Predicting Parkinson's disease based on transformed speech signal by DWT with two methods for features selection: GA-AdaBoost and BPSO-Reference-Cited by-同舟云学术

Predicting Parkinson's disease based on transformed speech signal by DWT with two methods for features selection: GA-AdaBoost and BPSO

Published:2022-08 Issue: Volume: Page:
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Container-title:2022 7th International Conference on Mathematics and Computers in Sciences and Industry (MCSI)
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Author:

Soumaya Zayrit¹,Benayad Nsiri²,Taoufiq Belhoussine Drissi¹,Abdelkrim Ammoumou¹

Affiliation:

1. University Hassan II - Casablanca,Laboratory Industrial Engineering, Information Processing and Logistics (GITIL). Faculty of Science Ain Chok.,Casablanca,Morocco

2. Research Center STIS, M2CS, National School of Arts and Crafts of Rabat (ENSAM), Mohammed V University in Rabat, Morocco,Casablanca,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10066055/10066067/10066063.pdf?arnumber=10066063

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2. Ηyper-sinh-Convolutional Neural Network for Early Detection of Parkinson’s Disease from Spiral Drawings

3. A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

4. Using Machine Learning to Predict Heart Disease

5. Statistical formant descriptors with linear predictive coefficients for accent classification

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