The Methodology Research On Fuzzy Representation And Decision Of Joint Operational Command And Control Process

In modern warfare, coordinating multi-services and arms to perform joint military tasks is one of the crucial problems military command and control field researches investigate at present. The procedure of command and control commanders impact is called the command and control process(C2P). C2 P is a key portion of the implementation of military missions, thus the research on C2 P study has been the core area of operational simulation theoretical research all the while. Traditional operational simulation separates the subject from the object, simplifying approximation obtained by means of the “exact”results of the analysis, which is difficult to solve complex C2 P problem under the joint operations conditions. To describe and solve many uncertainties the C2 P exists, fuzzy set theory provided a scientific theory and method. The thesis puts the theory and its extension into practice of joint operations command and control process(JOC2P) areas, to reason JOC2 P and make decision about JOC2 P by means of incomplete, imprecise or uncertain information, efficiently processing the uncertainty problems caused by ambiguity of battlefield information, which provides new ideas and methods for JOC2 P modeling.The aim of the thesis is: after drawing lessons from current research on JOC2 P, apply fuzzy sets and fuzzy reasoning methods to represent the uncertainties involved with JOC2 P, and to do fuzzy command and control, decision making under the complicated battlefield environment, further to provide scientific theories and methods for intellectualized design of command and control system. Key technologies include fuzzy ontology, fuzzy knowledge base, timed influenced net improved by fuzzy Bayesian decision and fuzzy multi-criteria group decision-making. From the aspects of representation and decision-making of fuzzy processing approaches of the JOC2 P, the work and innovation mainly comprises the following parts:(1) The solving framework for JOC2 P fuzzy representation and decision-making methods is proposed.First, the concept connotation, characteristics and complexity of the JOC2 P are investigated deeply, respectively. Then a discussion for solving fuzzy demand about JOC2 P representation and decision-making method is followed by. Thus the solving framework of JOC2 P fuzzy representation and decision-making methods is raised. In the specific design process, the framework will play an important role in guiding JOC2 P fuzzy representation and decision-making methods solutions.In aspects of JOC2 P fuzzy representation:(2) JOC2 P semantic representation based on fuzzy ontology is proposed, to solve fuzzy information modeling representation problem in the field of JOC2 P. In the first place, a novel fuzzy description logic L-SHOIN is designed, including its syntax and semantics, and on the basis of that, formal logic OWL is expanded to FOWL. Compared to current mainstream fuzzy ontology language, FOWL supports both quantitative reasoning and qualitative non-deterministic reasoning, which is more suitable to express fuzzy information of the military field. Next, based on JC3 IEDM data model, design JOC2 P fuzzy ontology with FOWL, solving fuzzy information modeling representation problem in the field of JOC2 P. Finally, JOC2 P fuzzy ontology semantic validation methods are studied, including fuzzy description logic and f-SWRL test method for solving JOC2 P fuzzy ontology concepts conflict, knowledge redundancy and data inconsistencies and other issues.(3) In view of lacking capacity of intelligent decision-making in the JOC2 P system,JOC2 P fuzzy knowledge base construction method is proposed. Basic Object Model(BOM) is a widely used class of simulation models in current command and control system, through appending semantic on BOM by fuzzy JOC2 P ontology, the development framework of joint task space model based on BOM is designed. Joint task space model extends intelligent command and control functions by reuse of existing plug-in. Therefore, the composition and working principle of the fuzzy knowledge base are investigated thoroughly, and construction method of the fuzzy knowledge base is given. Finally, a threat assessment example for fuzzy inference analysis application is presented.In aspects of JOC2 P fuzzy decision-making:(4) Fuzzy JOC2 P decision optimization method based on effects-based operations is proposed, to resolve the quantitative analysis and optimization in real battlefield situation. Timed influenced network is an effective tool from the qualitative description into quantitative analysis. But its decision nodes are basically manually specified a priori probability, without considering the impact of the real battlefield situation, consequently import Bayesian decision method: dealing known situational information by fuzzy processing, with the latest information to improve the input fuzzy state of nature prior distribution assumption, then calculate the posterior fuzzy risk, in order to update the prior probability of the decision nodes. On this basis, to achieve a improved fuzzy timed influenced. An anti-air warfare planning scenario is demonstrated to verify the effectiveness of the improved method and robustness.(5) JOC2 P fuzzy multi-criteria group decision making method is proposed, to implement JOC2 P fuzzy multiple criteria decision making by means of group decision making in the cognitive domain. Due to combat ambiguity, uncertainty and different preferences among decision-makers and other subjective factors, preference information that must be addressed with a variety of multi-group command staff in group decision problem. Because of interaction between network elements of COA and conflict relationship existing between the multi-criteria, triangular fuzzy number and intuitionistic fuzzy theory are introduced to express of uncertainty. A hybrid combining FANP and VIKOR fuzzy multi-criteria group decision making method is presented, and an operational plan for the preferred authentication scenario is given. Experimental results show that the algorithm has high computing efficiency and good scalability, which can assist commanders to decision effectively.To sum up, the thesis promotes fuzzy theory in the field of operational simulation applications, and have a greater improvement to JOC2 P modeling.