تشخیص بیماری دیابت با استفاده از الگوریتم ترکیبی گرده افشانی گل و الگوریتم گروهی نزدیکترین همسایه

نوع مقاله: مقاله پژوهشی

نویسندگان

1 علوم کامپیوتر دانشگده فنی و علوم پایه دانشگاه کوثر بجنورد

2 کامپیوتر، دانشکده علوم پایه و مهندسی دانشگاه کوثر بجنورد

چکیده

 دیابت بیماری است که علاوه بر پیشگیری، نیاز به مراقبت­های فراوانی از جمله میزان نوسانات سطح قند خون دارد. تشخیص به موقع بیماری نقش بسزایی در درمان ایفا می­کند و به طور چشمگیری صدمات ناشی از بیماری را کاهش می­دهد. بنابراین، نیاز به تشخیص بیماری دیابت احساس می­شود. به دلیل آنکه الگوریتم­های ترکیبی توانایی بالایی در پیش­بینی و تشخیص انواع بیماری­ها دارند، در این مقاله رویکردی هوشمندانه با الگوریتم ترکیبی گرده‌افشانی گل و الگوریتم گروهی نزدیک‌ترین همسایه برای تشخیص این بیماری ارائه شده است. صحت روش پیشنهادی با مجموعه داده PID با 768 نمونه و 8 ویژگی ارزیابی شده و صحت 97.78 درصد به دست آمده است. نتایج نشان می­دهد که صحت این روش به میزان قابل توجهی نسبت به مطالعات قبلی بهبود یافته است که برتری روش پیشنهادی را تأیید می­کند.

کلیدواژه‌ها


عنوان مقاله [English]

The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers

نویسندگان [English]

  • Zeinab Hassani 1
  • Najmeh Samadiani 2
1 computer science Kosar university of Bojnord
2 computer Kosar university of Bojnord
چکیده [English]

Diabetes is a disease which, as well as prevention, requires a high level of care, such as monitoring the blood sugar changes. The timely diagnosis of disease plays an important role in its treatment and decreases the damage caused by the disease. Therefore, it is essential to diagnose diabetes. Since hybrid algorithms have a high ability to predict and diagnose various diseases, this article presents an intelligent approach to the diagnosis of this disease, using a hybrid algorithm of flower pollination and K-nearest neighbor ensemble. The accuracy of the proposed method is measured to be 97.78, by using Pima Indians Diabetes (PID) dataset, consisting of 768 samples and 8 features. The results show that the accuracy of this approach has significantly increased compared with the previous studies, and confirms the superiority of the proposed method.

کلیدواژه‌ها [English]

  • Diabetes
  • Ensemble of a Subset of K-Nearest Neighbor Classifiers
  • Flower Pollination Algorithm
  • K-Nearest Neighbor Algorithm
 

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