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An efficient hybrid weather prediction model based on deep learning
Weather events directly affect human activities. In particular, extreme weather events with global warming, forest fires, and high air temperatures...
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Forecasts of fog events in northern India dramatically improve when weather prediction models include irrigation effects
Dense wintertime fog regularly impacts Delhi, severely affecting road and rail transport, aviation and human health. Recent decades have seen an...
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Evaluation of machine learning approaches for prediction of pigeon pea yield based on weather parameters in India
Pigeon pea is the second most important grain legume in India, primarily grown under rainfed conditions. Any changes in agro-climatic conditions will...
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Weather integrated multiple machine learning models for prediction of dengue prevalence in India
Dengue is a rapidly spreading viral disease transmitted to humans by Aedes mosquitoes. Due to global urbanization and climate change, the number of...
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Choosing multiple linear regressions for weather-based crop yield prediction with ABSOLUT v1.2 applied to the districts of Germany
ABSOLUT v1.2 is an adaptive algorithm that uses correlations between time-aggregated weather variables and crop yields for yield prediction. In...
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Novel combination artificial neural network models could not outperform individual models for weather-based cashew yield prediction
Cashew is an important cash crop which is ecologically sensitive, making it vulnerable to climate change. So, the present study compares the...
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Australia’s 2019/20 Black Summer fire weather exceptionally rare over the last 2000 years
Australia’s record-breaking 2019/20 Black Summer fire weather resulted from a combination of natural and anthropogenic climate factors, but the full...
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Machine learning ensembles, neural network, hybrid and sparse regression approaches for weather based rainfed cotton yield forecast
Cotton is a major economic crop predominantly cultivated under rainfed situations. The accurate prediction of cotton yield invariably helps farmers,...
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High-resolution wind speed forecast system coupling numerical weather prediction and machine learning for agricultural studies — a case study from South Korea
Forecasting wind speed near the surface with high-spatial resolution is beneficial in agricultural management. There is a discrepancy between the...
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Space weather-related activities and projects on-going at INAF-Turin Observatory
The Solar Physics Group at the INAF-Turin Astrophysical Observatory (OATo) is actually involved in different Space Weather (SW) projects and...
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Identification of weather patterns and transitions likely to cause power outages in the United Kingdom
Lightning strikes, snow, and wind are common causes of power system failures. Their frequency of occurrence varies depending on weather patterns and...
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Assessing the power grid vulnerability to extreme weather events based on long-term atmospheric reanalysis
This study presents a framework for evaluating the vulnerability of the electrical grid to storm outages, based on multi-year atmospheric reanalysis...
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A climatology of weather-driven anomalies in European photovoltaic and wind power production
Weather causes extremes in photovoltaic and wind power production. Here we present a comprehensive climatology of anomalies in photovoltaic and wind...
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Indigenous weather forecasting among Gujii pastoralists in southern Ethiopia: Towards monitoring drought
Indigenous weather forecasting (IWF) is practised by various communities around the world. Access to meteorological weather forecasting is limited in...
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A novel model for rainfall prediction using hybrid stochastic-based Bayesian optimization algorithm
Rainfall forecasting is considered one of the key concerns in the meteorological department because it is related strongly to social as well as...
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A new hybrid model for photovoltaic output power prediction
Recently, with the development of renewable energy technologies, photovoltaic (PV) power generation is widely used in the grid. However, as PV power...
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Air Pollution Interactions with Weather and Climate Extremes: Current Knowledge, Gaps, and Future Directions
Purpose of ReviewDuring the past decade, weather and climate extremes, enhanced by climate change trends, have received tremendous attention because...
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Spatial pattern of bias in areal rainfall estimations and its impact on hydrological modeling: a comparative analysis of estimating areal rainfall based on radar and weather station networks in South Korea
Areal rainfall is routinely estimated based on the observed rainfall data using distributed point rainfall gauges. However, the data collected are...
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Joint probability distribution of weather factors: a neural network approach for environmental science
This study introduces methodologies for constructing joint probability distribution functions utilizing the Copula function and neural networks, and...
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Prediction of mustard yield using different machine learning techniques: a case study of Rajasthan, India
Mustard is the second most important edible oilseed after groundnut for India. Adverse weather drastically reduces the mustard yield. Weather...
