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Katayoon Kiany, Abolfazl Baghbani, Hossam Abuel-Naga, Hasan Baghbani, Mahyar Arabani and Mohammad Mahdi Shalchian
This study examines the potential of the soft computing technique, namely, multiple linear regression (MLR), genetic programming (GP), classification and regression trees (CART) and GA-ENN (genetic algorithm-emotional neuron network), to predict the ulti...
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Martina Attenni, Carlo Bianchini, Marika Griffo and Luca James Senatore
The paper aims at investigating modelling strategies in HBIM context to identify at what extent the final use of the model might affects, or should affect, the modelling approach itself. Moreover, the discussion wants to shed light on the possibility of ...
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Dieter De Paepe, Andy Van Yperen-De Deyne, Jan Defever and Sofie Van Hoecke
Our anomaly detection model will be used to monitor seam welding in the cold mill annealing line of the ArcelorMittal Ghent steel mill.
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Emmanuel Okiria, Hiromu Okazawa, Keigo Noda, Yukimitsu Kobayashi, Shinji Suzuki and Yuri Yamazaki
The prediction of hydrological phenomena using simpler hydrological models requires less computing power and input data compared to the more complex models. Ordinarily, a more complex, white-box model would be expected to have better predictive capabilit...
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Jiaqi Yu, Wen-Shao Chang and Yu Dong
Building energy usage has been an important issue in recent decades, and energy prediction models are important tools for analysing this problem. This study provides a comprehensive review of building energy prediction models and uncertainties in the mod...
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Vasilis Bellos, Ioannis Kourtis, Eirini Raptaki, Spyros Handrinos, John Kalogiros, Ioannis A. Sibetheros and Vassilios A. Tsihrintzis
The present work deals with the reconstruction of the flood wave that hit Mandra town (Athens, Greece) on 15 November 2017, using the framework of forensic hydrology. The flash flood event was caused by a huge storm event with a high level of spatial and...
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Zhi Yung Tay, Januwar Hadi, Favian Chow, De Jin Loh and Dimitrios Konovessis
The global greenhouse gas emitted from shipping activities is one of the factors contributing to global warming; thus, there is an urgent need to mitigate the adverse effect of climate change. One of the key strategies is to build a vibrant maritime indu...
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Emmanuel Pintelas, Ioannis E. Livieris and Panagiotis Pintelas
Machine learning has emerged as a key factor in many technological and scientific advances and applications. Much research has been devoted to developing high performance machine learning models, which are able to make very accurate predictions and decis...
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Rajan Gill and Raffaello D?Andrea
Two low-order, parametric models are developed for the forces and moments that a rotating propeller undergoes in forward flight. The models are derived using a first-principles-based approach, and are computationally efficient in the sense of being repre...
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