Results 41 to 50 of about 275,127 (313)
Deferring the learning for better generalization in radial basis neural networks [PDF]
, 2001 Proceeding of: International Conference Artificial Neural Networks — ICANN 2001. Vienna, Austria, August 21–25, 2001The level of generalization of neural networks is heavily dependent on the quality of the training data.
Galván, Inés M. +5 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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Review and Analysis of the Development of Artificial Neural Networks
Кібернетика та комп'ютерні технології, 2023 Introduction. The creation of intelligent cyber-physical systems is impossible without knowledge of the analysis and process of development of scientific thought regarding artificial neural networks. The main task of this article is research and analysis
Oleksandr Bilokon
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Dead-end filtration of yeast suspensions: correlating specific resistance and flux data using artificial neural networks [PDF]
, 2006 The specific cake resistance in dead-end filtration is a complex function of suspension properties and operating conditions. In this study, the specific resistance of resuspended dried bakers yeast suspensions was measured in a series of 150 experiments ...
Ní Mhurchú, Jenny, Foley, Greg
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Nature Communications, 2018 Artificial neural networks are artificial intelligence computing methods which are inspired by biological neural networks. Here the authors propose a method to design neural networks as sparse scale-free networks, which leads to a reduction in ...
Decebal Constantin Mocanu +5 more
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Evolutionary Artificial Neural Networks in Neutron Spectrometry [PDF]
, 2010 Artificial Neural Networks (ANN), are highly simplified models of the brain processes (Graupe, 2007; Kasabov, 1998). AnANNis a biologically inspired computational model which consists of a large number of simple processing elements called neurons ...
Vega Carrillo, Héctor René +2 more
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THE INTELLIGENT SYSTEM FOR AUTOMOTIVE FUELS QUALITY DEFINITION
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2013 An intelligent system, based on hydrodynamic method and artificial neural networks usage for automotive fuels quality definition have been developed. Artificial neural networks optimal structures for the octane number of gasoline, cetane number, cetane ...
Volodymyr Drevetskiy , Marko Klepach
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Artificial Neural Networks in Agriculture [PDF]
, 2021 Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production.
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Observational Cosmology with Artificial Neural Networks
Universe, 2022 In cosmology, the analysis of observational evidence is very important when testing theoretical models of the Universe. Artificial neural networks are powerful and versatile computational tools for data modelling and have recently been considered in the ...
Juan de Dios Rojas Olvera +2 more
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Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source