Artificial Neural Network Tuning by Improved Sine Cosine Algorithm for HealthCare 4.0
Masa Gajevic, Nemanja Milutinovic, Jelena Krstovic, Luka Jovanović, Miodrag Živković, Marina Marjanović, Cătălin Stoean
Abstract
This paper explores classification of datasets for Healthcare 4.0 using artificial neural networks which are tuned by improved sine cosine algorithm (SCA).Healthcare 4.0 themes include internet of things (IoT), industrial IoT (IIoT), cognitive computing, artificial intelligence, cloud computing, fog computing, edge computing, and other industry 4.0 procedures.Health issues identification are critical since prompt treatment improves the quality of life for individuals affected.One of the most difficult challenges for artificial intelligence (AI) is selecting control parameters that are appropriate for the situation at hand.This paper presents a metaheuristics-based method for training the artificial neural network, by utilizing the SCA.