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Muhammad Nouman Amjad Raja, Tarek Abdoun and Waleed El-Sekelly
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Subin Kim, Heejin Hwang, Keunyeong Oh and Jiuk Shin
The seismically deficient column details in existing reinforced concrete buildings affect the overall behavior of the building depending on the failure type of the column. The purpose of this study is to develop and validate a machine-learning-based pred...
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Celal Cakiroglu
The current study offers a data-driven methodology to predict the ultimate strain and compressive strength of concrete reinforced by aramid FRP wraps. An experimental database was collected from the literature, on which seven different machine learning (...
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Guangchao Yang, Jigang Zhang, Zhehao Ma and Weixiao Xu
The steel tube-reinforced concrete (STRC) shear wall plays an important role in the seismic design of high-rise building structures. Due to the synergistic collaboration between steel tubes and concrete, they effectively enhance the ductility and energy ...
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Filippos Sofos, Christos G. Papakonstantinou, Maria Valasaki and Theodoros E. Karakasidis
Provide the compressive strength of fiber reinforced polymer confined concrete specimens with machine learning tools based on real, experimental measurements.
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Roman Trach
Recently, the bridge infrastructure in Ukraine has faced the problem of having a significant number of damaged bridges. It is obvious that the repair and restoration of bridges should be preceded by a procedure consisting of visual inspection and evaluat...
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Franz Wagner, Leonie Mester, Sven Klinkel and Hans-Gerd Maas
This study focuses on the development of novel evaluation methods for the analysis of thin carbon reinforced concrete (CRC) structures. CRC allows for the exploration of slender components and innovative construction techniques due to its high tensile st...
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Subhendu Das, Sridhar Tripathy, Priyanka Jagga, Purba Bhattacharya, Nayana Majumdar and Supratik Mukhopadhyay
Aging infrastructure is a threatening issue throughout the world. Long exposure to oxygen and moisture causes premature corrosion of reinforced concrete structures leading to the collapse of the structures. As a consequence, real-time monitoring of civil...
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Davide Bettoni, Anton Soppelsa, Roberto Fedrizzi and Raul Mario del Toro Matamoros
This paper discusses the development of a coupled Q-learning/fuzzy control algorithm to be applied to the control of solar domestic hot water systems. The controller brings the benefit of showing performance in line with the best reference controllers wi...
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Georgios K. Bekas and Georgios E. Stavroulakis
The present study investigates the potential of the implementation of machine learning techniques in optimized multi storey reinforced concrete frames. The variables that are taken into account in the objective function of the optimization problem are th...
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Georgios K. Bekas, Georgios E. Stavroulakis
Pág. 1 - 12
The present study investigates the potential of the implementation of machine learning techniques in optimized multi storey reinforced concrete frames. The variables that are taken into account in the objective function of the optimization problem are th...
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Ali Mirzazade, Cosmin Popescu and Björn Täljsten
The aim of this study was to find strains in embedded reinforcement by monitoring surface deformations. Compared with analytical methods, application of the machine learning regression technique imparts a noteworthy reduction in modeling complexity cause...
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Yonglin Chen, Junming Zhang, Zefu Li, Huliang Zhang, Jiping Chen, Weidong Yang, Tao Yu, Weiping Liu and Yan Li
Lightweight fiber-reinforced composite structures have been applied in aerospace for decades. Their mechanical properties are crucial for the safety of aircraft and mainly depend on manufacturing technologies such as autoclave, resin transfer molding and...
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Lulu Shen, Yuanxie Shen and Shixue Liang
Reinforced concrete slab-column structures, despite their advantages such as architectural flexibility and easy construction, are susceptible to punching shear failure. In addition, punching shear failure is a typical brittle failure, which introduces di...
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J. Clarke, A. McIlhagger, E. Archer, T. Dooher, T. Flanagan and P. Schubel
A problem for wind turbine operators is decreasing prices for wind-generated electricity. Many turbines are approaching their rated 20-year lives. A more economically viable and sustainable solution that reduces Levelized Cost of Energy (LCOE) and avoids...
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Tzu-Ching Tai, Chen-Cheng Lee and Cheng-Chien Kuo
This paper proposes a new hybrid algorithm for grey wolf optimization (GWO) integrated with a robust learning mechanism to solve the large-scale economic load dispatch (ELD) problem. The robust learning grey wolf optimization (RLGWO) algorithm imitates t...
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Stefan Strauß
Astonishing progress is being made in the field of artificial intelligence (AI) and particularly in machine learning (ML). Novel approaches of deep learning are promising to even boost the idea of AI equipped with capabilities of self-improvement. But wh...
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Stefan Strauß
Astonishing progress is being made in the field of artificial intelligence (AI) and particularly in machine learning (ML). Novel approaches of deep learning are promising to even boost the idea of AI equipped with capabilities of self-improvement. But wh...
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Jose M. Bernal-de-Lázaro
Pág. 74 - 81
This article summarizes the main contributions of the PhD thesis titled: "Application of learning techniques based on kernel methods for the fault diagnosis in Industrial processes". This thesis focuses on the analysis and design of fault diagnosis syste...
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Yongtao Lyu, Yibiao Niu, Tao He, Limin Shu, Michael Zhuravkov and Shutao Zhou
In this paper, a new method using the backpropagation (BP) neural network combined with the improved genetic algorithm (GA) is proposed for the inverse design of thin-walled reinforced structures. The BP neural network model is used to establish the mapp...
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