSpringer Science+Business Media, LLC 2011
The information of publication is updating

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William W. Cooper,Lawrence M. Seiford,Joe Zhu are not easily accepted by users. Instead, we work with video data captured via mobile cameras, transform the video into time series via human pose estimation, train time series classifiers, and deliver feedback to the user through a time series classification and explanation step. We evaluate our
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Rajiv D. Banker,William W. Cooper,Lawrence M. Seiford,Joe Zhuthat using such models can help to better identify very critical patients in a clinical setting. To elaborate on these models’ usability in practical settings, we describe the user interface design of a prototype developed for emergency settings. Finally, we discuss the scope and limitations of the
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William W. Cooper,Shanling Li,Lawrence M. Seiford,Joe Zhuwithout human intervention. Which modeling technique, learning strategy, and data pre-processing technique work well for epidemic forecasting is still an open problem. To help advance the state-of-the-art in AI/ML applied to epidemiology, a benchmark with a collection of performance points is needed
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Performance of the Bootstrap for DEA Estimators and Iterating the Principle,
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Engineering Applications of Data Envelopment Analysis,
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