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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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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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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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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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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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Short-Term Load Forecasting of Natural Gas with Deep Neural Network Regression [PDF]
, 2018 Deep neural networks are proposed for short-term natural gas load forecasting. Deep learning has proven to be a powerful tool for many classification problems seeing significant use in machine learning fields such as image recognition and speech ...
Brown, Ronald H. +2 more
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Using Artificial Intelligence in Wireless Sensor Routing Protocols [PDF]
, 2006 This paper represents a dissertation about how an artificial intelligence technique can be applied to wireless sensor networks. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically ...
Barbancho Concejero, Antonio +3 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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SIR: A New Wireless Sensor Network Routing Protocol Based on Artificial Intelligence [PDF]
, 2006 Currently, Wireless Sensor Networks (WSNs) are formed by hundreds of low energy and low cost micro-electro-mechanical systems. Routing and low power consumption have become important research issues to interconnect this kind of networks.
Barbancho Concejero, Antonio +3 more
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