Multiattribute decision making based on q-rung orthopair fuzzy Yager prioritized weighted arithmetic aggregation operator of q-rung orthopair fuzzy numbers

Kumar, Kamal; Chen, Shyi-Ming

doi:10.1016/j.ins.2023.119984

Cited by 3 publications

(1 citation statement)

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“…The weight of each decision attribute is obtained through subjective expert experience or objective data methods. Using operators such as the arithmetic mean, the multi-attribute information is aggregated, and the multiple alternatives are ranked [40].…”

Section: Remarkmentioning

confidence: 99%

A New Multi-Target Three-Way Threat Assessment Method with Heterogeneous Information and Attribute Relevance

Gao,

Lyu

2024

Mathematics

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Target threat assessment provides support for combat decision making. The multi-target threat assessment method based on a three-way decision can obtain threat classification while receiving threat ranking, thus avoiding the limitation of traditional two-way decisions. However, the heterogeneous situation information, attribute relevance, and adaptive information processing needs in complex battlefield environment bring challenges to existing methods. Therefore, this paper proposes a new multi-target three-way threat assessment method with heterogeneous information and attribute relevance. Firstly, dynamic assessment information is represented by heterogeneous information, and attribute weights are calculated by heterogeneous Criteria Importance Through Intercriteria Correlation (CRITIC). Then, the conditional probability is calculated by the heterogeneous weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the adaptive risk avoidance coefficients are constructed by calculating the uncertainty of the assessment value, and then the relative loss function matrices are constructed. Finally, the comprehensive loss function matrices are obtained by the weighted Heronian mean (HM) operator, and the comprehensive thresholds are calculated to obtain the three-way rules. The case study shows that compared with the existing methods, the proposed method can effectively handle the heterogeneous information and attribute relevance, and obtain the risk avoidance coefficients without presetting or field subjective settings, which is more suitable for the complex mission environment.

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Section: Remarkmentioning

confidence: 99%