scholarly journals Construction of Optimal Artificial Neural Network Architectures for Application to Chemical Systems: Comparison of Generalized Pattern Search Method and Evolutionary Algorithm

10.5772/15191 ◽  
2011 ◽  
Author(s):  
Matthias Ihme
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Evolutionary Algorithm ◽  
Search Method ◽  
Pattern Search ◽  
Network Architectures ◽  
Chemical Systems ◽  
Pattern Search Method ◽  
Generalized Pattern Search ◽  
Artificial Neural

Pattern Search Method and Artificial Neural Network Prediction of Double Ellipsoid Heat Source of Submerged Arc Welding

2011 ◽  
Vol 201-203 ◽  
pp. 1825-1833 ◽  
Author(s):  
Pei Lin Li ◽  
Hao Lu
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Heat Source ◽  
Source Parameters ◽  
Search Method ◽  
Pattern Search ◽  
Pattern Search Method ◽  
Neural Network Prediction ◽  
Artificial Neural ◽  
The Relationship

For the selection of the double ellipsoid heat source parameters, the thermal cycle of different process was measured and compared with the simulation result. The experimental results were according to the actual conditions and the simulation results were obtained by finite element method. The sensitivity of heat source parameters was discussed. Pattern search method was used to obtain the most accurate parameters corresponding to the specific process. By summarizing all of the processes of experiment, the relationship between the experimental process parameters and the corresponding double ellipsoid heat source parameters was obtained. The artificial neural network algorithm was applied to predict the relationship between all possible process and the double ellipsoid heat source parameters. The verification experiment showed that the prediction model was accurate.

Forecasting Stock Returns with Artificial Neural Networks

2011 ◽  
pp. 47-79 ◽  
Author(s):  
Suraphan Thawornwong ◽  
David Enke
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Stock Returns ◽  
Future Research ◽  
Network Architectures ◽  
Network Applications ◽  
Artificial Neural ◽  
Neural Network Applications

During the last few years there has been growing literature on applications of artificial neural networks to business and financial domains. In fact, a great deal of attention has been placed in the area of stock return forecasting. This is due to the fact that once artificial neural network applications are successful, monetary rewards will be substantial. Many studies have reported promising results in successfully applying various types of artificial neural network architectures for predicting stock returns. This chapter reviews and discusses various neural network research methodologies used in 45 journal articles that attempted to forecast stock returns. Modeling techniques and suggestions from the literature are also compiled and addressed. The results show that artificial neural networks are an emerging and promising computational technology that will continue to be a challenging tool for future research.

scholarly journals Analysis of Artificial Neural Network Architectures for Modeling Smart Lighting Systems for Energy Savings

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 119881-119891 ◽  
Author(s):  
Alberto Garces-Jimenez ◽  
Jose Luis Castillo-Sequera ◽  
Antonio Del Corte-Valiente ◽  
Jose Manuel Gomez-Pulido ◽  
Esteban Patricio Dominguez Gonzalez-Seco
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Energy Savings ◽  
Network Architectures ◽  
Smart Lighting ◽  
Artificial Neural ◽  
Neural Network Architectures ◽  
Lighting Systems
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