scholarly journals Application of Artificial Neural Networks and Hybrid Methods in the Solution of Inverse Problems

10.5772/16064 ◽  
2011 ◽  
Author(s):  
Jader Lugon ◽  
Antonio J. da Silva Neto ◽  
Luiz Biondi ◽  
Francisco Jose da Cunha Pires Soeiro ◽  
Cesar Costapinto ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Inverse Problems ◽  
Hybrid Methods ◽  
Artificial Neural

scholarly journals Artificial Neural Networks and Human Brain: Survey of Improvement Possibilities of Learning

2015 ◽  
Vol 3 ◽  
pp. 228 ◽  
Author(s):  
Aleksejs Zorins ◽  
Peteris Grabusts
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Human Brain ◽  
Network Topology ◽  
Hybrid Methods ◽  
Learning Algorithms ◽  
Real Life ◽  
Real Problem ◽  
Brain Functions ◽  
Artificial Neural

<p class="R-AbstractKeywords">There are numerous applications of Artificial Neural Networks (ANN) at the present time and there are different learning algorithms, topologies, hybrid methods etc. It is strongly believed that ANN is built using human brain’s functioning principles but still ANN is very primitive and tricky way for real problem solving. In the recent years modern neurophysiology advanced to a big extent in understanding human brain functions and structure, however, there is a lack of this knowledge application to real ANN learning algorithms. Each learning algorithm and each network topology should be carefully developed to solve more or less complex problem in real life. One may say that almost each serious application requires its own network topology, algorithm and data pre-processing. This article presents a survey of several ways to improve ANN learning possibilities according to human brain structure and functioning, especially one example of this concept – neuroplasticity – automatic adaptation of ANN topology to problem domain.</p>

New opportunities in solution of inverse problems in laser spectroscopy due to application of artificial neural networks

2002 ◽  
Author(s):  
I. V. Gerdova ◽  
I. V. Churina ◽  
S. A. Dolenko ◽  
Tatiana A. Dolenko ◽  
Viktor V. Fadeev ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Inverse Problems ◽  
Laser Spectroscopy ◽  
Artificial Neural

Inverse problems using Artificial Neural Networks in long range atmospheric dispersion

Kerntechnik ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. 115-120
Author(s):  
P. K. Sharma ◽  
B. Gera ◽  
A. K. Ghosh
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Inverse Problems ◽  
Long Range ◽  
Atmospheric Dispersion ◽  
Artificial Neural

Improvement of Sievert Integration Model in brachytherapy via inverse problems and Artificial Neural Networks

2019 ◽  
Vol 155 ◽  
pp. 260-264
Author(s):  
Eriberto O. do Nascimento ◽  
Lucas N. de Oliveira ◽  
Linda V.E. Caldas
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Inverse Problems ◽  
Integration Model ◽  
Artificial Neural
Sign in / Sign up

Export Citation Format

Share Document