Supply chain performance evaluation model for integrated circuit industry based on fuzzy analytic hierarchy process and fuzzy neural network
Abstract: To foster the advancement of telecommunications enterprise supply chains and facilitate their transition toward global market competitiveness, the author advocates for a novel performance evaluation framework tailored for the integrated circuit industry supply chain. This framework integrates the fuzzy analytic hierarchy process and fuzzy neural network methodologies to devise a comprehensive supplier performance assessment model. Leveraging extensive historical supplier data, the author employs MATLAB’s neural network toolbox for model training and simulation. The results indicate that the error value output after running the validation sample is relatively small. This indicates that the model can be effectively applied to the performance evaluation of common integrated circuit product suppliers in CM company. According to the performance results of the model application, all participating suppliers have performance scores greater than 0.7, indicating that in the supply and service process of butterfly integrated circuit products, the performance evaluation scores of each supplier meet the requirements of qualified suppliers, among them, suppliers DS1, DS8, and DS9 with a comprehensive performance score greater than 0.8 are relatively excellent suppliers. The model’s effectiveness and accuracy have been confirmed, demonstrating its practical applicability to CM Company. Moreover, its insights provide valuable guidance for establishing supplier performance evaluation systems across various product categories within telecommunications enterprises.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Supply chain performance evaluation model for integrated circuit industry based on fuzzy analytic hierarchy process and fuzzy neural network ; volume:34 ; number:1 ; year:2025 ; extent:15
Journal of intelligent systems ; 34, Heft 1 (2025) (gesamt 15)
- Urheber
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Chen, Qian
Wang, Xiangping
- DOI
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10.1515/jisys-2024-0370
- URN
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urn:nbn:de:101:1-2503110605421.388469021355
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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15.08.2025, 07:26 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Chen, Qian
- Wang, Xiangping
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