HIGH EFFICIENCY BIDIRECTIONAL LLC+C RESONANT CONVERTER WITH PARALLEL TRANSFORMERS FOR SOLAR- CHARGED ELECTRIC VEHICLES

Abstract

Healthcare is being revolutionised by the rise of cloud computing, artificial intelligence (AI),and the Internet of Things (IoT) technologies, that are replacing conventional approaches withintelligent, data-driven solutions. Cloud computing (CC) provides safe storage, expeditedpatient data access, and scalable infrastructure that can manage the enormous volumes of healthdata produced by wearables and Internet of Things devices in the modern healthcare industryPriyanka & Kaur (2018). In this scenario, machine learning (ML) techniques—like Long Short-Term Memory (LSTM) networks—are essential because they analyse intricate trends in health data over time to enhance disease predicting. Ant Colony Optimisation (ACO) is used in this study to train LSTM networks, improving prediction speed and accuracy for monitoring acute and chronic diseases. Ant behaviour serves as inspiration for ACO, that maximises the LSTM model's parameters to achieve faster convergence towards the most accurate prediction for a range of healthcare needs.