|
|
|
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
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
Stanislav Letkovský, Sylvia Jencová and Petra Va?anicová
Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial in...
ver más
|
|
|
|
|
|
|
Claudia Angelica Rivera-Romero, Jorge Ulises Munoz-Minjares, Carlos Lastre-Dominguez and Misael Lopez-Ramirez
Identifying patient posture while they are lying in bed is an important task in medical applications such as monitoring a patient after a surgical intervention, sleep supervision to identify behavioral and physiological markers, or for bedsore prevention...
ver más
|
|
|
|
|
|
|
Abdelkrim Lachgar, David J. Mulla and Viacheslav Adamchuk
One of the challenges in site-specific phosphorus (P) management is the substantial spatial variability in plant available P across fields. To overcome this barrier, emerging sensing, data fusion, and spatial predictive modeling approaches are needed to ...
ver más
|
|
|
|
|
|
|
Filippo Orazi, Simone Gasperini, Stefano Lodi and Claudio Sartori
Quantum computing has rapidly gained prominence for its unprecedented computational efficiency in solving specific problems when compared to classical computing counterparts. This surge in attention is particularly pronounced in the realm of quantum mach...
ver más
|
|
|
|
|
|
|
Shweta More, Moad Idrissi, Haitham Mahmoud and A. Taufiq Asyhari
The rapid proliferation of new technologies such as Internet of Things (IoT), cloud computing, virtualization, and smart devices has led to a massive annual production of over 400 zettabytes of network traffic data. As a result, it is crucial for compani...
ver más
|
|
|
|
|
|
|
Haoyu Lin, Pengkun Quan, Zhuo Liang, Dongbo Wei and Shichun Di
In the context of automatic charging for electric vehicles, collision localization for the end-effector of robots not only serves as a crucial visual complement but also provides essential foundations for subsequent response design. In this scenario, dat...
ver más
|
|
|
|
|
|
|
Junting Wang, Tianhe Xu, Wei Huang, Liping Zhang, Jianxu Shu, Yangfan Liu and Linyang Li
Underwater sound speed is one of the most significant factors that affects high-accuracy underwater acoustic positioning and navigation. Due to its complex temporal variation, the forecasting of the underwater sound speed field (SSF) becomes a challengin...
ver más
|
|
|
|
|
|
|
Edwin Peralta-Garcia, Juan Quevedo-Monsalbe, Victor Tuesta-Monteza and Juan Arcila-Diaz
Structured Query Language (SQL) injections pose a constant threat to web services, highlighting the need for efficient detection to address this vulnerability. This study compares machine learning algorithms for detecting SQL injections in web microservi...
ver más
|
|
|
|