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Abstract

Parkinson’s disease is a neuro-degenerative movement disorder that causes voice and speech disorders. Therefore, the disease can be diagnosed as a dysfunctional disease. In this study, Computational Intelligence Methods, a new method for classifying Parkinson’s disease, have been used. This method has been tested with two data sets and compared with classical methods. According to the obtained results, this method yielded better results than the classical methods.

Keywords

Parkinson’s disease Z-number Artificial neural network Computational intelligence methods Neuro-Fuzzy IS Type-2 FIS Z-FIS 

References

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Research Laboratory of Intelligent Control and Decision Making Systems in Industry and EconomicsAzerbaijan State Oil and Industry UniversityBakuAzerbaijan

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