Fuzzy pattern recognition to characterize evolutionary complex systems. Application to the french telephone network

机译：模糊模式识别可表征演化复杂系统。应用于法国电话网

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Diagnosis methods for the functional state of a static system are well-known. But the diagnosis of a dynamic process is more difficult to handle because the system state evolves in time. This paper builds membership functions along the paths according to which the system state evolves from one known functional state to another. These multi-dimensional membership functions are used to characterize and to follow the complex system state evolution.

机译：静态系统功能状态的诊断方法是众所周知的。但是，动态过程的诊断更难以处理，因为系统状态及时发展。本文构建了根据该路径的隶属函数，系统状态从一个已知的功能状态从一个已知的功能状态发展到另一个。这些多维隶属函数函数用于表征和遵循复杂的系统状态演进。

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《Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on》|1996年|P.780-785|共6页
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Boutleux; E.; Dubuisson; B.;
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中图分类无线电电子学、电信技术;
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入库时间 2022-08-26 14:02:09

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4. Fuzzy pattern recognition to characterize evolutionary complex systems. Application to the french telephone network [C] . Boutleux E., Dubuisson B., Institute of Electric and Electronic Engineer IEEE International Conference on Fuzzy Systems . 1996

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Fuzzy pattern recognition to characterize evolutionary complex systems. Application to the french telephone network

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