414   Artículos

 
en línea
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 ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh    
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Alvaro A. Teran-Quezada, Victor Lopez-Cabrera, Jose Carlos Rangel and Javier E. Sanchez-Galan    
Convolutional neural networks (CNN) have provided great advances for the task of sign language recognition (SLR). However, recurrent neural networks (RNN) in the form of long?short-term memory (LSTM) have become a means for providing solutions to problem... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin    
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Junlin Lou, Burak Yuksek, Gokhan Inalhan and Antonios Tsourdos    
In this study, we consider the problem of motion planning for urban air mobility applications to generate a minimal snap trajectory and trajectory that cost minimal time to reach a goal location in the presence of dynamic geo-fences and uncertainties in ... ver más
Revista: Aerospace    Formato: Electrónico

 
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
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... ver más
Revista: Clean Technologies    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
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... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
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... ver más
Revista: Future Internet    Formato: Electrónico

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