Abstract Edge Artificial Intelligence (AI) incorporates a network of interconnected systems
and devices that receive, cache, process, and analyse data in close communication with the …

The article examines machine learning models for precipitation forecasting in the Ambica
River basin, addressing the important requirement for accurate hydrological forecasts in …

This study evaluates three Machine Learning (ML) models—Temporal Kolmogorov-Arnold
Networks (TKAN), Long Short-Term Memory (LSTM), and Temporal Convolutional Networks …

The forecasting of river flows and pollutant concentrations is essential in supporting
mitigation measures for anthropogenic and climate change effects on rivers and their …

Water quality prediction is crucial for effective river stream management. Dissolved oxygen,
conductivity and chemical oxygen demand are vital chemical parameters for water quality …

In modern aquaculture, the focus is on optimizing production and minimizing environmental
impact through the use of recirculating water systems, particularly in outdoor setups. In such …

Water quality prediction is crucial for effective river stream management. Dissolved oxygen,
conductivity and chemical oxygen demand are vital chemical parameters for water quality …

This study introduces a novel machine-learning approach using Sentinel-2 satellite images
for water quality assessment in the Danube River. Utilizing a deep neural network to build a …

This study introduces a novel machine-learning approach using Sentinel-2 satellite images
for water quality assessment in the Danube River. Uti-lizing a deep neural network to build a …

Abstract The Water Quality Index (WQI) shows the condition of water quality in an area
based on the status of water quality resulting from the measurement of physical, chemical …