Entropy-Weighted TOPSIS-Based Bird Strike Risk Assessment for an Airport

Abstract

Abstract To identify the factors with higher bird strike risk at a certain airport, and to provide a theoretical basis for the airport to develop targeted and dynamic bird strike prevention strategies, this study has established a bird strike risk assessment index system for the airport based on the “3M1E” theory and relevant content of the “Management Measures for the Prevention and Control of Bird Strikes and Animal Intrusions at Transport Airports”. Then, under the premise of reasonably selecting the parameters of generalized intuitionistic fuzzy entropy, the entropy method is used to simultaneously determine the expert weights and indicator weights. Finally, a weighted TOPSIS model was utilized to assess and rank the high-risk factors contributing to bird strike incidents. Then, taking the bird strike event occurrence at a certain airport as an example for analysis, the second-level indicators are ranked. The results show that the top three indicators are Bird Prevention Funding ( $$D_3$$ D 3 ), Habitat Distribution ( $$C_1$$ C 1 ), and Dispersal Activities ( $$D_5$$ D 5 ). The assessment results provide the necessary basic data for the bird strike prevention work of the airport.

Keywords

• Binary semantics
• Entropy weight method
• TOPSIS model
• Bird strike