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Oleg Sova,Oleksandr Turinskyi,Andrii Shyshatskyi,Volodymyr Dudnyk,Ruslan Zhyvotovskyi,Yevgen Prokopenko,Taras Hurskyi,Valerii Hordiichuk,Anton Nikitenko,Artem Remez
Pág. 46 - 55
The algorithm to train artificial neural networks for intelligent decision support systems has been constructed. A distinctive feature of the proposed algorithm is that it conducts training not only for synaptic weights of an artificial neural network, b...
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Sergey Shchanikov, Ilya Bordanov, Alexey Kucherik, Evgeny Gryaznov and Alexey Mikhaylov
Arrays of memristive devices coupled with photosensors can be used for capturing and processing visual information, thereby realizing the concept of ?in-sensor computing?. This is a promising concept associated with the development of compact and low-pow...
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Oleg Sova,Andrii Shyshatskyi,Yurii Zhuravskyi,Olha Salnikova,Oleksandr Zubov,Ruslan Zhyvotovskyi,?gor Romanenko,Yevhen Kalashnikov,Artem Shulhin,Alexander Simonenko
Pág. 6 - 14
The method of training artificial neural networks for intelligent decision support systems is developed. A distinctive feature of the proposed method is that it provides training not only of the synaptic weights of the artificial neural network, but also...
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Mohamed Shaban
Parkinson?s disease (PD) is a serious movement disorder that may eventually progress to mild cognitive dysfunction (MCI) and dementia. According to the Parkinson?s foundation, one million Americans were diagnosed with PD and almost 10 million individuals...
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Vladislav Kholkin, Olga Druzhina, Valerii Vatnik, Maksim Kulagin, Timur Karimov and Denis Butusov
For the last two decades, artificial neural networks (ANNs) of the third generation, also known as spiking neural networks (SNN), have remained a subject of interest for researchers. A significant difficulty for the practical application of SNNs is their...
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Ioannis G. Tsoulos and Alexandros Tzallas
Perhaps one of the best-known machine learning models is the artificial neural network, where a number of parameters must be adjusted to learn a wide range of practical problems from areas such as physics, chemistry, medicine, etc. Such problems can be r...
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Yunlong Zhang, Dongsheng Du, Sheng Shi, Weiwei Li and Shuguang Wang
The intensity non-stationarity is one of the basic characteristics of ground motions, the influences of which on the dynamic responses of structures is a pressing issue in the field of earthquake engineering. The BP neural network modified by the genetic...
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Diego Mellado, Carolina Saavedra, Steren Chabert, Romina Torres and Rodrigo Salas
Deep learning models are part of the family of artificial neural networks and, as such, they suffer catastrophic interference when learning sequentially. In addition, the greater number of these models have a rigid architecture which prevents the increme...
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Dthenifer Cordeiro Santana, Gustavo de Faria Theodoro, Ricardo Gava, João Lucas Gouveia de Oliveira, Larissa Pereira Ribeiro Teodoro, Izabela Cristina de Oliveira, Fábio Henrique Rojo Baio, Carlos Antonio da Silva Junior, Job Teixeira de Oliveira and Paulo Eduardo Teodoro
Using multispectral sensors attached to unmanned aerial vehicles (UAVs) can assist in the collection of morphological and physiological information from several crops. This approach, also known as high-throughput phenotyping, combined with data processin...
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Chiou-Yann Lee, Chun-Ru Wen and Binh Thi-Thanh-Nguyen
This study presents a novel financial performance forecasting method that combines the threshold technique with Artificial Neural Networks (ANN). It applies the threshold regression method to identify the factors within the board of directors that influe...
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Stanislav Letkovský, Sylvia Jencová and Petra Va?anicová
Predicting bankruptcy within selected industries is crucial because of the potential ripple effects and unique characteristics of those industries. It serves as a risk management tool, guiding various stakeholders in making decisions. While artificial in...
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Luana Centorame, Thomas Gasperini, Alessio Ilari, Andrea Del Gatto and Ester Foppa Pedretti
Machine learning is a widespread technology that plays a crucial role in digitalisation and aims to explore rules and patterns in large datasets to autonomously solve non-linear problems, taking advantage of multiple source data. Due to its versatility, ...
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Daniel Einarson, Fredrik Frisk, Kamilla Klonowska and Charlotte Sennersten
Machine learning (ML) is increasingly used in diverse fields, including animal behavior research. However, its application to ambiguous data requires careful consideration to avoid uncritical interpretations. This paper extends prior research on ringed m...
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Dimitris Papadopoulos and Vangelis D. Karalis
Sample size is a key factor in bioequivalence and clinical trials. An appropriately large sample is necessary to gain valuable insights into a designated population. However, large sample sizes lead to increased human exposure, costs, and a longer time f...
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Tomasz Gajewski and Pawel Skiba
The main goal of this work is to combine the usage of the numerical homogenization technique for determining the effective properties of representative volume elements with artificial neural networks. The effective properties are defined according to the...
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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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Íñigo Manuel Iglesias-Sanfeliz Cubero, Andrés Meana-Fernández, Juan Carlos Ríos-Fernández, Thomas Ackermann and Antonio José Gutiérrez-Trashorras
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Sachin Gowda, Vaishakh Kunjar, Aakash Gupta, Govindaswamy Kavitha, Bishnu Kant Shukla and Parveen Sihag
In the realm of urban geotechnical infrastructure development, accurate estimation of the California Bearing Ratio (CBR), a key indicator of the strength of unbound granular material and subgrade soil, is paramount for pavement design. Traditional labora...
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Laura Guimarães, António Paulo Carvalho, Pedro Ribeiro, Cláudia Teixeira, Nuno Silva, André Pereira, João Amorim and Luís Oliva-Teles
Triops longicaudatus is a crustacean typically inhabiting temporary freshwater bodies in regions with a Mediterranean climate. These crustaceans are easily maintained in the laboratory and show a set of biological features that make them good candidates ...
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Sipho G. Thango, Georgios A. Drosopoulos, Siphesihle M. Motsa and Georgios E. Stavroulakis
A methodology to predict key aspects of the structural response of masonry walls under blast loading using artificial neural networks (ANN) is presented in this paper. The failure patterns of masonry walls due to in and out-of-plane loading are complex d...
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