Results 21 to 30 of about 2,288,742 (339)

Validation of the usefulness of artificial neural networks for risk prediction of adverse drug reactions used for individual patients in clinical practice.

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, Yoh Takekuma, Hitoshi Kashiwagi, Takayuki Miyai, Masaki Kobayashi, Ken Iseki, Mitsuru Sugawara   +6 more
doaj   +1 more source

Prediction of Ultimate Bearing Capacity of Skirted Footing Resting on Sand Using Artificial Neural Networks [PDF]

Journal of Soft Computing in Civil Engineering, 2018
The paper presents the prediction of ultimate bearing capacity of different regular shaped skirted footing resting on sand using artificial neural network.
Rakesh Dutta, Radha Rani, Tammineni Gnananandarao   +2 more
doaj   +1 more source

Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?

bioRxiv, 2018
The internal representations of early deep artificial neural networks (ANNs) were found to be remarkably similar to the internal neural representations measured experimentally in the primate brain.
Martin Schrimpf, J. Kubilius, Ha Hong, N. Majaj, R. Rajalingham, Elias B. Issa, Kohitij Kar, P. Bashivan, Jonathan Prescott-Roy, Kailyn Schmidt, Daniel Yamins, J. DiCarlo   +11 more
semanticscholar   +1 more source

Artificial Neural Network Methods for the Solution of Second Order Boundary Value Problems

Computers Materials & Continua, 2019
: We present a method for solving partial differential equations using artificial neural networks and an adaptive collocation strategy. In this procedure, a coarse grid of training points is used at the initial training stages, while more points are ...
C. Anitescu, E. Atroshchenko, N. Alajlan, T. Rabczuk   +3 more
semanticscholar   +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., Pavlović R., Milošević D., Đorđević B., Ranđić S., Stojić D.   +5 more
doaj   +1 more source

Artificial Neural Network in Cosmic Landscape [PDF]

, 2017
In this paper we propose that artificial neural network, the basis of machine learning, is useful to generate the inflationary landscape from a cosmological point of view.
Liu, Junyu
core   +3 more sources

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, Ajay Singh, Tammineni Gnananandarao   +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, Yikun Liu, Decai Lin, Guohui Qu, Jiqiang Zhi, Shuang Liang, Fengjiao Wang, Dukui Zheng, Anqi Shen, Lifeng Bo, Shiwei Zhu   +10 more
doaj   +1 more source

The High Time Resolution Universe Survey VI: An Artificial Neural Network and Timing of 75 Pulsars [PDF]

, 2012
We present 75 pulsars discovered in the mid-latitude portion of the High Time Resolution Universe survey, 54 of which have full timing solutions. All the pulsars have spin periods greater than 100 ms, and none of those with timing solutions are in ...
A Jameson, A Lyne, A Possenti, Abdo, B R Barsdell, B Stappers, Bailes, Bates, Bhat, Bishop, Boyles, Burke-Spolaor, C Ng, C Nietner, Camilo, Cognard, Cordes, D J Champion, D Thornton, Eatough, Eatough, Edwards, Espinoza, Faucher-Giguère, Faucher-Giguère, Ferdman, Hobbs, Hobbs, Jenet, Keane, Keith, Keith, Keith, Keith, Kramer, Kramer, Kramer, L Levin, Levin, Looney, Lorimer, Lyne, Lyne, Lyne, M Bailes, M Burgay, M J Keith, M Kramer, Manchester, Manchester, McLaughlin, N D R Bhat, N D'Amico, O'Brien, P Coster, Ransom, Ray, Ridley, Rosen, S Burke-Spolaor, S D Bates, S Johnston, S Milia, Smits, Stappers, Taylor, van Leeuwen, W van Straten, Weltevrede, Weltevrede   +69 more
core   +5 more sources

Neural Network Applications [PDF]

, 1995
Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in ...
Jain, L.C., Veelenturf, L.P.J., Vonk, E.
core   +3 more sources