Microgrids have recently emerged as a building block for smart grids combining distributed
renewable energy sources (RESs), energy storage devices, and load management …

This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …

Climate change is one of the greatest challenges facing humanity, and we, as machine
learning (ML) experts, may wonder how we can help. Here we describe how ML can be a …

Artificial intelligence (AI) is proving to be an efficient alternative approach to classical
modeling techniques. AI refers to the branch of computer science that develops machines …

Prediction of solar irradiance is essential for minimizing energy costs and providing high
power quality in electrical power grids with distributed solar photovoltaic generations …

With the rapid advancement of the high-performance computing technology and the
increasing availability of the mass-storage memory device, the application of the data-driven …

Using Artificial Intelligence to Improve Real-Time Decision-Making for High-Impact Weather
in: Bulletin of the American Meteorological Society Volume 98 Issue 10 (2017) Jump to …

With the numerous Internet of Things (IoT) devices, the cloud-centric data processing fails to
meet the requirement of all IoT applications. The limited computation and communication …

The challenges to optimally utilize weather dependent renewable energy sources call for
powerful tools for forecasting. This paper presents a non-parametric machine learning …

Solar desalination has emerged as a sustainable solution for addressing global water
scarcity in the energy-water nexus, particularly for remote areas in developing countries …