با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
---|---|---|
1 |
Evolutionary correlated gravitational search algorithm (ECGS) with genetic optimized Hopfield neural network (GHNN) – A hybrid expert system for diagnosis of diabetes
الگوریتم جستجوی گرانشی همبسته تکاملی (ECGS) با شبکه عصبی بهینه سازی شده ژنتیکی (GHNN) - یک سیستم متخصص ترکیبی برای تشخیص دیابت-2019 In worldwide 415 million of peoples are affected by diabetics in the year of 2015, that is increased from
the year of 2012. Based on the survey, it clearly shows the diabetics are one of the dangerous diseases
because it leads to create several risk of early death. Due to the seriousness of the diabetic, it has been
detected in early stage by creating expert system. During this process, the expert system has several
issues such as accuracy of prediction due to the huge dimension of the diabetic feature that reduce the
entire efficiency of the system. So, in this paper introduced the evolutionary correlated gravitational
search algorithm (ECGS) for selecting the optimized features. The introduced method analyzes each diabetic
feature according to the correlation and mutual information is selected with minimum computation
time and cost. The selected features are processed by genetic optimized Hopfield neural network (GHNN)
for predicting the diabetic related features effectively. Then the efficiency of the system is implemented
using MATLAB tool that utilizes the Pima Indian Diabetic Dataset for analyzing the efficiency of introduced
diabetic expert system. The efficiency of the system is evaluated in terms of using mean square
error rate, F-measurer, accuracy, confusion matrix and ROC curve. Keywords: Diabetics | Evolutionary correlated gravitational search | algorithm (ECGS) | Genetic optimized Hopfield neural network | (GHNN) | Pima Indian Diabetic Dataset |
مقاله انگلیسی |