Journal article
Enhancing fuzzy evidential reasoning approach using dynamic adjustment mechanism and new rule-based transformation for engineering emergency response evaluation
Engineering applications of artificial intelligence, v 123
Aug 2023
Abstract
With the frequent occurrence of various emergency events in engineering field, engineering emergency response (EER) evaluation plays an increasingly significant role in handling such situations and provides great challenges to research since the uncertain information and the urgent response time. Aiming at achieving timely and effective emergency response, an enhanced evidential reasoning (ER) approach based on the dynamic adjustment mechanism and new rule-based transformation is proposed. First, the linguistic terms to represent various preference information provided by experts are encoded into the trapezoidal interval type-2 fuzzy sets (TrIT2FSs) with different granularities. Second, for ensuring the validity of the information, based on the definition of the expert decision risk preference coefficients, a dynamic adjustment mechanism is constructed to identify and adjust the preference information. Meanwhile, combined with social network, the experts’ weights can be calculated and revised several times to obtain group information. Then, a new rule-based transformation and related optimization models are proposed to convert the TrIT2FSs into interval belief structures. Furthermore, considering the importance of attributes, the relative weights and interval belief structures are combined. Finally, according to integrated interval belief structures obtained by the analytical ER algorithm, a new ranking approach with the optimism degree and decision tendency degree is constructed to rank the interval expected utility and score utility of each alternative. To further show the effectiveness, superiorities, and stability of the proposed method, a case study on the EER evaluation is preformed and some comparisons and discussions are provided.
•Dynamic adjustment mechanism is constructed to adjust preference information.•New rule-based transformation is proposed to obtain interval belief structures.•Experts’ weights are calculated considering trust relationships among them.•Interval expected utilities and score utilities are introduced to rank alternatives.•An example of engineering emergency response evaluation is used to verify the method.
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Details
- Title
- Enhancing fuzzy evidential reasoning approach using dynamic adjustment mechanism and new rule-based transformation for engineering emergency response evaluation
- Creators
- Yan Tu - Wuhan University of TechnologyZhuang Ma - Wuhan University of TechnologyJun Liu - Wuhan University of TechnologyXiaoyang Zhou - Xi'an Jiaotong UniversityBenjamin Lev - Drexel University
- Publication Details
- Engineering applications of artificial intelligence, v 123
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:001007024800001
- Scopus ID
- 2-s2.0-85160419237
- Other Identifier
- 991020548567104721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Engineering, Electrical & Electronic
- Engineering, Multidisciplinary