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M.H.J.P. Gunarathna, Kazuhito Sakai, Tamotsu Nakandakari, Kazuro Momii and M.K.N. Kumari
Poor data availability on soil hydraulic properties in tropical regions hampers many studies, including crop and environmental modeling. The high cost and effort of measurement and the increasing demand for such data have driven researchers to search for...
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Wenhao Li, Xianxia Zhang, Yueying Wang and Songbo Xie
Model predictive control (MPC), an extensively developed rolling optimization control method, is widely utilized in the industrial field. While some researchers have incorporated predictive control into underactuated unmanned surface vehicles (USVs), mos...
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Luis Zuloaga-Rotta, Rubén Borja-Rosales, Mirko Jerber Rodríguez Mallma, David Mauricio and Nelson Maculan
The forecasting of presidential election results (PERs) is a very complex problem due to the diversity of electoral factors and the uncertainty involved. The use of a hybrid approach composed of techniques such as machine learning (ML) and Simulation in ...
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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...
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Alexios Lekidis, Angelos Georgakis, Christos Dalamagkas and Elpiniki I. Papageorgiou
The scheduled maintenance of industrial equipment is usually performed with a low frequency, as it usually leads to unpredicted downtime in business operations. Nevertheless, this confers a risk of failure in individual modules of the equipment, which ma...
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Ahmed Skhiri, Ali Ferhi, Anis Bousselmi, Slaheddine Khlifi and Mohamed A. Mattar
A correct determination of irrigation water requirements necessitates an adequate estimation of reference evapotranspiration (ETo). In this study, monthly ETo is estimated using artificial neural network (ANN) models. Eleven combinations of long-term ave...
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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 ...
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Syed Safdar Hussain and Syed Sajjad Haider Zaidi
This study introduces a novel predictive methodology for diagnosing and predicting gear problems in DC motors. Leveraging AdaBoost with weak classifiers and regressors, the diagnostic aspect categorizes the machine?s current operational state by analyzin...
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Bochi Guo, Yu Liu, Hui Zhou, Wei Yan and Shuanggen Zhang
Automatic modulation recognition (AMR) provides excellent performance advantages over conventional algorithms and plays a key role in modern communication. However, a general challenge is that the channel errors greatly deteriorate the classification cap...
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Daniel Rusche, Nils Englert, Marlen Runz, Svetlana Hetjens, Cord Langner, Timo Gaiser and Cleo-Aron Weis
Background: In this study focusing on colorectal carcinoma (CRC), we address the imperative task of predicting post-surgery treatment needs by identifying crucial tumor features within whole slide images of solid tumors, analogous to locating a needle in...
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