Abstract:

Aiming at the problem of less combat capacity evaluation methods of city system, the index system is brought forward and the subordinate function of each index is given. An assessment model based on BP neural network whose thresholds and connection weights are optimized by the simulated annealing and genetic algorithm (SAGA) is proposed to solve the problems. And the problems of the classical genetic algorithm and BP neural network trapping into the local minimum point, low convergence speed and with bad anti-jamming ability are solved. Using the characteristic dominances of self-adaptive, self-learning, efficient fault tolerant and wide mapping of BP neural networks, the model can weaken human factors of the index to improve the accuracy, objectivity and authority of assessment results. According to the simulation, the feasibility and validity of city system’s campaign capability assessment by this method are verified.