Research And Realization Of Qualitative And Quantitative Integration Modeling Method Based On COSIM

Traditional quantitative modeling can not be comprehensively applied for the complicatedsystem with high qualitative and quantitative requirements; while qualitative modeling canoptimistically describe the uncertainty and unpredictability of the qualitative behavior when managingthe same system. So, to get better result during the description on complicated application system, wecan combine qualitative modeling with quantitative modeling. Under the basis of the existingmodeling theory and technology, the modeling and simulation theory for Multidiscipline VirtualPrototype (COSIM) has been improved and new modeling and simulation methods were developed tomeet the requirements of multidisciplinary virtual prototyping complex products. This new theory canintegrate the unification and reuse of heterogeneous models in virtual prototype modeling, whichfurther enables the models of collaborative simulation to be distributed, hierarchical, andheterogeneous. The core theory, based on the hierarchical structure of the meta-meta model, providesconvenient interfaces for users to extend the qualitative model in order to build methods of qualitativeand quantitative integrated modeling for complex systems.In this paper, the integration of qualitative and quantitative modeling method was proposed basedon COSIM Theory. By extending the Meta model, Meta model, and model layers of hierarchicalmodel structure in COSIM, this method is designed to formally represent the hierarchical model of thestructure of the qualitative and quantitative integrated modeling. Considering the characteristics ofhierarchical description of the qualitative and quantitative model, the class diagram, package diagram,and static diagram of UML were extended by the UML mechanism. And the qualitative andquantitative modeling language based on COSIM was developed.The qualitative and quantitative integrated modeling should describe the qualitative model andquantitative model, in addition to consider the information exchange and the transform between themodels. The method predominantly in the cloud model was used, which achieved aquantitative/qualitative collaborative solution. Considering that the Gaussian Distribution Cloudmodel has some deficiencies on describing the exponential distribution such as life cycle, queuingtime and failure distribution, a new cloud model based on exponential distribution was proposed aswell. It contains normal cloud generator and backward cloud generator algorithm as its corefunctionality. Finally, the analysis of the effectiveness and feasibility of the new cloud model byexperiments was realized.The qualitative and quantitative hybrid modeling method proposed was applied to the missile defense system. The integrated modeling language was used to establish the static structure anddynamic behavior of the System. The method predominantly in the cloud model was established toachieve the conversion of information between the qualitative model and quantitative model. Thequalitative reasoning engine was used to develop missile defense decision. Through the analyses ofexperiments, the simulation system consisting of qualitative model and quantitative model has beenproved to represent the complex systems accurately and improve the success probabilitity of missiledefense.