The Research On Photoelectric Defense System Combat Effectiveness Evaluation Methods

The war of modern high technology conditions puts forward higher request tophotoelectric defense system from design to combat use. The discretion of the combateffectiveness evaluation is an important index of weapon system quality. Thereforethis dissertation makes further research on combat effectiveness evaluation methodsof photoelectric defense system in design and actual battlefield use stage, respectively.At present, the combat effectiveness evaluation is more for combat aircraft, the UAVand anti-ship missile, etc. This dissertation makes research on combat effectivenessevaluation of the photoelectric defense system under the condition of less references,which has practical significance.This dissertation summarizes the present situation of the development of combateffectiveness evaluation methods at home and abroad, introduces the basic theory ofcombat effectiveness evaluation, basic process, and the basic principles of setting upcombat effectiveness evaluation index system. Then, this dissertation establishes thecombat effectiveness evaluation index system for the purpose of evaluating thedesign scheme of the largest combat efficiency and the combat effectivenessevaluation index system for the purpose of evaluating the fighting effect ofphotoelectric defense system.In system design, we hope to get the photoelectric defense system of the biggest combat effectiveness. At this time, the combat effectiveness evaluation problem is amultiple attribute decision making problem. This dissertation puts forward the greysituation decision-making principle and grey model associated assessment principleexpanded by the real number to the interval number; introduces the combination lawof subjective and objective weighting of experts consultation method andinformation entropy, perfects the two model, makes them more appropriate for thecombat effectiveness evaluation of photoelectric defense system. Examples provethe validity of the two models.When used in combat, the influence factors of the combat effectiveness arecomplex and show a nonlinear relationship. This dissertation will apply to BP neuralnetwork and support vector machine (SVM) method to combat effectivenessevaluation, propose the thought of make the photoelectric defense system combateffectiveness value to different "classification", that is to map the data to the "veryhigh","high","normal""low" and "very low" five categories through the neuralnetwork, further evaluate the photoelectric defense system combat effectiveness. Theexample verifies the validity of the methods above, respectively, which overcome theweakness of the expert decision-making system not easy to modify and the poorquality of the adaptive ability. This dissertation puts forward to optimize the BPneural network weights and threshold by use of the bat algorithm, gets the bestweights and threshold, constructs BP neural network, and solve the problem of BPneural network structure which is difficult to determine.For the problem of the information acquired with incomplete and uncertaintiesunder the complex battlefield environment, this dissertation adopts the combinationmethod of the rough sets and support vector machine (SVM) to evaluate the combateffectiveness of the photoelectric defense system. Using rough set theory to attributereduction, this dissertation inputs the characteristics after attribute reduction to thesupport vector machine. The classification results are better than the classificationresults of no attribute reduction. The calculation example shows that the method iseffective and practical.