Research On The Optimization Of Weapon And Equipment Decision Making Based On Intelligent Algorithm And Fuzzy Reasoning

With the development of combat theory and advanced combat equipment centered on information technology,the command and decision-making mode of combat equipment and combat formation has changed significantly.However,the non-linearity of the development of the war situation,the grayness of information,the randomness of events,and the sudden change in the situation put forward higher requirements for the command and decision-making methods.In this context,"command and decision personnel + knowledge and experience" of the command and decision mode of weapons and equipment is no longer applicable to the operational needs of modern warfare.The command and decision-making of weapons and equipment are oriented to the complex and changeable battlefield environment,and it can make a reasonable and effective weapons and equipment application plan according to the actual situation in the complex environment,which has an important impact on the overall combat effectiveness and the outcome of the battle.Therefore,this paper takes the weapon and equipment command decision-making in the complex battlefield environment as the application background.Starting from the actual application requirements of weapon equipment command decision,the main problems in the process of weapon equipment command decision-making in-depth research,build the weapons and equipment command decision-making reasoning and optimization framework,for command decision personnel to provide practical and effective auxiliary decision support.This paper mainly focuses on five key technologies in the framework of weapon and equipment command decision reasoning and optimization: military target detection,military target threat assessment,single weapon and equipment utilization decision,weapon and equipment combination optimization,and weapon and equipment application plan optimization.In this way,the following research work is carried out in this paper:(1)Military target detection technology in a complex environment is the basis and key to improving battlefield situation generation and analysis ability.Aiming at the task of military target detection in complex environments,this paper proposes a target detection method in complex environments based on the YOLOv3-DAR algorithm.Based on the YOLOv3 network structure,this paper introduces a deformable convolution improved Res Net50-d residual network as a feature extraction network.This paper introduces a feature fusion module based on dual attention mechanism and a feature reconstruction module in the feature fusion stage.This paper proposes the YOLOv3-DAR network structure and applies it to battlefield image detection.The model has better detection results in deformation and occlusion target detection in complex environments.(2)Most existing target threat assessment methods rely on numerical information,and it is challenging to handle mixed feature information containing qualitative and quantitative information effectively.A target threat assessment method based on the M-ANFIS-PNN model is proposed to address this problem.Based on the adaptive network-based fuzzy inference system,the M-ANFIS-PNN model is proposed.By introducing the influence matrix of rule antecedent and the influence matrix of rule antecedent,the model has the ability to process mixed feature information,and the output layer is replaced by polynomial neural network to improve the prediction accuracy of the model.This paper uses the affinity propagation clustering algorithm to identify the model structure based on improved Gower distance.The improved model is applied to target threat assessment,which can effectively handle mixed feature information with high prediction accuracy and can effectively accomplish the quantitative assessment of the target threat level.(3)For the single weapon and equipment utilization decision problem,a single weapon and equipment utilization decision method based on the HHO-ICA algorithm and fuzzy logic is proposed.Firstly,the HHO-ICA hybrid optimization algorithm is proposed by combining the characteristics of the harris hawk optimization algorithm and the imperialistic competition algorithm.Secondly,a command decision rule generation method is proposed based on the HHO-ICA algorithm to improve the generation efficiency and accuracy of fuzzy command decision rules.Thirdly,based on the command decision rules,a Mamdani fuzzy reasoning system is constructed,which takes the target feature information as input and the weapon equipment type as output.According to the generated command decision-making rules,the final decision-making result of the single weapon and equipment utilization is obtained through fuzzy reasoning.(4)Aiming at the combination optimization problem of weapons and equipment,a weapon and equipment combination optimization method based on D-NSGA-GKM algorithm is proposed.Considering the confrontation characteristics of both sides and the uncertainty of the performance of weapons and equipment,this paper takes the strike decision of the firepower execution unit as the optimization variable.Specifically,this paper establishes a weapon-target allocation model that takes the minimum remaining value of the enemy combat unit on the battlefield,the least consumption of combat resources,and the least loss of battlefield value of the combat unit as the multiple optimization objectives.And the performance of weapon equipment is described by introducing uncertainty and uncertainty adjusting factor.Based on non-dominated sorting genetic algorithm Ⅲ,this paper introduces a non-dominated sorting algorithm based on the dominance degree matrix.This paper introduces a reference point generation method based on a genetic K-means clustering algorithm.This paper introduces a penalty-based boundary intersection distance instead of vertical distance in the environmental selection stage.In this way,this paper proposes the D-NSGA-GKM algorithm.At the same time,the improved optimization algorithm is used to solve the weapon equipment combination optimization model,which effectively improves the efficiency,diversity,and convergence of mainstream multi-objective optimization algorithms when solving this model.(5)Aiming at the optimization and decision-making of weapon and equipment application scheme,a weapon and equipment application scheme optimization and decision-making method based on intuitionistic fuzzy VIKOR group decision-making model is proposed.The evaluation index system for weapon and equipment utilization program preference is constructed by analyzing the key points,risk points,and evaluation focus of the weapon and equipment utilization program preference.In order to avoid the loss of information,the decision information and index evaluation information of command decision-makers are converted into intuitionistic fuzzy numbers that are more in line with the actual decision-making.For command decision-makers,it weights unknown problems.According to the similarity and hesitation of decision-making information,the decision-making weight of command decision-makers is determined;For the problem that the weight of the evaluation index is unknown,this paper proposes a comprehensive weighting method based on the intuitionistic fuzzy optimal worst method and the entropy weight method to obtain the comprehensive weight of each evaluation index.Finally,the VIKOR method is extended to the intuitionistic fuzzy environment.The candidate schemes are prioritized by the extended VIKOR method.