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Type :article
ISSN :1868-5137
Main Author :Abdullah Hussein Abdullah Al-Amoodi
Title :DAS benchmarking methodology based on FWZIC II and FDOSM II to support industrial community characteristics in the design and implementation of advanced driver assistance systems in vehicles
Place of Production :Tanjung Malim
Publisher :Fakulti Komputeran dan Meta Teknologi
Year of Publication :2023
Notes :Journal of Ambient Intelligence and Humanized Computing
Corporate Name :Universiti Pendidikan Sultan Idris
HTTP Link :Click to view web link

Abstract : Universiti Pendidikan Sultan Idris
This study proposed a novel methodology of data acquisition systems (DASs) benchmarking based on fuzzy-weighted zero-inconsistency (FWZIC II) and fuzzy decision by opinion score method (FDOSM II), which are applied in an intuitionistic fuzzy set (IFS) context and account for hesitation when benchmarking DASs, to support industrial community characteristics in the design and implementation of advanced driver assistance systems in vehicles. The proposed methodology comprises two consecutive phases. The first phase involves constructing a decision matrix based on the intersection of the DAS alternatives and criteria. The second phase (development phase) proposes the formulation of a novel FWZIC II to weight the criteria and the formulation of a novel FDOSM II to benchmark DASs. Fourteen DASs were benchmarked based on the 15 DAS criteria, which included seven sub-criteria for comprehensive complexity assessment and eight sub-criteria for design and implementation, which had a significant effect on the DAS design when implemented by industrial communities. A systematic ranking and sensitivity analysis were conducted to demonstrate that the benchmarking results were subject to systematic ranking, as indicated by the high correlations across all described scenarios of changing criteria weight values. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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