Achieving method of competitive group action decision support system

Abstract

An achieving method of a competitive group action decision support system integrates artificial intelligence, computer simulation, data mining, visualized modeling and a dynamic virtual battlefield space establishing technology, and establishes an action plan simulation deduction tool which can be understood by a user and does not need underlying programming through a standardized action environment element model library, a confrontation object model library and an action rule library. By means of the achieving method, establishment of a standardized action model integration deduction system is achieved, unification of ordinary-time accumulation, individualized application, mathematical model, intuitive graphical and action process and possible ending is achieved, the scientization and accuracy of action scheme deduction are improved, and support on individualized scientific decision making of the user is achieved.

Description

technical field [0001] The invention belongs to the technical field of computers and software, in particular to computer decision support for competitive group confrontation actions, and is a method for realizing a competitive group action decision support system. Background technique [0002] The effects of competitive group confrontation actions, such as military combat operations and group ball games, rely on the accurate prediction of the future confrontation situation before the action and the scientific formulation of one's own action plan based on the prediction. Although in the long-term practice, people have summarized some laws about the decision-making of countermeasures, explored many effective decision-making methods, and built a decision-making support system based on modern information technology, but generally speaking, the following problems have not been effectively solved. [0003] One is that it has not got rid of the stereotype of relying mainly on the m...

AI Technical Summary

Problems solved by technology

[0003] One is that it has not got rid of the stereotype of relying mainly on the mental thinking of decision makers, and it is difficult to solve the problem that the individual thinking results of the human brain are difficult to be effectively shared, integrated, systematic, and visualized, and the individual thinking cannot be effectively and systematically integrated into the decision-making basis of the group

[0004] The second is that it has not gotten rid of the stereotype of predicting and making decisions mainly based on historical experience, it is difficult to solve the problem of accurately grasping and effectively displaying the trend of future confrontation, and it is impossible to allow decision makers to make effective decisions based on "future experience"

[0005] The third is that it has not gotten rid of the stereotype of extensive forecasting and decision-making, cannot allow a large amount of useful daily training data and action process data to be effectively used in forecasting and decision-making, and cannot achieve quantitative and accurate forecasting and decision-making.

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