An integrated method for shared power bank supplier selection based on linguistic hesitant fuzzy multi-criteria group decision making

Knowledge-Based Systems, Journal Year: 2024, Volume and Issue: 301, P. 112300 - 112300

Published: Aug. 3, 2024

Language: Английский

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Gauging road safety advances using a hybrid EWM–PROMETHEE II–DBSCAN model with machine learning

Frontiers in Public Health, Journal Year: 2024, Volume and Issue: 12

Published: Aug. 22, 2024

Introduction Enhancing road safety conditions alleviates socioeconomic hazards from traffic accidents and promotes public health. Monitoring progress recalibrating measures are indispensable in this effort. A systematic scientific decision-making model that can achieve defensible decision outputs with substantial reliability stability is essential, particularly for system analyses. Methods We developed a methodology combining the entropy weight method (EWM), preference ranking organization enrichment evaluation (PROMETHEE), density-based spatial clustering of applications noise (DBSCAN)—referred to as EWM–PROMETHEE II–DBSCAN—to support monitoring, measures, action planning. Notably, we enhanced DBSCAN machine learning algorithm (grid search) determine optimal parameters neighborhood radius minimum number points, significantly impacting quality. Results In real case study assessing Southeast Asia, multi-level comparisons validate robustness proposed model, demonstrating its effectiveness decision-making. The integration tool traditional technique forms robust framework, improving data analysis complex environments. This framework addresses DBSCAN’s limitations nearest neighbor search parameter selection, yielding more reliable outcomes, especially small sample scenarios. empirical results provide detailed insights into performance potential areas improvement within Asia. Conclusion offers governmental officials managers credible monitoring overall conditions. Furthermore, it enables policymakers legislators identify strengths drawbacks formulate policies strategies optimize regional safety.

Language: Английский

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Multi-criteria decision-making based on the combination of interval-valued hesitant fuzzy information and ORESTE method

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: May 6, 2024

As an important extension of hesitant fuzzy sets, interval-valued sets (IVHFSs) show the flexibility decision makers (DMs) in expressing information. Accordingly, numerous research findings have been provided since introduction IVHFSs. However, a few issues IVHFS utilization remain to be addressed. To do this, this study introduces multi-criteria decision-making (MCDM) method based on combination information and French organization Rangement et Synthese de Ronnees Relationnelles (ORESTE). First, shortcomings generalized normalized Hamming distance for elements (IVHFEs) previous studies are discussed. Subsequently, several novel measures possibility degree formula developed. Meanwhile, proofs properties illustrate effectiveness proposed formula. Second, MCDM ORESTE is Lastly, problem identifying optimal bidding schemeis presented demonstrate method. Acomparative with other methods conducted identical illustrative example.

Language: Английский

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An enhanced whale optimizer based feature selection technique with effective ensemble classifier for network intrusion detection system

Peer-to-Peer Networking and Applications, Journal Year: 2024, Volume and Issue: 18(2)

Published: Dec. 28, 2024

Language: Английский

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