Hybrid of particle swarm optimization algorithm and fuzzy system for diabetes diagnosis
- سال انتشار: 1403
- محل انتشار: مجله آنالیز غیر خطی و کاربردها، دوره: 15، شماره: 2
- کد COI اختصاصی: JR_IJNAA-15-2_004
- زبان مقاله: انگلیسی
- تعداد مشاهده: 69
نویسندگان
Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran
Department of Computer Engineering, Khoy Branch, Islamic Azad University, Khoy, Iran
Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran
Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, Iran
چکیده
Diabetes is a dangerous disease in which the body is incapable of controlling blood sugar due to inadequate insulin hormone levels. This chronic disease increases blood sugar in patients. Therefore, if it is not controlled, it will cause many complications. A considerable number of people in the world suffer from this disease owing to its damage and lack of its initial diagnosis. The patient visits the doctor frequently to diagnose his/her illness and conducts various tests that are boring and costly. Increasing machine learning approaches through heuristics, and novel methods can somewhat decrease the problems. The current study aims to propose a model that can predict diabetes in patients with high accuracy. The paper introduces a new method based on the assortment of metaheuristic algorithms of a particle swarm and fuzzy inference system. The proposed method utilizes fuzzy systems to binary the particle swarm algorithm. The achieved model is applied to the diabetes dataset and then evaluated using a neural network classifier. The results indicate an increase in classification accuracy to ۹۵.۴۷% compared to other existing methods.کلیدواژه ها
Diabetes, PSO Algorithm, Neural Networks, Fuzzy systems, Meta-heuristic algorithmsاطلاعات بیشتر در مورد COI
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