This study presents an automated machine learning (AutoML) framework to predict the
casualty rate and direct economic loss induced by earthquakes. The AutoML framework …

Summary Artificial Neural Networks (ANNs) and Kriging have both been used for hydraulic
head simulation. In this study, the two methodologies were combined in order to simulate the …

Lumped, conceptual groundwater models can be used to simulate groundwater level time-
series quickly and efficiently without the need for comprehensive modelling expertise. A new …

Climate variability is strongly influencing hydrological processes under complex weather
conditions, and it should be considered to forecast reservoir inflow for efficient dam …

Artificial neural networks (ANNs) have recently been used to predict the hydraulic head in
well locations. In the present work, the particle swarm optimization (PSO) algorithm was …

Reducing uncertainty in design flood estimates is an essential part of flood risk planning and
management. This study presents results from flood frequency estimates and associated …

Emergency departments are characterized by the need for quick diagnosis under pressure.
To select the most appropriate treatment, a series of rules to support decision-making has …

The problem of groundwater depletion has arisen as havoc in countries like India due to
expanding intensive agriculture, growing population, and burgeoning urban centres. Delhi is …

In the era of sustainable agriculture, the issue of proper and precise implementation of
agrotechnical operations, without harmful effects on the natural environment, begins to play …

The purpose of this study is to examine the uncertainty of various aspects of a combined
artificial neural network (ANN), kriging and fuzzy logic methodology, which can be used for …