AIMC Topic: Weather

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Short-term power load forecasting method based on Bagging-stochastic configuration networks.

PloS one
Accurate short-term load forecasting is of great significance in improving the dispatching efficiency of power grids, ensuring the safe and reliable operation of power grids, and guiding power systems to formulate reasonable production plans and redu...

Convolutional Neural Networks Facilitate Process Understanding of Megacity Ozone Temporal Variability.

Environmental science & technology
Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominan...

Parallel prediction of dengue cases with different risks in Mexico using an artificial neural network model considering meteorological data.

International journal of biometeorology
In 2022, Mexico registered an increase in dengue cases compared to the previous year. On the other hand, the amount of precipitation reported annually was slightly less than the previous year. Similarly, the minimum-mean-maximum temperatures recorded...

Conductive interpenetrating network organohydrogels of gellan gum/polypyrrole with weather-tolerance, piezoresistive sensing and shape-memory capability.

International journal of biological macromolecules
To develop ecofriendly multifunctional gel materials for sustainable flexible electronic devices, composite organohydrogels of gellan gum (GG) and polypyrrole (PPy) with an interpenetrating network structure (IPN-GG/PPy organohydrogels) were develope...

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...

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...

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...

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...

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...