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Dibo Dong, Shangwei Wang, Qiaoying Guo, Yiting Ding, Xing Li and Zicheng You
Predicting wind speed over the ocean is difficult due to the unequal distribution of buoy stations and the occasional fluctuations in the wind field. This study proposes a dynamic graph embedding-based graph neural network?long short-term memory joint fr...
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Abdullah F. Al-Aboosi, Aldo Jonathan Muñoz Vazquez, Fadhil Y. Al-Aboosi, Mahmoud El-Halwagi and Wei Zhan
Accurate prediction of renewable energy output is essential for integrating sustainable energy sources into the grid, facilitating a transition towards a more resilient energy infrastructure. Novel applications of machine learning and artificial intellig...
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Christy Pérez-Albornoz, Ángel Hernández-Gómez, Victor Ramirez and Damien Guilbert
Installation of new wind farms in areas such as the north coast of the Yucatan peninsula is of vital importance to face the local energy demand. For the proper functioning of these facilities it is important to perform wind data analysis, the data having...
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Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li and Fengjun Hu
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
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Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa and Fernando Morgado-Dias
Wind forecasting, which is essential for numerous services and safety, has significantly improved in accuracy due to machine learning advancements. This study reviews 23 articles from 1983 to 2023 on machine learning for wind speed and direction nowcasti...
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Juan M. Lujano-Rojas, Rodolfo Dufo-López, Jesús Sergio Artal-Sevil and Eduardo García-Paricio
Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to const...
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Ryunosuke Komura and Masayuki Matsuoka
Malaria is a major public health concern, and accurate mapping of malaria risk is essential to effectively managing the disease. However, current models are unable to predict malaria risk with high temporal and spatial resolution. This study describes a ...
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Nikolaos Malamos, Dimitrios Koulouris, Ioannis L. Tsirogiannis and Demetris Koutsoyiannis
The evaluation of weather forecast accuracy is of major interest in decision making in almost every sector of the economy and in civil protection. To this, a detailed assessment of Bologna Limited-Area Model (BOLAM) seven days fine grid 3 h predictions i...
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Chenghan Luo, Shaoping Shang, Yanshuang Xie, Zhigang He, Guomei Wei, Feng Zhang, Lei Wang and Xueding Li
The terrain, such as Taiwan Island, have been shown to have complex effects on typhoons and the associated typhoon waves. Terrain effects change with typhoon tracks. In this study, three types of typhoon tracks (northern, middle and southern) were define...
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Deokhwan Kim, Cheolhee Jang, Jeonghyeon Choi and Jaewon Kwak
As a significant portion of the available water resources in volcanic terrains such as Jeju Island are dependent on groundwater, reliable groundwater level forecasting is one of the important tasks for efficient water resource management. This study aims...
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