Long Short-Term Memory vs Gated Recurrent Unit: A Literature Review on the Performance of Deep Learning Methods in Temperature Time Series Forecasting
Temperature forecasting is a crucial aspect of meteorology and climate change studies, but
challenges arise due to the complexity of time series data involving seasonal patterns and …
challenges arise due to the complexity of time series data involving seasonal patterns and …
Forecasting of daily new lumpy skin disease cases in Thailand at different stages of the epidemic using fuzzy logic time series, NNAR, and ARIMA methods
V Punyapornwithaya, O Arjkumpa, N Buamithup… - Preventive Veterinary …, 2023 - Elsevier
Lumpy skin disease (LSD) is an important transboundary disease affecting cattle in
numerous countries in various continents. In Thailand, LSD is regarded as a serious threat …
numerous countries in various continents. In Thailand, LSD is regarded as a serious threat …
Recent advances in electrical engineering: exploring graph neural networks for weather prediction in data-scarce environments
In regions like Nepal, characterized by diverse geography, missing weather data poses a
significant challenge for traditional imputation methods. These methods often struggle to …
significant challenge for traditional imputation methods. These methods often struggle to …
Trend analysis and forecasting of meteorological variables in the lower Thoubal river watershed, India using non-parametrical approach and machine learning models
Climate change, variability and their impact assessment are major concerns of the scientific
community across the world. Changes and variations in meteorological variables have …
community across the world. Changes and variations in meteorological variables have …
Short-term prediction of 80–88 km wind speed in near space based on VMD–PSO–LSTM
S Yang, H Yang, N Li, Z Ding - Atmosphere, 2023 - mdpi.com
The accurate prediction of atmospheric wind speed in near space is of importance for both
middle and upper atmospheric scientific research and engineering applications. In order to …
middle and upper atmospheric scientific research and engineering applications. In order to …
Predicting wind turbine energy production with deep learning methods in GIS: A study on HAWTs and VAWTs
M Mokarram, TM Pham - Sustainable Energy Technologies and …, 2024 - Elsevier
The increasing global demand for renewable energy necessitates accurate forecasting
methods to optimize wind energy production, particularly in regions with varying climatic …
methods to optimize wind energy production, particularly in regions with varying climatic …
A new interval type-2 fuzzy aggregation approach for combining multiple neural networks in clustering and prediction of time series
M Ramírez, P Melin - International Journal of Fuzzy Systems, 2023 - Springer
Inspired by how some cognitive abilities affect the human decision-making process, the
proposed approach combines neural networks with type-2 fuzzy systems. The proposal …
proposed approach combines neural networks with type-2 fuzzy systems. The proposal …
[HTML][HTML] Risk Assessment of Urban Water and Energy Supply Using Copula Function: A Water–Energy Nexus Approach in an Arid City
Planning for the future of water and energy supply systems in urban areas requires a
thorough assessment of associated risks. In this study, monthly water and energy demand …
thorough assessment of associated risks. In this study, monthly water and energy demand …
[HTML][HTML] Exploration of Deep-Learning-Based Error-Correction Methods for Meteorological Remote-Sensing Data: A Case Study of Atmospheric Motion Vectors
H Cao, H Leng, J Zhao, X Xu, J Yang, B Li, Y Zhou… - Remote Sensing, 2024 - mdpi.com
Meteorological satellite remote sensing is important for numerical weather forecasts, but its
accuracy is affected by many things during observation and retrieval, showing that it can be …
accuracy is affected by many things during observation and retrieval, showing that it can be …
Accuracy Assessment of Monthly Rainfall Predictions using Seasonal ARIMA and Long Short-Term Memory (LSTM)
AA Akbar, Y Darmawan, A Wibowo… - Journal of Computer …, 2024 - icsejournal.com
Hydro meteorological disasters are common in Indonesia. Rainfall predictions can help
mitigate the impact of these disasters. This research aims to compare the accuracy of …
mitigate the impact of these disasters. This research aims to compare the accuracy of …