4.868   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
Ognjen Radovic,Srdan Marinkovic,Jelena Radojicic    
Credit scoring attracts special attention of financial institutions. In recent years, deep learning methods have been particularly interesting. In this paper, we compare the performance of ensemble deep learning methods based on decision trees with the b... ver más
Revista: Facta Universitatis. Series: Economics and Organization    Formato: Electrónico

 
en línea
Jiarui Xia and Yongshou Dai    
Ground roll noise suppression is a crucial step in processing deep pre-stack seismic data. Recently, supervised deep learning methods have gained popularity in this field due to their ability to adaptively learn and extract powerful features. However, th... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Nan Lao Ywet, Aye Aye Maw, Tuan Anh Nguyen and Jae-Woo Lee    
Urban Air Mobility (UAM) emerges as a transformative approach to address urban congestion and pollution, offering efficient and sustainable transportation for people and goods. Central to UAM is the Operational Digital Twin (ODT), which plays a crucial r... ver más
Revista: Aerospace    Formato: Electrónico

 
en línea
Nawaf Alharbi, Mustafa Youldash, Duha Alotaibi, Haya Aldossary, Reema Albrahim, Reham Alzahrani, Wahbia Ahmed Saleh, Sunday O. Olatunji and May Issa Aldossary    
Fetal hypoxia is a condition characterized by a lack of oxygen supply in a developing fetus in the womb. It can cause potential risks, leading to abnormalities, birth defects, and even mortality. Cardiotocograph (CTG) monitoring is among the techniques t... ver más
Revista: AI    Formato: Electrónico

 
en línea
Feng Zhou, Shijing Hu, Xin Du, Xiaoli Wan and Jie Wu    
In the current field of disease risk prediction research, there are many methods of using servers for centralized computing to train and infer prediction models. However, this centralized computing method increases storage space, the load on network band... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Konstantinos Psychogyios, Andreas Papadakis, Stavroula Bourou, Nikolaos Nikolaou, Apostolos Maniatis and Theodore Zahariadis    
The advent of computer networks and the internet has drastically altered the means by which we share information and interact with each other. However, this technological advancement has also created opportunities for malevolent behavior, with individual... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Javid Misirli and Emiliano Casalicchio    
The Internet of Things (IoT) uptake brought a paradigm shift in application deployment. Indeed, IoT applications are not centralized in cloud data centers, but the computation and storage are moved close to the consumers, creating a computing continuum b... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Xie Lian, Xiaolong Hu, Liangsheng Shi, Jinhua Shao, Jiang Bian and Yuanlai Cui    
The parameters of the GR4J-CemaNeige coupling model (GR4neige) are typically treated as constants. However, the maximum capacity of the production store (parX1) exhibits time-varying characteristics due to climate variability and vegetation coverage chan... ver más
Revista: Water    Formato: Electrónico

 
en línea
Yongen Lin, Dagang Wang, Tao Jiang and Aiqing Kang    
Reliable streamflow forecasting is a determining factor for water resource planning and flood control. To better understand the strengths and weaknesses of newly proposed methods in streamflow forecasting and facilitate comparisons of different research ... ver más
Revista: Water    Formato: Electrónico

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