219   Artículos

 
en línea
Vinh Pham, Maxim Tyan, Tuan Anh Nguyen and Jae-Woo Lee    
Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity... ver más
Revista: Aerospace    Formato: Electrónico

 
en línea
Zeyu Xu, Wenbin Yu, Chengjun Zhang and Yadang Chen    
In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic collaboration between quantum and classical computing models has emerged as a promising solution for tackling complex computational challenges. Long short-term memory (LSTM)... ver más
Revista: Information    Formato: Electrónico

 
en línea
Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea    
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap... ver más
Revista: Information    Formato: Electrónico

 
en línea
Yusuf Brima, Ulf Krumnack, Simone Pika and Gunther Heidemann    
Self-supervised learning (SSL) has emerged as a promising paradigm for learning flexible speech representations from unlabeled data. By designing pretext tasks that exploit statistical regularities, SSL models can capture useful representations that are ... ver más
Revista: Information    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
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Mei-Yung Leung, Khursheed Ahmed and Isabella Y. S. Chan    
Engineers often play vital roles in technical planning, designing, and operating projects, as well as implementing standard requirements in the physical sites. Although architectural designs may be similar in a construction project, the technical problem... ver más
Revista: Buildings    Formato: Electrónico

 
en línea
Lijun Zu, Wenyu Qi, Hongyi Li, Xiaohua Men, Zhihui Lu, Jiawei Ye and Liang Zhang    
The digital transformation of banks has led to a paradigm shift, promoting the open sharing of data and services with third-party providers through APIs, SDKs, and other technological means. While data sharing brings personalized, convenient, and enriche... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Bao She, Jiating Hu, Linsheng Huang, Mengqi Zhu and Qishuo Yin    
To grasp the spatial distribution of soybean planting areas in time is the prerequisite for the work of growth monitoring, crop damage assessment and yield estimation. The research on remote sensing identification of soybean conducted in China mainly foc... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Jialun Zhang, Donglin Dong and Longqiang Zhang    
Estimating groundwater level (GWL) changes is crucial for the sustainable management of water resources in the face of urbanization and population growth. Existing prediction methods for GWL variations have limitations due to their inability to account f... ver más
Revista: Water    Formato: Electrónico

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