Grassland fire is a common natural disaster

which causes significant impacts on the ecological environment of grasslands and human life.Therefore

rapid localization of fires in the early stage is particularly crucial.Aiming at the problem of early localization of grassland fires.a JAYA algorithm based on improved emotional intelligence is proposed.This algorithm endows unmanned aerial vehicle(UAV)with human-like psychological states and evaluates current status of each UAV through self-assessment.Additionally

social evaluation rules are introduced to classify UAVs

providing an effective basis for updating the positions of various types of UAVs

thus achieving efficient fire point localization.Comparative simulation experiments are conducted in the MATLAB environment

and the experimental results demonstrate that the emotional intelligence JAYA algorithm exhibits better performance in terms of success rate and convergence speed

offering a new method for the rapid localization of grassland fire points.