Deep learning disease prediction model for use with intelligent robots
(چکیده مقاله) :
Abstract :
Deep learning applications with robotics contribute to massive challenges that are not ad- dressed in machine learning. The present world is currently suffering from the COVID-19 pandemic, and millions of lives are getting affected every day with extremely high death counts. Early detection of the disease would provide an opportunity for proactive treat- ment to save lives, which is the primary research objective of this study. The proposed prediction model caters to this objective following a stepwise approach through cleaning, feature extraction, and classification. The cleaning process constitutes the cleaning of miss- ing values ,which is proceeded by outlier detection using the interpolation of splines and entropy-correlation. The cleaned data is then subjected to a feature extraction process us- ing Principle Component Analysis. A Fitness Oriented Dragon Fly algorithm is introduced to select optimal features, and the resultant feature vector is fed into the Deep Belief Net- work. The overall accuracy of the proposed scheme experimentally evaluated with the tra- ditional state of the art models. The results highlighted the superiority of the proposed model wherein it was observed to be 6.96% better than Firefly, 6.7% better than Particle Swarm Optimization, 6.96% better than Gray Wolf Optimization ad 7.22% better than Drag- onfly Algorithm.
(توضیحات تکمیلی) :
(توضیحات تکمیلی) :
Description :
مقاله ISI انگلیسی اصلی
سال انتشار: 2020
فایل ISI انگلیسی اصلی ، با فرمت Pdf
تعداد صفحات فایل ISI انگلیسی اصلی: 13 صفحه
سال انتشار: 2020
فایل ISI انگلیسی اصلی ، با فرمت Pdf
تعداد صفحات فایل ISI انگلیسی اصلی: 13 صفحه
Authors / Descriptions(نویسندگان/توضیحات): سال انتشار 2020 \ مقاله ISI انگلیسی اصلی \ نویسندگان: Srinivas Koppu a , Praveen Kumar Reddy Maddikunta a , Gautam Srivastava
Sent date(تاریخ ارسال) :
1399/06/14 | 9/4/2020
Number of visits(تعداد بازدید):
611
Key words (کلمات کلیدی):
COVID-19 Deep learning Intelligent robotics Data cleaning Disease prediction Dragonfly optimization Feature extraction Fitness basis
Number of pages(تعداد صفحات) :
13
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