130   Artículos

 
en línea
Feifei He, Qinjuan Wan, Yongqiang Wang, Jiang Wu, Xiaoqi Zhang and Yu Feng    
Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal... ver más
Revista: Water    Formato: Electrónico

 
en línea
Tianao Qin, Ruixin Chen, Rufu Qin and Yang Yu    
Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. G... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Benjamin Burrichter, Juliana Koltermann da Silva, Andre Niemann and Markus Quirmbach    
This study employs a temporal fusion transformer (TFT) for predicting overflow from sewer manholes during heavy rainfall events. The TFT utilised is capable of forecasting overflow hydrographs at the manhole level and was tested on a sewer network with 9... ver más
Revista: Hydrology    Formato: Electrónico

 
en línea
Mykhailo Lohachov, Ryoji Korei, Kazuo Oki, Koshi Yoshida, Issaku Azechi, Salem Ibrahim Salem and Nobuyuki Utsumi    
This article investigates approaches for broccoli harvest time prediction through the application of various machine learning models. This study?s experiment is conducted on a commercial farm in Ecuador, and it integrates in situ weather and broccoli gro... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Efrain Noa-Yarasca, Javier M. Osorio Leyton and Jay P. Angerer    
Timely forecasting of aboveground vegetation biomass is crucial for effective management and ensuring food security. However, research on predicting aboveground biomass remains scarce. Artificial intelligence (AI) methods could bridge this research gap a... ver más
Revista: Agronomy    Formato: Electrónico

 
en línea
Pengfei Ning, Dianjun Zhang, Xuefeng Zhang, Jianhui Zhang, Yulong Liu, Xiaoyi Jiang and Yansheng Zhang    
The Array for Real-time Geostrophic Oceanography (Argo) program provides valuable data for maritime research and rescue operations. This paper is based on Argo historical and satellite observations, and inverted sea surface and submarine drift trajectori... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Anik Baul, Gobinda Chandra Sarker, Prokash Sikder, Utpal Mozumder and Ahmed Abdelgawad    
Short-term load forecasting (STLF) plays a crucial role in the planning, management, and stability of a country?s power system operation. In this study, we have developed a novel approach that can simultaneously predict the load demand of different regio... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Lifen Hu, Ming Zhang, Zhi-Ming Yuan, Hongxia Zheng and Wenbin Lv    
Floating structures have become a major part of offshore structure communities as offshore engineering moves from shallow waters to deeper ones. Floating installation ships or platforms are widely used in these engineering operations. Unexpected wave-ind... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Abdelfatah Ahmed, Mohamed Bader, Ismail Shahin, Ali Bou Nassif, Naoufel Werghi and Mohammad Basel    
The Arabic language has always been an immense source of attraction to various people from different ethnicities by virtue of the significant linguistic legacy that it possesses. Consequently, a multitude of people from all over the world are yearning to... ver más
Revista: Information    Formato: Electrónico

 
en línea
Min Yue and Shuhong Ma    
A crucial component of multimodal transportation networks and long-distance travel chains is the forecasting of transfer passenger flow between integrated hubs in urban agglomerations, particularly during periods of high passenger flow or unusual weather... ver más
Revista: Applied Sciences    Formato: Electrónico

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