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SAE technical paper series, Volume 930861.
.... This paper describes how a neural network approach can be used as a cheap... 
Computer simulation | Diagnostics | Neural networks | Data acquisition and handling | Marine engines | Artificial intelligence
eJournal
2002, The electrical engineering and applied signal processing series, ISBN 0849323592, 1 v. (various pagings)
Book
Expert systems with applications, ISSN 0957-4174, 2010, Volume 37, Issue 1, pp. 479 - 489
Artificial neural networks (ANNs) are flexible computing frameworks and universal approximators that can be applied to a wide range of time series forecasting problems with a high degree of accuracy... 
Time series forecasting | Auto-regressive integrated moving average (ARIMA) | Artificial neural networks (ANNs) | ENSEMBLE | REGRESSION | MARKET | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | GENETIC ALGORITHMS | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | ARIMA | CYCLES | TIME-SERIES | ARCHITECTURE | ARMA | SELECTION | Neural networks | Analysis
Journal Article
International journal of quantum information, ISSN 0219-7499, 12/2018, Volume 16, Issue 8
It was recently proposed to leverage the representational power of artificial neural networks, in particular Restricted Boltzmann Machines, in order to model complex quantum states of many-body systems [G. Carleo and M... 
quantum many-body states | Boltzmann machines | Machine learning | COMPUTER SCIENCE, THEORY & METHODS | PHYSICS, MATHEMATICAL | PHYSICS, PARTICLES & FIELDS | Physics - Quantum Physics
Journal Article
Journal of thermal analysis and calorimetry, ISSN 1588-2926, 2016, Volume 126, Issue 2, pp. 837 - 843
The main purpose of this research was to investigate the efficiency of artificial neural networks in modeling thermal conductivity data of water–EG (40–60... 
Polymer Sciences | Chemistry | Analytical Chemistry | Measurement Science and Instrumentation | Physical Chemistry | Nanofluid | Thermal conductivity | Inorganic Chemistry | Artificial neural network | Thermophysical properties | FE3O4 NANOFLUID | CHEMISTRY, ANALYTICAL | HEAT-TRANSFER | INCLUSIONS | TUBES | CHEMISTRY, PHYSICAL | VISCOSITY | MODEL | FLOW | ETHYLENE-GLYCOL | THERMODYNAMICS | TEMPERATURE | AL2O3
Journal Article
Neurocomputing (Amsterdam), ISSN 0925-2312, 2017, Volume 234, pp. 11 - 26
Journal Article
SAE technical paper series, Volume 2007-01-4264.
This paper describes the application and capability of neural network as an artificial intelligence tool to determine the performance and emissions in a compressed natural gas direct injection (CNG-DI) engine... 
Neural networks | Simulation and modeling | Fuel injection | Artificial intelligence | Natural gas
eJournal
SAE technical paper series, Volume 2007-01-4101.
This paper describes the applicable and capability of neural network as an artificial intelligence tool to determine the performance and emissions in a compressed natural gas direct injection (CNG-DI) engine... 
Diesel exhaust emissions | Diesel / Compression Ignition engines | Performance tests | Computational fluid dynamics | Simulation and modeling | Compressed natural gas | Spark ignition engines | Neural networks | Single cylinder engines | Mathematical models | Fuel injection | Artificial intelligence | Alternative fuels
eJournal
Neural networks, ISSN 0893-6080, 2019, Volume 116, pp. 279 - 287
Convolutional neural networks with strong representation ability of deep structures have ever increasing popularity in many research areas... 
Deep learning | Pattern recognition | Convolutional neural networks | Convolution techniques | Machine learning | Image classification | NEUROSCIENCES | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Algorithms | Neural networks | Analysis
Journal Article
Neurocomputing (Amsterdam), ISSN 0925-2312, 01/2018, Volume 273, pp. 281 - 295
It is reported a continuous-time neural network in CMOS that uses memristors. These nanodevices are used to achieve some analog functions such as constant current sourcing, decaying term emulation, and resistive connection... 
Memristor | Neural network | Hopfield | Continuous-time signal | Analog VLSI design | Team model | DESIGN | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Very-large-scale integration | Neural circuitry | Convergence (Social sciences) | Neural networks | Analysis | Complementary metal oxide semiconductors | Electrical engineering | Titanium dioxide
Journal Article