Intelligent control method of warfare simulation experiment based on neural network
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To solve the currently existing problems of time consuming and low flexibility in warfare simulation experiment, an intelligent control method based on neural network is advanced, imitating human's thinking process of decision. Firstly, the main general idea and framework of the intelligent control are introduced. Secondly, the structure and training algorithm of three layered feedforward neural network, and the global exploration and regional optimization method of warfare simulation experiment are described. Lastly, a simulation experiment example of large scale formation optimization in air battle demonstrates the procedure of the method, which shows that the sufficiently trained neural network could replace the costly global exploration experiments, and the solution efficiency is improved greatly.
[1] Chen Rui-jun. A Study on Terminal Correction of Airborne Dispenser Based on BP Neural Network , 2012 .
[2] Zhang Yao-zhong. Formation-optimizing algorithm for large-scale air combat , 2010 .
[3] Michael Negnevitsky,et al. Artificial Intelligence: A Guide to Intelligent Systems , 2001 .
[4] Wang Wei-ping. Adaptive Control Method of Experiments' Number in System-of-Systems Combat Simulation , 2011 .