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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 7-8/2014

01.12.2014 | Original Article

An improved PROMETHEE II method based on Axiomatic Fuzzy Sets

verfasst von: Xiaojuan Tian, Xiaodong Liu, Lidong Wang

Erschienen in: Neural Computing and Applications | Ausgabe 7-8/2014

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Abstract

This paper proposes an improved Preference Ranking Organization Method for Enrichment Evaluations II method based on Axiomatic Fuzzy Sets (AFS). With AFS, the preference functions of alternatives can be easily decided by the ranking and difference degrees of performance values on each attribute. Furthermore, the method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. In case study, the evaluation of the industrial economic benefit of 16 provinces or municipalities of China is used to demonstrate the performance of the proposed method. The ranking results show that the whole evaluating procedure is feasible and effective.
Vorheriger Artikel Backstepping control for output-constrained nonlinear systems based on nonlinear mapping
Nächster Artikel RFID-based intelligent shopping environment: a comprehensive evaluation framework with neural computing approach

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Metadaten
Titel
An improved PROMETHEE II method based on Axiomatic Fuzzy Sets
verfasst von
Xiaojuan Tian
Xiaodong Liu
Lidong Wang
Publikationsdatum
01.12.2014
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 7-8/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1651-8

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