The Use of Convex Least Square Regression to Represent a Fuzzy DEA Model

William Chung

doi:10.1109/ICIMSA.2017.7985612

The Use of Convex Least Square Regression to Represent a Fuzzy DEA Model

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

Abstract

Convex Nonparametric Least Squares (CNLSs) is a nonparametric regression technique to estimate monotonic increasing and convex functions. In addition, CNLS method builds on the same axioms as Data Envelopment Analysis (DEA) and also takes into account noise. This paper is to investigate the use of convex least square regression to represent a fuzzy DEA model. By the results of CNLS, we can repeatedly use the corresponding fuzzy DEA model to assess the performance of unobserved decision making units. Note that DEA results cannot be repeatedly used as the regression results for unobserved entities. The popularity of fuzzy DEA would be enhanced.

Original language	English
Title of host publication	2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA)
Publisher	IEEE
Pages	116-120
ISBN (Electronic)	9781509063352, 978-1-5090-6334-5
DOIs	https://doi.org/10.1109/ICIMSA.2017.7985612
Publication status	Published - Jun 2017
Event	2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA) - TBD, Seoul, Korea, Republic of Duration: 13 Jun 2017 → 15 Jun 2017 http://icatse.org/icimsa2017/ http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=40764

Conference

Conference	2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA)
Abbreviated title	ICIMSA 2017
Place	Korea, Republic of
City	Seoul
Period	13/06/17 → 15/06/17
Internet address	http://icatse.org/icimsa2017/ http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=40764

Research Keywords

Convex least square regression
Fuzzy DEA

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10.1109/ICIMSA.2017.7985612

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title = "The Use of Convex Least Square Regression to Represent a Fuzzy DEA Model",

abstract = "Convex Nonparametric Least Squares (CNLSs) is a nonparametric regression technique to estimate monotonic increasing and convex functions. In addition, CNLS method builds on the same axioms as Data Envelopment Analysis (DEA) and also takes into account noise. This paper is to investigate the use of convex least square regression to represent a fuzzy DEA model. By the results of CNLS, we can repeatedly use the corresponding fuzzy DEA model to assess the performance of unobserved decision making units. Note that DEA results cannot be repeatedly used as the regression results for unobserved entities. The popularity of fuzzy DEA would be enhanced.",

keywords = "Convex least square regression, Fuzzy DEA",

author = "William Chung",

year = "2017",

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doi = "10.1109/ICIMSA.2017.7985612",

language = "English",

pages = "116--120",

booktitle = "2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA)",

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note = "2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA), ICIMSA 2017 ; Conference date: 13-06-2017 Through 15-06-2017",

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Chung, W 2017, The Use of Convex Least Square Regression to Represent a Fuzzy DEA Model. in 2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA)., 7985612, IEEE, pp. 116-120, 2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA), Seoul, Korea, Republic of, 13/06/17. https://doi.org/10.1109/ICIMSA.2017.7985612

The Use of Convex Least Square Regression to Represent a Fuzzy DEA Model. / Chung, William.
2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA). IEEE, 2017. p. 116-120 7985612.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T1 - The Use of Convex Least Square Regression to Represent a Fuzzy DEA Model

AU - Chung, William

PY - 2017/6

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N2 - Convex Nonparametric Least Squares (CNLSs) is a nonparametric regression technique to estimate monotonic increasing and convex functions. In addition, CNLS method builds on the same axioms as Data Envelopment Analysis (DEA) and also takes into account noise. This paper is to investigate the use of convex least square regression to represent a fuzzy DEA model. By the results of CNLS, we can repeatedly use the corresponding fuzzy DEA model to assess the performance of unobserved decision making units. Note that DEA results cannot be repeatedly used as the regression results for unobserved entities. The popularity of fuzzy DEA would be enhanced.

AB - Convex Nonparametric Least Squares (CNLSs) is a nonparametric regression technique to estimate monotonic increasing and convex functions. In addition, CNLS method builds on the same axioms as Data Envelopment Analysis (DEA) and also takes into account noise. This paper is to investigate the use of convex least square regression to represent a fuzzy DEA model. By the results of CNLS, we can repeatedly use the corresponding fuzzy DEA model to assess the performance of unobserved decision making units. Note that DEA results cannot be repeatedly used as the regression results for unobserved entities. The popularity of fuzzy DEA would be enhanced.

KW - Convex least square regression

KW - Fuzzy DEA

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M3 - RGC 32 - Refereed conference paper (with host publication)

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BT - 2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA)

PB - IEEE

T2 - 2017 International Conference on Industrial Engineering, Management Science and Application (ICIMSA)

Y2 - 13 June 2017 through 15 June 2017

ER -

The Use of Convex Least Square Regression to Represent a Fuzzy DEA Model

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