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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...
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Raziyeh AmirTeymoori, Seyed AbdolMajid Jalaee, Mohsen ZayandehRoodi
Pág. 124 - 134
The synchronization of business cycles is one of the new topics that have been raised in recent decades in the field of international business at the same time of increased economic integration between countries. Accordingly, considering the influenced I...
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Yu Yao and Quan Qian
We develop the online process parameter design (OPPD) framework for efficiently handling streaming data collected from industrial automation equipment. This framework integrates online machine learning, concept drift detection and Bayesian optimization t...
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Emanuele Santonicola, Ennio Andrea Adinolfi, Simone Coppola and Francesco Pascale
Nowadays, a vehicle can contain from 20 to 100 ECUs, which are responsible for ordering, controlling and monitoring all the components of the vehicle itself. Each of these units can also send and receive information to other units on the network or exter...
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Timothy O. Hodson, Keith J. Doore, Terry A. Kenney, Thomas M. Over and Muluken B. Yeheyis
Streamflow is one of the most important variables in hydrology, but it is difficult to measure continuously. As a result, nearly all streamflow time series are estimated from rating curves that define a mathematical relationship between streamflow and so...
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Valentina Vendittoli, Wilma Polini, Michael S. J. Walter and Stefan Geißelsöder
Additive manufacturing has transformed the production process by enabling the construction of components in a layer-by-layer approach. This study integrates Artificial Neural Networks to explore the nuanced relationship between process parameters and mec...
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Wendimu Fanta Gemechu, Wojciech Sitek and Gilmar Ferreira Batalha
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Han Zhang, Yadong Wu, Weihan Zhang and Yuling Zhang
The precise ascertainment of stellar ages is pivotal for astrophysical research into stellar characteristics and galactic dynamics. To address the prevalent challenges of suboptimal accuracy in stellar age determination and limited proficiency in apprehe...
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Wei Wang, Huanhuan Feng, Yanzong Li, Quanwei You and Xu Zhou
At present, the determination of tunnel parameters mainly rely on engineering experience and human judgment, which leads to the subjective decision of parameters and an increased construction risk. Machine learning algorithms could provide an objective t...
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Yiming Chen and Shuang Liang
In the field of education, cognitive diagnosis is crucial for achieving personalized learning. The widely adopted DINA (Deterministic Inputs, Noisy And gate) model uncovers students? mastery of essential skills necessary to answer questions correctly. Ho...
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