A deep learning-based approach for predicting COVID-19 diagnosis.

This paper focuses on forecasting the total count of confirmed COVID-19 cases in Saudi Arabia through a range of methodologies, including ARIMA, mathematical modeling, and deep learning network (DQN) techniques. Its primary aim is to anticipate the verified COVID-19 cases in Saudi Arabia, aiding in decision-making for life-saving interventions by enhancing awareness of COVID-19 infection. Mathematical modeling and ARIMA are employed for their efficacy in forecasting, while DQN approaches, particularly through comparative analysis, are utilized for prediction.

Artificial intelligence in healthcare: combining deep learning and Bayesian optimization to forecast COVID-19 confirmed cases.

Healthcare is a topic of significant concern within the academic and business sectors. The COVID-19 pandemic has had a considerable effect on the health of people worldwide. The rapid increase in cases adversely affects a nation's economy, public health, and residents' social and personal well-being.

Energy Internet Opportunities in Distributed Peer-to-Peer Energy Trading Reveal by Blockchain for Future Smart Grid 2.0.

The Energy Internet (EI) and Smart Grid 2.0 (SG 2.0) concepts are potential challenges in industry and research.

Model for Managing the Integration of a Vehicle-to-Home Unit into an Intelligent Home Energy Management System.

Integration of vehicle-to-home (V2H) centralized photovoltaic (HCPV) systems is a requested and potentially fruitful research topic for both industry and academia. Renewable energy sources, such as wind turbines and solar photovoltaic panels, alleviate energy deficits. Furthermore, energy storage technologies, such as batteries, thermal, and electric vehicles, are indispensable.

Multi-Agent Systems for Resource Allocation and Scheduling in a Smart Grid.

Multi-Agent Systems (MAS) have been seen as an attractive area of research for civil engineering professionals to subdivide complex issues. Based on the assignment's history, nearby agents, and objective, the agent intended to take the appropriate action to complete the task. MAS models complex systems, smart grids, and computer networks.