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

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.