Results 21 to 30 of about 2,398,861 (301)
Application of Artificial Neural Network to Search for Gravitational-Wave Signals Associated with Short Gamma-Ray Bursts [PDF]
, 2015 We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts.
Harry, Ian W. +8 more
core +3 more sources
PLoS ONE, 2020 Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their usefulness in medicine.
Shungo Imai +6 more
doaj +1 more source
Classification of asteroid families with artificial neural networks [PDF]
Serbian Astronomical Journal, 2020 This paper describes an artificial neural network for classification of asteroids into families. The data used for artificial neural network training and testing were obtained by the Hierarchical Clustering Method (HCM).
Vujičić D. +5 more
doaj +1 more source
Prediction of Free Swell Index for the Expansive Soil Using Artificial Neural Networks [PDF]
Journal of Soft Computing in Civil Engineering, 2019 Prediction of the free swell index of the expansive soil using artificial neural network has been presented in this paper. Input parameters for the artificial neural network model were plasticity index and shrinkage index, while the output was the free ...
Rakesh Dutta +2 more
doaj +1 more source
Artificial Neural Network Systems
, 2021 Artificial Neural Networks is a calculation method that builds several processing units based on interconnected connections. The network consists of an arbitrary number of cells or nodes or units or neurons that connect the input set to the output. It is a part of a computer system that mimics how the human brain analyzes and processes data.
Dastres, Roza, Soori, Mohsen
openaire +4 more sources
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
openaire +6 more sources
Analysis of Artificial Neural-Network [PDF]
International Journal of Trend in Scientific Research and Development, 2018 An Artificial Neural Network ANN is a computational model that is inspired by the way biological neural networks in the human brain process information. Artificial Neural Networks have generated a lot of excitement in Machine Learning research and industry, thanks to many breakthrough results in speech recognition, computer vision and text processing ...
Rajesh CVS, Nadikoppula Pardhasaradhi
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Pricing American Put Option using RBF-NN: New Simulation of Black-Scholes
Moroccan Journal of Pure and Applied Analysis, 2022 The present work proposes an Artificial Neural Network framework for calculating the price and delta hedging of American put option. We consider a sequence of Radial Basis function Neural Network, where each network learns the difference of the price ...
Zaineb El Kharrazi +2 more
doaj +1 more source
Research Progress of Oilfield Development Index Prediction Based on Artificial Neural Networks
Energies, 2021 Accurately predicting oilfield development indicators (such as oil production, liquid production, current formation pressure, water cut, oil production rate, recovery rate, cost, profit, etc.) is to realize the rational and scientific development of ...
Chenglong Chen +10 more
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Optimal Artificial Neural Network Type Selection Method for Usage in Smart House Systems
Sensors, 2020 In the process of the “smart” house systems work, there is a need to process fuzzy input data. The models based on the artificial neural networks are used to process fuzzy input data from the sensors. However, each artificial neural network has a certain
Vasyl Teslyuk +3 more
doaj +1 more source