An ANN verifying approach to equipment campaign model

To any simulating system, only its credibility being confirmed can it take on practical worthiness. When economical and feasibility were concerned, the verifying and validating tactic was put forward to equipment compaign simulation prototype system. Then damage parameter experiment was done under typical condition. Neural network was used to verify error between experiment data and experiential value of damage parameters, the trained neural network was embedded into model. At last system simulating result was validated through real war data and experiment data of real equipment. So a fresh approach on complexity theory was explored to equipment simulating model or analogous problem.