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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2
Pattern Matching in High Energy Physics by Using Neural Network and Genetic Algorithm
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
| ASCII Text | x | ||
| Marcello Castellano, Giuseppe Mastronardi, Vitoantonio Bevilacqua, E. Nappi, "Pattern Matching in High Energy Physics by Using Neural Network and Genetic Algorithm," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 2, pp. 2159, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000. | |||
| BibTex | x | ||
| @article{ 10.1109/IJCNN.2000.857891, author = {Marcello Castellano and Giuseppe Mastronardi and Vitoantonio Bevilacqua and E. Nappi}, title = {Pattern Matching in High Energy Physics by Using Neural Network and Genetic Algorithm}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {2}, year = {2000}, issn = {1098-7576}, pages = {2159}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857891}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - Pattern Matching in High Energy Physics by Using Neural Network and Genetic Algorithm SN - 1098-7576 SP EP A1 - Marcello Castellano, A1 - Giuseppe Mastronardi, A1 - Vitoantonio Bevilacqua, A1 - E. Nappi, PY - 2000 KW - neural network KW - genetic algorithms KW - pattern recognition KW - high energy physics VL - 2 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER - | |||
In this paper, two different approaches to provide information from events by high-energy physics experiments are shown. Usually the representations produced in such experiments are spot-composed and the classical algorithms to be needed for data analysis are time consuming. For this reason the possibility to speed up pattern recognition tasks by soft computing approach with parallel algorithms has been investigated. The first scheme shown in the following is a two layer neural network with forward connections; the second one consists of an evolutionary algorithm with elitistic strategy and mutation and crossover adaptive probability. Test results of these approaches have been carried out analyzing a set of images produced by an optical Ring imaging Cherenkov (RICH) detector at CERN.
Index Terms:
neural network, genetic algorithms, pattern recognition, high energy physics
Citation:
Marcello Castellano, Giuseppe Mastronardi, Vitoantonio Bevilacqua, E. Nappi, "Pattern Matching in High Energy Physics by Using Neural Network and Genetic Algorithm," ijcnn, vol. 2, pp.2159, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000
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