252   Artículos

 
en línea
Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib    
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow... ver más
Revista: Water    Formato: Electrónico

 
en línea
Haobin Wen, Long Zhang and Jyoti K. Sinha    
On top of the condition-based maintenance (CBM) practice for rotating machinery, the robust estimation of remaining useful life (RUL) for rolling-element bearings (REB) is of particular interest. The failure of a single bearing often results in secondary... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Xiaoou Li    
This paper tackles the challenge of time series forecasting in the presence of missing data. Traditional methods often struggle with such data, which leads to inaccurate predictions. We propose a novel framework that combines the strengths of Generative ... ver más
Revista: Information    Formato: Electrónico

 
en línea
Yunzhou Chen, Shumin Wang, Ziying Gu and Fan Yang    
Spatial population distribution data is the discretization of demographic data into spatial grids, which has vital reference significance for disaster emergency response, disaster assessment, emergency rescue resource allocation, and post-disaster recons... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Zhe Yang, Yi Huang, Yaqin Chen, Xiaoting Wu, Junlan Feng and Chao Deng    
Controllable Text Generation (CTG) aims to modify the output of a Language Model (LM) to meet specific constraints. For example, in a customer service conversation, responses from the agent should ideally be soothing and address the user?s dissatisfactio... ver más
Revista: Applied Sciences    Formato: Electrónico

 
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
Krzysztof Drachal and Michal Pawlowski    
This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities? prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approa... ver más
Revista: International Journal of Financial Studies    Formato: Electrónico

 
en línea
Saile Zhang, Qingzhen Yang, Rui Wang and Xufei Wang    
The use of traditional optimization methods in engineering design problems, specifically in aerodynamic and infrared stealth optimization for engine nozzles, requires a large number of objective function evaluations, therefore introducing a considerable ... ver más
Revista: Aerospace    Formato: Electrónico

 
en línea
Vedat Dogan and Steven Prestwich    
In a multi-objective optimization problem, a decision maker has more than one objective to optimize. In a bilevel optimization problem, there are the following two decision-makers in a hierarchy: a leader who makes the first decision and a follower who r... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Sofía Ramos-Pulido, Neil Hernández-Gress and Gabriela Torres-Delgado    
Current research on the career satisfaction of graduates limits educational institutions in devising methods to attain high career satisfaction. Thus, this study aims to use data science models to understand and predict career satisfaction based on infor... ver más
Revista: Informatics    Formato: Electrónico

« Anterior     Página: 1 de 15     Siguiente »