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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...
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Ming-Yen Lin, Ping-Chun Wu and Sue-Chen Hsueh
This study introduces session-aware recommendation models, leveraging GRU (Gated Recurrent Unit) and attention mechanisms for advanced latent interaction data integration. A primary advancement is enhancing latent context, a critical factor for boosting ...
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Ligang Yuan, Jing Liu, Haiyan Chen, Daoming Fang and Wenlu Chen
Scene taxiing time is an important indicator for assessing the operational efficiency of airports as well as green airports, and it is also a fundamental parameter in flight regularity statistics. The accurate prediction of taxiing time can help decision...
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Mohammad Barooni and Deniz Velioglu Sogut
The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an...
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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...
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Qiang Cheng, Yong Cao, Zhifeng Liu, Lingli Cui, Tao Zhang and Lei Xu
The computer numerically controlled (CNC) system is the key functional component of CNC machine tool control systems, and the servo drive system is an important part of CNC systems. The complex working environment will lead to frequent failure of servo d...
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Ilia Zaznov, Julian Martin Kunkel, Atta Badii and Alfonso Dufour
This paper introduces a novel deep learning approach for intraday stock price direction prediction, motivated by the need for more accurate models to enable profitable algorithmic trading. The key problems addressed are effectively modelling complex limi...
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Bochi Guo, Yu Liu, Hui Zhou, Wei Yan and Shuanggen Zhang
Automatic modulation recognition (AMR) provides excellent performance advantages over conventional algorithms and plays a key role in modern communication. However, a general challenge is that the channel errors greatly deteriorate the classification cap...
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Kevin Mero, Nelson Salgado, Jaime Meza, Janeth Pacheco-Delgado and Sebastián Ventura
Unemployment, a significant economic and social challenge, triggers repercussions that affect individual workers and companies, generating a national economic impact. Forecasting the unemployment rate becomes essential for policymakers, allowing them to ...
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Gulshan Saleem, Usama Ijaz Bajwa, Rana Hammad Raza and Fan Zhang
Surveillance video analytics encounters unprecedented challenges in 5G and IoT environments, including complex intra-class variations, short-term and long-term temporal dynamics, and variable video quality. This study introduces Edge-Enhanced TempoFuseNe...
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