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Ioannis E. Livieris
During the last few decades, machine learning has constituted a significant tool in extracting useful knowledge from economic data for assisting decision-making. In this work, we evaluate the performance of weight-constrained recurrent neural networks in...
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Jacek Rapinski and Artur Janowski
Modern Global Navigation Satellite Systems (GNSS) allow for positioning with accuracies ranging from tens of meters to single millimeters depending on user requirements and available equipment. A major disadvantage of these systems is their unavailabilit...
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Ioannis E. Livieris
In this work, a new approach for training artificial neural networks is presented which utilises techniques for solving the constraint optimisation problem. More specifically, this study converts the training of a neural network into a constraint optimis...
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Iman Rahimi, Amir H. Gandomi, Panagiotis G. Asteris and Fang Chen
The novel coronavirus disease, also known as COVID-19, is a disease outbreak that was first identified in Wuhan, a Central Chinese city. In this report, a short analysis focusing on Australia, Italy, and UK is conducted. The analysis includes confirmed a...
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S. Indrapriyadarsini, Shahrzad Mahboubi, Hiroshi Ninomiya, Takeshi Kamio and Hideki Asai
Gradient-based methods are popularly used in training neural networks and can be broadly categorized into first and second order methods. Second order methods have shown to have better convergence compared to first order methods, especially in solving hi...
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T.A. Osipova,K.S. Zaytsev,V.O. Bifert
Pág. 23 - 29
Today there is a significant increase in the number of incidents involving the use of plastic cards, as well as a variety of fraudulent methods used by cybercriminals. The presented article is devoted to the application of machine learning methods to cou...
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T.A. Osipova,K.S. Zaytsev,V.O. Bifert
Pág. 23 - 29
Today there is a significant increase in the number of incidents involving the use of plastic cards, as well as a variety of fraudulent methods used by cybercriminals. The presented article is devoted to the application of machine learning methods to cou...
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Mahsa Yousefi and Ángeles Martínez
While first-order methods are popular for solving optimization problems arising in deep learning, they come with some acute deficiencies. To overcome these shortcomings, there has been recent interest in introducing second-order information through quasi...
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Yaru Li, Yulai Zhang and Yongping Cai
The selection of the hyper-parameters plays a critical role in the task of prediction based on the recurrent neural networks (RNN). Traditionally, the hyper-parameters of the machine learning models are selected by simulations as well as human experience...
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Veysel Akyuncu,Mucteba Uysal,Harun Tanyildizi,Mansur Sumer
Pág. 337 - 353
This paper presents the modeling of an experimental investigation carried out to evaluate some mechanical and durability properties of concrete mixtures in which cement was partially replaced with Class C and Class F fly ash. A total of 39 mixtures with ...
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Evangelos D. Spyrou, Chrysostomos Stylios and Ioannis Tsoulos
Air pollution is a pressing concern in urban areas, necessitating the critical monitoring of air quality to understand its implications for public health. Internet of Things (IoT) devices are widely utilized in air pollution monitoring due to their senso...
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Fahad Ahmed, Ho Huu Loc, Edward Park, Muhammad Hassan and Panuwat Joyklad
Floods are among the major natural disasters that cause loss of life and economic damage worldwide. Floods damage homes, crops, roads, and basic infrastructure, forcing people to migrate from high flood-risk areas. However, due to a lack of information a...
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Panagiotis Oikonomou and Stylianos Pappas
In this paper a microscopic, non-discrete, mathematical model based on stigmergy for predicting the nodal aggregation dynamics of decentralized, autonomous robotic swarms is proposed. The model departs from conventional applications of stigmergy in bioin...
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Ismael Sanchez Torreguitart, Tom Verstraete and Lasse Mueller
The LS89 high pressure axial turbine vane was originally designed and optimized for a downstream isentropic Mach number of 0.9. This profile has been widely used for computational fluid dynamics (CFD) validation in the open literature but very few attemp...
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Xiaoqing Wei, Nianping Li, Jinqing Peng, Jianlin Cheng, Jinhua Hu and Meng Wang
To minimize the total energy consumption of a cooling tower-assisted heat pump (CTAHP) system in cooling mode, a model-based control strategy with hybrid optimization algorithm for the system is presented in this paper. An existing experimental device, w...
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