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基于神经网络的飞机极限数据专家系统 被引量:1

Expert System for Utmost Flight Data of Aircraft Based on Neural Networks
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摘要 利用神经网络专家系统的方法对飞机飞行参数的极限允许值进行计算 ,可以使推理过程变得简洁、清晰 ,避免了常规方法在软件实现上的诸多缺点。同时 ,本文采用一种模糊规则方法对神经网络专家系统的推理行为进行描述 ,使得神经网络专家系统能够回答有关 why和 how的询问。以最大允许马赫数的计算为例 ,本文设计了用于该参数推理的神经网络专家系统 。 The process of reasoning utmost flight data becomes conc ise and clear because a method for expert system based on neural networks is uti lized in the process. If utmost flight data are figured out by general methods, th ere will be many shortages in the software for determining the utmost flight dat a. Ho wever, those shortages belonging to general methods will not be met in the above -mentioned method. Application of a fuzzy rule-based method used to d escribe reasoning action of neural networks make it possible that expert system can answer those inquires about why and how. This paper designs an expert syste m for determining utmost Mach number based on neural networks and gives a simple example. Finally, some are written for expounding the conclusions of studying t he expert system of the utmost flight data of the aircraft based on neural netwo rks.
出处 《南京航空航天大学学报》 EI CAS CSCD 北大核心 2004年第1期87-90,共4页 Journal of Nanjing University of Aeronautics & Astronautics
基金 国家自然科学基金 ( 50 1350 30 )资助项目
关键词 神经网络 飞机 飞行参数 极限允许值 专家系统 模糊规则 aircraft utmost flight data neural networks e xpert system fuzzy rules interpretation mechanism
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  • 1.[M].,..
  • 2Maire F. Rule-extraction by backpropagation of polyhedra[J]. Neural Networks, 1999,12:717~725.
  • 3Taha I, Ghosh J. Symbolic interpretation of artificial neural networks[J]. IEEE Trans Knowledge Data Eng,1999,11:448~463.
  • 4Tsukimoto H. Extracting rules from trained neural networks[J]. IEEE Trans. Neural Networks, 2000,11:377~389.
  • 5Setiono R. Extracting M-of-N rules from trained neural networks[J]. IEEE Trans Neural Networks, 2000,11:512~519.
  • 6Castro L, Mantas J, Benitez M.Interpretation of artificial neural networks by means of fuzzy rules[J]. IEEE Transactions on Neural Networks, 2002,13(1):101~116.

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