Abstract
Over time, different metaheuristics have been used for optimization in different soft computing techniques, such as fuzzy systems and neural networks. In this work we focus on the optimization of fuzzy systems with the Crow Search Algorithm. The fuzzy systems are designed to provide the classification of the patient’s night blood pressure profile. For this goal, two fuzzy systems are designed, one with trapezoidal membership functions and the other with Gaussian membership functions, to study their corresponding performances. When observing the results of the aforementioned study, it was decided to carry out the optimization to improve the classification of the nocturnal blood pressure profile of the patients and thereby provide a more accurate diagnosis. After carrying out the experimentation and once the different optimized fuzzy systems have been tested, it was concluded that the fuzzy system with Gaussian membership functions provides a better classification in a sample of 30 patients.
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Acknowledgment
The authors would like to express their thanks to the Consejo Nacional de Ciencia y Tecnologia and Tecnologico Nacional de Mexico/Tijuana Institute of Technology for the facilities and resources granted for the development of this research.
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Miramontes, I., Melin, P., Prado-Arechiga, G. (2021). Fuzzy System for Classification of Nocturnal Blood Pressure Profile and Its Optimization with the Crow Search Algorithm. In: Balas, V., Jain, L., Balas, M., Shahbazova, S. (eds) Soft Computing Applications. SOFA 2018. Advances in Intelligent Systems and Computing, vol 1222. Springer, Cham. https://doi.org/10.1007/978-3-030-52190-5_2
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DOI: https://doi.org/10.1007/978-3-030-52190-5_2
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