Results 41 to 50 of about 273,096 (313)
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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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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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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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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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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Medical imaging analysis with artificial neural networks
, 2010 Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection ...
J. Ren +8 more
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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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Guiding AlphaFold to predict how Munc13‐1 opens Syntaxin‐1
FEBS Open Bio, EarlyView.The syntaxin‐1 Habc‐domain (orange), linker (pink) and SNARE motif (yellow) form a closed conformation that binds to Munc18‐1 (violet) and is opened by the Munc13‐1 MUN domain (cyan) to form the SNARE complex that triggers neurotransmitter release.
Madhurima Chattopadhyay +2 more
wiley +1 more source
Gas-turbine diagnostics using artificial neural-networks for a high bypass ratio military turbofan engine [PDF]
, 2004 The Tristar aircraft, operated by the Royal Air Force, fly many thousands of hours per year in the transport and air-to-air refuelling roles. A large amount of engine data is recorded for each of the Rolls-Royce RB211-524B4 engines: it is used to aid ...
Singh, Riti +3 more
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Artificial neural networks as the data ruling components of future intelligent energy systems
MATEC Web of Conferences, 2017 The main target of this work is to study artificial neural networks and their role in the future intelligent energy systems. Artificial neural networks in the near future will be a very effective tool for data analysis and very perspective for energy ...
Buran Anna, Denisov Maksim
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