The invention discloses a ground-air cooperative fire barrier opening method based on digital twinborn and neural networks, and belongs to the technical field of
forest steppe fire prevention. Geographic information, weather and fire
monitoring data are collected and preprocessed, and a digital twinborn model is constructed to simulate meteorological elements. And then constructing an evaluation
index system to evaluate the
fire risk, and dividing risk grades. An isolation belt is planned by adopting a
genetic algorithm, and a parameter combination is explored through selection, crossing and
mutation operations. During air-ground collaborative operation, the unmanned aerial vehicle guides construction, the helicopter lifts materials, and the scheme is monitored and adjusted in real time. The
fire retardant effect is evaluated through
simulation and actual data, the efficiency and the
cost effectiveness are set up, and all links are optimized according to results. According to the method, the
fire risk is accurately assessed, the isolation belt is scientifically planned, the ground-air collaborative operation efficiency is improved,
dynamic monitoring and optimization are realized, the cost is reduced, and an effective means is provided for
forest steppe fire prevention and control.