Results 21 to 30 of about 162,584 (247)
Intuitionistic fuzzy neural network with filtering functions. An index matrix interpretation [PDF]
Notes on IFS, 2023 Biological neurons and their connection in neural networks have motivated the creation of the architecture of artificial neural networks. In the previously considered cases, the description of the neural networks and their connections are described with ...
Sotir Sotirov +3 more
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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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This chapter contains a description of the historical evolution of artificial neural networks since their inception, with the appearance of the first relevant learning method by Paul Werbos in 1986, which remained ignored until it was discovered simultaneously by three groups of independent researchers: LeCun (1986); Parker (1985); and Rumelhart ...
Paulo Botelho Pires +2 more
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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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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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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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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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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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SHS Web of Conferences, 2018 In the work performed adaptation of artificial neural networks in modern security systems potentially dangerous technical objects — high-rise buildings as tools for assessing and forecasting in management decision.
Peganov Nikolay +2 more
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