Adaptive assessment of reservoir scheduling to hydrometeorological comprehensive dry and wet condition evolution in a multi-reservoir region of southeastern China
H Chen, B Xu, H Qiu, S Huang, RSV Teegavarapu… - Journal of …, 2025 - Elsevier
The role of reservoirs in water resource management is becoming crucial for flood control
and drought mitigation in any basin because of the frequent occurrence of extreme weather …
and drought mitigation in any basin because of the frequent occurrence of extreme weather …
Hypertuned wavelet convolutional neural network with long short-term memory for time series forecasting in hydroelectric power plants
Energy planning in Brazil is based on assessing the availability of hydrological resources in
the future, thus guaranteeing the supply of energy based on hydroelectric generation …
the future, thus guaranteeing the supply of energy based on hydroelectric generation …
[HTML][HTML] PredXGBR: A Machine Learning Framework for Short-Term Electrical Load Prediction
The growing demand for consumer-end electrical load is driving the need for smarter
management of power sector utilities. In today's technologically advanced society, efficient …
management of power sector utilities. In today's technologically advanced society, efficient …
[HTML][HTML] State of the art in energy consumption using deep learning models
In the literature, it is well known that there is a bidirectional causality between economic
growth and energy consumption. This is why it is crucial to forecast energy consumption. In …
growth and energy consumption. This is why it is crucial to forecast energy consumption. In …
[HTML][HTML] An Ensemble Approach to Predict a Sustainable Energy Plan for London Households
The energy sector plays a vital role in driving environmental and social advancements.
Accurately predicting energy demand across various time frames offers numerous benefits …
Accurately predicting energy demand across various time frames offers numerous benefits …
Study of Rainfall Occurrence Process by Markov Chain Models and Decision Tree-based Ensemble and Boosting Techniques
Rainfall prediction is vital for water resource management, agricultural planning, and urban
design. While extensive research exists on rainfall magnitude forecasting, less attention has …
design. While extensive research exists on rainfall magnitude forecasting, less attention has …
A Random Forest-Convolutional Neural Network Deep Learning Model for Predicting the Wholesale Price Index of Potato in India
The wholesale price index (WPI) is a crucial economic indicator that provides insights into
the pricing dynamics of different goods within a country, especially potato commodities. In …
the pricing dynamics of different goods within a country, especially potato commodities. In …
Machine learning-based modeling of Syrian agricultural GDP trends: A comparative analysis
K Alakkari - DYSONA-Applied Science, 2025 - applied.dysona.org
This research examined the effectiveness of Autoregressive Integrated Moving Average
(ARIMA), Neural Network Autoregressive (NNAR), and eXtreme Gradient Boosting …
(ARIMA), Neural Network Autoregressive (NNAR), and eXtreme Gradient Boosting …
Time series study of climate variables utilising a seasonal ARIMA technique for the Indian states of Punjab and Haryana
P Dahiya, M Kumar, S Manhas, A Saini… - Discover Applied …, 2024 - Springer
Weather parameters, such as precipitation and temperature predictions, could be
advantages in to making decisions, risk management, and water resource optimization …
advantages in to making decisions, risk management, and water resource optimization …
What works better with LSTM, decomposition or deseasonalisation for rainfall forecasting?
Forecasting rainfall is crucial for countries like India where farming is the livelihood for
around half of the population and rainfall is their most important water source. The intensity …
around half of the population and rainfall is their most important water source. The intensity …