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Coagulant dosage determination using deep learning-based graph attention multivariate time series forecasting model.

Water research
Determination of coagulant dosage in water treatment is a time-consuming process involving nonlinear data relationships and numerous factors. This study provides a deep learning approach to determine coagulant dosage and/or the settled water turbidit...

Prediction of mustard yield using different machine learning techniques: a case study of Rajasthan, India.

International journal of biometeorology
Mustard is the second most important edible oilseed after groundnut for India. Adverse weather drastically reduces the mustard yield. Weather variables affect the crop differently during different stages of development. Weather influence on crop yiel...

Decision support system to classify the vulnerability of broiler production system to heat stress based on fuzzy logic.

International journal of biometeorology
In this study, we develop an artificial intelligence model to predict the vulnerability of broiler production systems (broilers and facilities) to heat conditions using a fuzzy model approach. The model was designed with a multiple-input and a single...

Deep Learning with Attention Mechanisms for Road Weather Detection.

Sensors (Basel, Switzerland)
There is great interest in automatically detecting road weather and understanding its impacts on the overall safety of the transport network. This can, for example, support road condition-based maintenance or even serve as detection systems that assi...

A Synthetic Data Generation Technique for Enhancement of Prediction Accuracy of Electric Vehicles Demand.

Sensors (Basel, Switzerland)
In terms of electric vehicles (EVs), electric kickboards are crucial elements of smart transportation networks for short-distance travel that is risk-free, economical, and environmentally friendly. Forecasting the daily demand can improve the local s...

A new rainfall prediction model based on ICEEMDAN-WSD-BiLSTM and ESN.

Environmental science and pollution research international
Precipitation, as an important indicator describing the evolution of the regional climate system, plays an important role in understanding the spatial and temporal distribution characteristics of regional precipitation. Scientific and accurate predic...

The use of weather nowcasting convolutional neural network extrapolators in cardiac PET imaging.

Journal of medical radiation sciences
INTRODUCTION: Algorithms to predict short-term changes in local weather modalities have been used in meteorology for many years. These algorithms predict the temporospatial change in the movement of weather patterns such as cloud cover or precipitati...

Development and performance of a machine learning-based tool that predicts influent flow to a WRF 72 h in advance and integrates with existing wet weather nutrient management protocols.

Water environment research : a research publication of the Water Environment Federation
Influent flow to the 75 mgd Neuse River Resource Recovery Facility (NRRRF) was modeled using machine learning. The trained model can predict hourly flow 72 h in advance. This model was deployed in July 2020, and has been in operation over two and a h...

Anthropogenic fingerprints in daily precipitation revealed by deep learning.

Nature
According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe. However, verifying this prediction using observations has remained a substantial challenge owing to lar...

Machine learning approach for the estimation of missing precipitation data: a case study of South Korea.

Water science and technology : a journal of the International Association on Water Pollution Research
Precipitation is one of the driving forces in water cycles, and it is vital for understanding the water cycle, such as surface runoff, soil moisture, and evapotranspiration. However, missing precipitation data at the observatory becomes an obstacle t...