Identifying Learning Standards of Artificial Neural Networks: A Study

Learning Standards ◽

Determination of S-N curves with the application of artificial neural networks

Fatigue & Fracture of Engineering Materials & Structures ◽

10.1046/j.1460-2695.1999.00198.x ◽

1999 ◽

Vol 22 (8) ◽

pp. 723-728 ◽

Cited By ~ 1

Author(s):

Artymiak ◽

Bukowski ◽

Feliks ◽

Narberhaus ◽

Zenner

Keyword(s):

Neural Networks ◽

Applications of artificial neural networks to adaptive training systems.

PsycEXTRA Dataset ◽

10.1037/e456072004-001 ◽

1992 ◽

Author(s):

Peter L. Rothman

Keyword(s):

Neural Networks ◽

Adaptive Training ◽

Training Systems ◽

Use of Artificial Neural Networks for Risk Assessment for Work and Organizational Issues

PsycEXTRA Dataset ◽

10.1037/e666722007-001 ◽

2006 ◽

Author(s):

Maria Karanika ◽

Tom Cox

Keyword(s):

Neural Networks ◽

Risk Assessment ◽

Organizational Issues ◽

Artificial neural networks for diagnosis and prognosis in prostate cancer

Seminars in Urologic Oncology ◽

10.1053/suro.2002.32492 ◽

2002 ◽

Vol 20 (2) ◽

pp. 89-95 ◽

Cited By ~ 35

Author(s):

Guido Schwarzer ◽

Martin Schumacher

Keyword(s):

Prostate Cancer ◽

Neural Networks ◽

Diagnosis And Prognosis ◽

FUTURE OF ARTIFICIAL NEURAL NETWORKS IN SPACE EXPLORATION AND SPACE ENGINEERING

Scientific Review Series 1 Economics and Law ◽

10.33051/2076-4650-2018-6-6-11 ◽

2018 ◽

pp. 6-11

Author(s):

Kobiljon Kh. Zoidov ◽

◽

Svetlana V. Ponomareva ◽

Daniel I. Serebryansky ◽

◽

...

Keyword(s):

Neural Networks ◽

Space Exploration ◽

Differentiation Between Mass-forming Type Peripheral Cholangiocarcinoma and Hepatic Abscesses: Application of Artificial Neural Networks to CT Images

Journal of the Korean Radiological Society ◽

10.3348/jkrs.2005.53.5.343 ◽

2005 ◽

Vol 53 (5) ◽

pp. 343 ◽

Cited By ~ 1

Author(s):

Nak Jong Seong ◽

Jeong Min Lee ◽

Se Hyung Kim ◽

Joon Koo Han ◽

Young Jun Kim ◽

...

Keyword(s):

Neural Networks ◽

Ct Images ◽

Peripheral Cholangiocarcinoma ◽

Физико-технические проблемы разработки полезных ископаемых ◽

A New Model Based on Artificial Neural Networks and Game Theory for the Selection of Underground Mining Method

10.15372/ftprpi20200108 ◽

2020 ◽

Keyword(s):

Neural Networks ◽

Game Theory ◽

Underground Mining ◽

Mining Method ◽

New Model ◽

Model Based ◽

Artificial Neural ◽

Selection Of

Bankruptcy Prediction Models: A Bet on Artificial Neural Networks

Global Journal For Research Analysis ◽

10.15373/22778160/february2014/16 ◽

2012 ◽

Vol 3 (2) ◽

pp. 48-50

Author(s):

Ana Isabel Velasco Fernández ◽

◽

Ricardo José Rejas Muslera ◽

Juan Padilla Fernández-Vega ◽

María Isabel Cepeda González

Keyword(s):

Neural Networks ◽

Prediction Models ◽

Bankruptcy Prediction ◽

On the Use of Function Approximation Potential of Artificial Neural Networks for Predicting Elastic Moduli of Binary Oxide Glass Systems

Global Journal For Research Analysis ◽

10.15373/22778160/february2014/60 ◽

2012 ◽

Vol 3 (2) ◽

pp. 186-189

Author(s):

Dr.R.Sheelarani Dr.R.Sheelarani ◽

◽

Dr. K.T. Arulmozhi Dr. K.T. Arulmozhi

Keyword(s):

Neural Networks ◽

Function Approximation ◽

Elastic Moduli ◽

Binary Oxide ◽

Oxide Glass ◽

Efficient Operation of Wind Turbine with Doubly Fed Induction Generator Using TLBO Algorithm and Artificial Neural Networks

International Review on Modelling and Simulations (IREMOS) ◽

10.15866/iremos.v9i6.10309 ◽

2016 ◽

Vol 9 (6) ◽

pp. 464 ◽

Cited By ~ 1

Author(s):

Mohamed Sadek ◽

Mahmoud Elkholy ◽

Hamed Metwally

Keyword(s):

Neural Networks ◽

Wind Turbine ◽

Induction Generator ◽

Doubly Fed Induction Generator ◽

Efficient Operation ◽

Tlbo Algorithm ◽

Artificial Neural ◽

Doubly Fed