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A complete pattern recognition approach under Atanassov's intuitionistic fuzzy sets

机译:基于Atanassov直觉模糊集的完整模式识别方法

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摘要

This research is aimed at developing a method for solving pattern recognition problems under the Atanassov's intuitionistic fuzzy sets based on similarity measures. First we proposed two similarity measures and then developed a method based on our similarity measures. We also proved that our method is able to solve the pattern recognition problems. Finally, a fault diagnosis example of the turbine vibration has been examined by our method. The example demonstrates that the proposed method cannot only diagnose the main faults of the turbine generator but also it can detect useful information for future trends and multi-fault analysis. In addition, for the convenience of computing and ranking processes, a computer interface decision support system is also developed to help decision maker make diagnoses more efficiently.
机译:这项研究的目的是开发一种基于相似性度量的解决阿塔纳索夫直觉模糊集下的模式识别问题的方法。首先,我们提出了两个相似性度量,然后根据相似性度量开发了一种方法。我们还证明了我们的方法能够解决模式识别问题。最后,通过我们的方法检查了涡轮振动的故障诊断实例。算例表明,所提出的方法不仅可以诊断涡轮发电机的主要故障,而且可以检测出有用的信息,以备将来趋势和多故障分析之用。另外,为方便计算和排序过程,还开发了计算机接口决策支持系统,以帮助决策者更有效地进行诊断。

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