A two-stage EDM method based on KU-CBR with the incomplete linguistic intuitionistic fuzzy preference relations

Incomplete linguistic q-rung orthopair fuzzy preference relations and their application to multi-criteria decision making

“…On August 8th, 2020, a typhoon landed in the coastal area of a city. The wind near the center was 16 level, the wind power of the center was 52 m/s and the pressure of the center was 930 HPA [57]. To help the department of emergency management to propose an emergency plan, the government gathered some experts in meteorology, typhoon, flooding, electricity, disaster relief and other fields to form a decision team.…”

“…Therefore, the decision team decided to use the historical data of Meranti. According to the experience of Xiamen City, the team offered four possible alternatives, A 1 : 800 evacuees, 1002 commanders and fighters, 170 fire engines, 100 fire boats, 3100 rescue equipment; A 2 : 650 evacuees, 900 commanders and fighters, 130 fire engines, 80 fire boats, 2980 rescue equipment; A 3 : 700 evacuees, 950 commanders and fighters, 150 fire engines, 120 fire boats, 3400 rescue equipment; A 4 : 750 evacuees, 970 commanders and fighters, 145 fire engines, 125 fire boats, 2690 rescue equipment [57]. To find the most suitable alternative, the department of emergency management decided to use Lq-ROFNs to evaluate these four alternatives based on a LTS S = {s 0 : extremely low, s 1 : very low, s 2 : low, s 3 : sightly low, s 4 : medium, s 5 : sightly high, s 6 : high, s 7 : very high, s 8 : extremely high}.…”