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Short- and long-term weather prediction based on a hybrid of CEEMDAN, LMD, and ANN.

PloS one
Agriculture is one of the major economic sectors in Africa, and it predominantly depends on the climate. However, extreme climate changes do have a negative impact on agricultural production. The damage resulting from extreme climate change can be mi...

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...

Deep learning to extract the meteorological by-catch of wildlife cameras.

Global change biology
Microclimate-proximal climatic variation at scales of metres and minutes-can exacerbate or mitigate the impacts of climate change on biodiversity. However, most microclimate studies are temperature centric, and do not consider meteorological factors ...

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...

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...

Machine learning ensembles, neural network, hybrid and sparse regression approaches for weather based rainfed cotton yield forecast.

International journal of biometeorology
Cotton is a major economic crop predominantly cultivated under rainfed situations. The accurate prediction of cotton yield invariably helps farmers, industries, and policy makers. The final cotton yield is mostly determined by the weather patterns th...

Unmasking the sky: high-resolution PM prediction in Texas using machine learning techniques.

Journal of exposure science & environmental epidemiology
BACKGROUND: Although PM (fine particulate matter with an aerodynamic diameter less than 2.5 µm) is an air pollutant of great concern in Texas, limited regulatory monitors pose a significant challenge for decision-making and environmental studies.

Enhancement of ANN-based wind power forecasting by modification of surface roughness parameterization over complex terrain.

Journal of environmental management
Wind energy plays an important role in the sustainable energy transition towards a low-carbon society. Proper assessment of wind energy resources and accurate wind energy prediction are essential prerequisites for balancing electricity supply and dem...

Comparative analysis of different Karnal bunt disease prediction models developed by machine learning techniques for Punjab conditions.

International journal of biometeorology
Timely prediction of pathogen is important key factor to reduce the quality and yield losses. Wheat is major crop in northern part of India. In Punjab, wheat face challenge by different diseases so the study was conducted for two locations viz. Ludhi...