research-article

Prediction of Supplier Performance: A Novel Dea-Anfis Based Approach

Authors:

Rohaifa Khaldi,

Raddouane Chiheb,

Abdellatif El Afia,

Adil Akaaboune,

Rdouan FaiziAuthors Info & Claims

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

Article No.: 60, Pages 1 - 6

https://doi.org/10.1145/3090354.3090416

Published: 29 March 2017 Publication History

Abstract

The focus of this paper is on investigating the feasibility of using ANFIS combined with DEA for supplier's post-evaluation. The proposed framework aims at modeling performance measurement, and forecasting of a selected hospital's drug suppliers. Even though it is broadly employed as a benchmarking tool to evaluate DMUs efficiency, DEA can hardly be used to predict the performance of unseen DMUs. For this reason, ANFIS model has been integrated to DEA due to its nonlinear mapping, strong generalization capabilities and pattern prediction functionalities. DEA based BCC model is used to evaluate the efficiency scores of a set of suppliers, then ANFIS intervenes to learn DEA patterns and to forecast the performance of new suppliers. The results of this research highlight the prediction power of the proposed model in a new scope. They present it as an efficient benchmarking tool and a promising decision support system applied at the operational level.

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Cited By

Bouzbita SAfia A(2022)A Fuzzy Meta Model for Adjusting Ant Colony System ParametersProceedings of the 5th International Conference on Big Data and Internet of Things10.1007/978-3-031-07969-6_4(48-58)Online publication date: 3-Jul-2022
https://doi.org/10.1007/978-3-031-07969-6_4
Khaldi RAfia AChiheb R(2019)Performance prediction of pharmaceutical suppliersInternational Journal of Computer Applications in Technology10.1504/ijcat.2019.10117260:4(317-325)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1504/ijcat.2019.101172
Khaldi REl Afia AChiheb RLazaar MDuvallet CAl Achhab MMahboub OSilkan H(2019)Impact of Multistep Forecasting Strategies on Recurrent Neural Networks Performance for Short and Long HorizonsProceedings of the 4th International Conference on Big Data and Internet of Things10.1145/3372938.3372979(1-8)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3372938.3372979
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Index Terms

Prediction of Supplier Performance: A Novel Dea-Anfis Based Approach
1. Applied computing
  1. Operations research
    1. Forecasting
2. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

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cover image ACM Other conferences

BDCA'17: Proceedings of the 2nd international Conference on Big Data, Cloud and Applications

March 2017

685 pages

ISBN:9781450348522

DOI:10.1145/3090354

Conference Chairs:
Mohamed Lazaar
ENSA, Tetuan, Morocco
,
Youness Tabii
ENSA, Tetuan, Morocco
,
Mohamed Chrayah
ENSA, Tetuan - Morocco
,
Mohammed Al Achhab
ENSA, Tetuan, Morocco

Copyright © 2017 ACM.

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Ministère de I'enseignement supérieur: Ministère de I'enseignement supérieur

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2017

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BDCA'17

BDCA'17: 2nd international Conference on Big Data, Cloud and Applications

March 29 - 30, 2017

Tetouan, Morocco

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Cited By

Bouzbita SAfia A(2022)A Fuzzy Meta Model for Adjusting Ant Colony System ParametersProceedings of the 5th International Conference on Big Data and Internet of Things10.1007/978-3-031-07969-6_4(48-58)Online publication date: 3-Jul-2022
https://doi.org/10.1007/978-3-031-07969-6_4
Khaldi RAfia AChiheb R(2019)Performance prediction of pharmaceutical suppliersInternational Journal of Computer Applications in Technology10.1504/ijcat.2019.10117260:4(317-325)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1504/ijcat.2019.101172
Khaldi REl Afia AChiheb RLazaar MDuvallet CAl Achhab MMahboub OSilkan H(2019)Impact of Multistep Forecasting Strategies on Recurrent Neural Networks Performance for Short and Long HorizonsProceedings of the 4th International Conference on Big Data and Internet of Things10.1145/3372938.3372979(1-8)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3372938.3372979
Bounabi MEl Moutaouakil KSatori KLazaar MDuvallet CAl Achhab MMahboub OSilkan H(2019)Text classification using Fuzzy TF-IDF and Machine Learning ModelsProceedings of the 4th International Conference on Big Data and Internet of Things10.1145/3372938.3372956(1-6)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3372938.3372956
Mezouar HEl Afia ALazaar MDuvallet CAl Achhab MMahboub OSilkan H(2019)A 4-level reference for self-adaptive processes based on SCOR and integrating Q-LearningProceedings of the 4th International Conference on Big Data and Internet of Things10.1145/3372938.3372953(1-5)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3372938.3372953
AlAfandy KOmara HLazaar MAl Achhab MLazaar MDuvallet CAl Achhab MMahboub OSilkan H(2019)Artificial Neural Networks Optimization and Convolution Neural Networks to Classifying Images in Remote SensingProceedings of the 4th International Conference on Big Data and Internet of Things10.1145/3372938.3372945(1-8)Online publication date: 23-Oct-2019
https://dl.acm.org/doi/10.1145/3372938.3372945
Khaldi REl Afia AChiheb R(2019)Forecasting of BTC volatility: comparative study between parametric and nonparametric modelsProgress in Artificial Intelligence10.1007/s13748-019-00196-w8:4(511-523)Online publication date: 1-Dec-2019
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Khaldi REl Afia AChiheb RFaizi R(2018)Forecasting of Bitcoin Daily Returns with EEMD-ELMAN based ModelProceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications10.1145/3230905.3230948(1-6)Online publication date: 2-May-2018
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Sarhani MEl Afia A(2018)Generalization enhancement of support vector regression in electric load forecasting with model selectionProceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications10.1145/3230905.3230947(1-6)Online publication date: 2-May-2018
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Khaldi RChiheb REl Afia A(2018)Feedforward and Recurrent Neural Networks for Time Series ForecastingProceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications10.1145/3230905.3230946(1-6)Online publication date: 2-May-2018
https://dl.acm.org/doi/10.1145/3230905.3230946

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