Fuzzy Brain Emotional Controller for Heart Disease Diagnosis

• Autorzy: Pham Duc Hung , Nguyen Viet-Ngu , Le Thi Minh-Tam

Identyfikatory

DOI

10.15439/2022R50

• Konferencja: Seventh International Conference on Research in Intelligent and Computing in Engineering
• Języki publikacji: EN

Abstrakty

EN

This article provides a new way for classifying heart disease. A classifier using a controller for brain emotional learning and a fuzzy system is presented. The controller's parameter updating laws are built using the gradient descent method. The method's convergence and stability are ensured by the Lyapunov function. Using the heart disease dataset from the University of California, Irvine (UCI), the performance of the system is examined. In addition, a comparison with different classifiers is provided. The outcomes of our experiments illustrate the efficacy of our strategy.

Słowa kluczowe

EN

heart disease prediction; fuzzy system; brain emotional learning controller

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2022
• Tom: Vol. 33
• Strony: 33--36
• Opis fizyczny: Bibliogr. 11 poz., rys., tab., wykr.

Twórcy

autor

Pham Duc Hung

• Faculty Electrical and Electronic Engineering, Hung Yen University of Technology and Education, Vietnam

autor

Nguyen Viet-Ngu

• Faculty Electrical and Electronic Engineering, Hung Yen University of Technology and Education, Vietnam

autor

Le Thi Minh-Tam

• Faculty Electrical and Electronic Engineering, Hung Yen University of Technology and Education, Vietnam

Bibliografia

• [1] C. M. Lin, D. H. Pham, and T. T. Huynh, "Encryption and Decryption of Audio Signal and Image Secure Communications Using Chaotic System Synchronization Control by TSK Fuzzy Brain Emotional Learning Controllers," IEEE Transactions on Cybernetics, pp. 1-15, 2021.
• [2] C. Lucas, D. Shahmirzadi, and N. Sheikholeslami, "Introducing BELBIC: brain emotional learning based intelligent controller," Intelligent Automation Soft Computing, vol. 10, no. 1, pp. 11-21, 2004.
• [3] H. S. A. Milad and J. J. I. A. Gu, "Expanded neo-fuzzy adaptive decayed brain emotional learning network for online time series predication," vol. 9, pp. 65758-65770, 2021.
• [4] C.-M. Lin, D.-H. Pham, and T.-T. Huynh, "Synchronization of Chaotic System Using a Brain-Imitated Neural Network Controller and Its Applications for Secure Communications," IEEE Access, vol. 9, pp. 75923-75944, 2021.
• [5] T.-T. Huynh, C.-M. Lin, T.-L. Le, V.-P. Vu, and F. Chao, "Self-organizing double function-link fuzzy brain emotional control system design for uncertain nonlinear systems," IEEE Transactions on Systems, Man, Cybernetics: Systems, 2020.
• [6] T.-L. Le, T.-T. Huynh, L.-Y. Lin, C.-M. Lin, and F. Chao, "A K-means Interval Type-2 Fuzzy Neural Network for Medical Diagnosis," International Journal of Fuzzy Systems, vol. 21, no. 7, pp. 2258-2269, 2019.
• [7] A. A. Bakhsh, "High-performance in classification of heart disease using advanced supercomputing technique with cluster-based enhanced deep genetic algorithm," The Journal of Supercomputing, pp. 1-22, 2021.
• [8] V. B. Charles, D. Surendran, SureshKumar, and Control, "Heart disease data based privacy preservation using enhanced ElGamal and ResNet classifier," Biomedical Signal Processing, vol. 71, p. 103185, 2022.
• [9] S. Qiao et al., "RLDS: An explainable residual learning diagnosis system for fetal congenital heart disease," Future Generation Computer Systems, vol. 128, pp. 205-218, 2022/03/01/ 2022.
• [10] A. K. Dwivedi, "Performance evaluation of different machine learning techniques for prediction of heart disease," Neural Computing and Applications, vol. 29, no. 10, pp. 685-693, 2018.
• [11] V. B. Charles, D. Surendran, A. J. B. S. P. SureshKumar, and Control, "Heart disease data based privacy preservation using enhanced ElGamal and ResNet classifier," vol. 71, p. 103185, 2022.

Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).