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Top-level modeling theory of multi-discipline virtual prototype 被引量:2
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作者 Tingyu Lin Xudong Chai Bohu Li 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2012年第3期425-437,共13页
Multi-disciplinary virtual prototypes of complex products are increasingly and widely used in modern advanced manufactur- ing. How to effectively address the problems of unified modeling, composition and reuse based o... Multi-disciplinary virtual prototypes of complex products are increasingly and widely used in modern advanced manufactur- ing. How to effectively address the problems of unified modeling, composition and reuse based on the multi-disciplinary heteroge- neous models has brought great challenges to the modeling and simulation (M&S) science and technology. This paper presents a top-level modeling theory based on the meta modeling framework (M2F) of the COllaborative SIMulation (COSlM) theory of virtual prototyping to solve the problems. Firstly the fundamental prin- ciples of the top-level modeling theory are decribed to expound the premise, assumptions, basic conventions and special require- ments in the description of complex heterogeneous systems. Next the formalized definitions for each factor in top level modeling are proposed and the hierarchical nature of them is illustrated. After demonstrating that they are self-closing, this paper divides the top- level modeling into two views, static structural graph and dynamic behavioral graph. Finally, a case study is discussed to demon- strate the feasibility of the theory. 展开更多
关键词 top-level modeling virtual prototype complex product multi-discipline modeling and simulation.
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Multi-source Fuzzy Information Fusion Method Based on Bayesian Optimal Classifier 被引量:8
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作者 SU Hong-Sheng 《自动化学报》 EI CSCD 北大核心 2008年第3期282-287,共6页
为了做常规贝叶斯的最佳的分类器,拥有处理模糊信息并且认识到推理过程的自动化的能力,一个新贝叶斯的最佳的分类器被建议,模糊信息嵌入。它不能仅仅有效地处理模糊信息,而且保留贝叶斯的最佳的分类器的学习性质。另外根据模糊集合... 为了做常规贝叶斯的最佳的分类器,拥有处理模糊信息并且认识到推理过程的自动化的能力,一个新贝叶斯的最佳的分类器被建议,模糊信息嵌入。它不能仅仅有效地处理模糊信息,而且保留贝叶斯的最佳的分类器的学习性质。另外根据模糊集合理论的进化,含糊的集合也是嵌入的进它产生含糊的贝叶斯的最佳的分类器。它能同时从积极、反向的方向模仿模糊信息的双重的特征。进一步,贝叶斯的最佳的分类器也是的集合对从积极、反向、不确定的方面就模糊信息的三方面的特征而言求婚了。最后,一个知识库的人工的神经网络(KBANN ) 被介绍认识到贝叶斯的最佳的分类器的自动推理。它不仅减少贝叶斯的最佳的分类器的计算费用而且改进它学习质量的分类。 展开更多
关键词 模糊信息 混合方法 贝叶斯最佳分类器 自动推理 神经网络
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