Results 21 to 30 of about 4,712,882 (251)
Mathematics, 2023 When realized on computational devices with finite quantities of memory, feedforward artificial neural networks and the functions they compute cease being abstract mathematical objects and turn into executable programs generating concrete computations ...
Vladimir A. Kulyukin
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Neural Network with Combined Approximation of the Surface of the Response
Наукові вісті Національного технічного університету України "Київський політехнічний інститут", 2018 Background. There are a large number of neural networks that have their advantages and disadvantages, for example, simple, fast and easy to use single-stranded perceptrons are suitable for linear and linearized regression tasks, and more complicated ...
Oleksandra S. Mishchuk +1 more
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Artificial Intelligence to Analyze the Cortical Thickness Through Age
Frontiers in Artificial Intelligence, 2021 In this study, Artificial Intelligence was used to analyze a dataset containing the cortical thickness from 1,100 healthy individuals. This dataset had the cortical thickness from 31 regions in the left hemisphere of the brain as well as from 31 regions ...
Sergio Ledesma +5 more
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Artificial Neural Networks and the Grid [PDF]
, 2004 We introduce a novel system for the usage of neural network resources on a world-wide basis. Our approach employs the upcoming infrastructure of the Grid as a transparent environment to allow users the exchange of information (neural network objects, neural network paradigms) and exploit the available computing resources for neural network specific ...
Erich Schikuta, Thomas Weishäupl
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Advances in Artificial Neural Networks – Methodological Development and Application
Algorithms, 2009 Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other ...
Yanbo Huang
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Adsorption Science & Technology, 2022 The application of artificial neural networks on adsorption modeling has significantly increased during the last decades. These artificial intelligence models have been utilized to correlate and predict kinetics, isotherms, and breakthrough curves of a ...
Hilda Elizabeth Reynel-Ávila +7 more
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Scaling tabular data of training datasets with neural networks
Вісник Харківського національного університету імені В.Н. Каразіна. Серія: Математичне моделювання, інформаційні технології, автоматизовані системи управління, 2023 The paper proposes a method of scaling the tabular data of the training dataset using neural networks, describes the architecture of such networks. Relevance.
Дмитро Узлов +3 more
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Artificial neural networks compared with Bayesian generalized linear regression for leaf rust resistance prediction in Arabica coffee [PDF]
Pesquisa Agropecuária Brasileira, 2017 : The objective of this work was to evaluate the use of artificial neural networks in comparison with Bayesian generalized linear regression to predict leaf rust resistance in Arabica coffee (Coffea arabica).
Gabi Nunes Silva +9 more
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Estimation of soil properties by an artificial neural network
Magazine of Civil Engineering, 2022 Empirical dependencies are often used in various fields of geotechnics and civil engineering. The existing empirical formulas are mainly developed with the use of regression and multiple regression.
Ofrikhter Ian +3 more
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Generative capacities of cellular automata codification for evolution of NN codification [PDF]
, 2002 Proceeding of: International Conference on Artificial Neural Networks. ICANN 2002, Madrid, Spain, August 28-30, 2002Automatic methods for designing artificial neural nets are desired to avoid the laborious and erratically human expert’s job. Evolutionary
Gutiérrez Sánchez, Germán +3 more
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