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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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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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Growing Artificial Neural Networks [PDF]
, 2021 14 pages, Accepted for publication in Springer Nature - Book Series: Transactions on Computational Science and Computational Intelligence, Advances in Artificial Intelligence and Applied Cognitive Computing - Springer ID: 89066307 (Book ID: 495585_1_En)
John Mixter, Ali Akoglu
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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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Artificial Neural Networks as Decision Support Tools in Cytopathology: Past, Present, and Future
Biomedical Engineering and Computational Biology, 2016 Abraham Pouliakis +2 more
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Artificial nonmonotonic neural networks
Artificial Intelligence, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Basilis Boutsinas, Michael N. Vrahatis
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Neural Networks as Artificial Specifications [PDF]
, 2018 In theory, a neural network can be trained to act as an artificial specification for a program by showing it samples of the programs executions. In practice, the training turns out to be very hard. Programs often operate on discrete domains for which patterns are difficult to discern. Earlier experiments reported too much false positives.
I. S. Wishnu B. Prasetya, Minh An Tran
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TRAINING OF ARTIFICIAL NEURAL NETWORK
Journal of Numerical and Applied Mathematics, 2021 The methodology of neural networks is even more often applied in tasks of management and decision-making, including in the sphere of trade and finance. The basis of neural networks is made by nonlinear adaptive systems which proved the efficiency at the solution of problems of forecasting.
I. Sh. Didmanidze +2 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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Artificial neural networks for neuroscientists: a primer [PDF]
Neuron, 2020 Artificial neural networks (ANNs) are essential tools in machine learning that have drawn increasing attention in neuroscience. Besides offering powerful techniques for data analysis, ANNs provide a new approach for neuroscientists to build models for complex behaviors, heterogeneous neural activity and circuit connectivity, as well as to explore ...
Guangyu Robert Yang, Xiao-Jing Wang
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