Research on Forest Fire Helicopter Demand Forecast based on Index Fuzzy Segmentation and TOPSIS

In recent years, forest fires have occurred frequently, and relying on helicopter to extinguish fires is an important means of forest fire prevention. The rapid determination of helicopter demand after a forest fire can not only save time for dispatching helicopters, but also improve fire rescue efficiency. In order to effectively predict the number of fire helicopters needed in forest fires, a demand forecasting model based on index fuzzy segmentation (IFS) and TOPSIS is proposed. In view of the fuzzy nature of reliability level segmentation has usually been overlooked in the past research, the IFS model was constructed based on the theory of fuzzy membership function. With the proposed IFS model, the problem of forest fire helicopter demand prediction was further adapted into the treatment of a prototypical multi-attribute decision making issue. Building on that, the TOPSIS method was further adopted to legitimately recognize the number of forest fire helicopter demand prediction. Case analysis and comparative analysis show that the demand forecasting model based on index fuzzy segmentation and TOPSIS method has strong feasibility and rationality, which provides a scientific method for predicting the number of forest fire helicopter demand resource.