TIFNCWBHG-MAGDM for System Evaluation Based on TIFNs for the Safety Input of Coal Enterprise | Zendy

Chao Zhang | Zendy; Qingjie Qi | Zendy

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TIFNCWBHG-MAGDM for System Evaluation Based on TIFNs for the Safety Input of Coal Enterprise

Author(s) -

Chao Zhang,

Qingjie Qi

Publication year - 2021

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2021/6644806

Subject(s) - computer science , operator (biology) , fuzzy logic , resource (disambiguation) , function (biology) , stability (learning theory) , coal , position (finance) , weight function , computation , operations research , business , mathematics , engineering , artificial intelligence , algorithm , computer network , biochemistry , chemistry , statistics , finance , repressor , evolutionary biology , machine learning , biology , transcription factor , gene , waste management

Determining the safety input structure is essential to achieve efficient resource utilization and the safe production of coal enterprises. In this paper, the system evaluation method, TIFNCWBHG-MAGDM, is proposed to evaluate the safety input of coal enterprises. It is based on the integration of the intuitionistic triangular fuzzy numbers (TIFNs), TIFNs Compound Weight Bonferroni Hybrid Geometric (TIFNCWBHG) operator, and multiattribute group decision-making (MAGDM) theory. First, the judgment matrix of TIFNs is constructed from multiperspective: multitime points, multiattributes, and multiexperts. The TIFNCWBHG operator integrates the TIFNs score function, stability weight, and position weight. Then, the priorities for safety inputs are determined. The experimental results showed that safety inputs in industrial hygiene, propaganda, and education significantly impact the overall level of safety inputs. Also, it was proved that the efficiency of the safety input is important. The proposed TIFNCWBHG-MAGDM effectively coordinated the stability weight, position weight, and computation of TIFNs score function, taking the advantages of TIFNs. Accordingly, it was proved that it could optimize the safety input structure.

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