Deep learning (DL), a new generation of artificial neural network research, has transformed
industries, daily lives, and various scientific disciplines in recent years. DL represents …

Urban big data fusion creates huge values for urban computing in solving urban problems.
In recent years, various models and algorithms based on deep learning have been …

Rainfall–runoff modelling is one of the key challenges in the field of hydrology. Various
approaches exist, ranging from physically based over conceptual to fully data-driven …

Abstract Launched in May 2018, the Gravity Recovery and Climate Experiment Follow‐On
mission (GRACE‐FO)—the successor of the erstwhile GRACE mission—monitors changes …

The recent proliferation of ubiquitous computing technologies has led to the emergence of
urban computing that aims to provide intelligent services to inhabitants of smart cities. Urban …

Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming
industry applications and generating new and improved capabilities for scientific discovery …

Objective In the last few years, several techniques and models are used for retrieving
significant information from urban big data of smart cities. This research work aims at …

Accurate and timely precipitation estimates are critical for monitoring and forecasting natural
disasters such as floods. Despite having high-resolution satellite information, precipitation …

The Coronavirus pandemic and the work-from-home have drastically changed the working
style and forced us to rapidly shift towards cloud-based platforms & services for seamless …

Predicting groundwater levels is challenging, especially in regions of water scarcity where
data availability is often limited. However, these regions have substantial water needs and …