Modularized assembly and overall parameter rapid generation method of equipment model

Abstract

A modular assembly and overall parameter rapid generation method of an equipment model is characterized in that on the basis of a class gene map representation recombination technology and a modularization theory, under the condition that a battlefield environment is complex and battlefield tasks are variable, equipment multi-source gene recombination data fitting is carried out through building block modular equipment modeling and construction of a maximum likelihood model; the modular assembly and overall parameter rapid generation method of the equipment model is established, the problems that a traditional modeling method is poor in reusability, modules are not universal, and the modeling method is difficult to adapt to rapid upgrading and updating of the equipment are solved, and the modeling method is more friendly and more flexible.

Description

technical field [0001] The invention relates to a method for modular assembly of an equipment model and rapid generation of overall parameters, and belongs to the field of aerospace equipment modeling intelligence technology. Background technique [0002] In the prior art, the joint XX scheme deduction evaluation technical framework based on the Monte Carlo method includes the deduction method and the effectiveness analysis evaluation method, but does not reflect the modular assembly of equipment; while the research on a certain evaluation method based on simulation deduction, according to the simulation deduction In the process of constructing the naval war game evaluation index system, factors are mainly extracted from different stages, and the modular assembly of equipment is not reflected; in addition, the integrated method of combat game simulation and effectiveness evaluation involved in the existing technology realizes the "combat plan design- The iterative evolution ...

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Problems solved by technology

[0003] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a method for modular assembly of equipment models and rapid generation of overall parameters. In the case of changing battlefield missions, by building block modular equipment modeling and building a maximum likelihood model to fit equipment multi-source gene recombination data, a modular assembly of equipment models and a rapid generation of overall parameters are established, which solves the problem of traditional The modeling method has poor reusability, the modules are not universal, and it is difficult to adapt to the problem of rapid equipment upgrades. A more friendly and flexible modeling method is provided

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