A new approach in modeling the response of RPC detectors

The response of RPC detectors is highly sensitive to environmental variables. A novel approach is presented to model the response of RPC detectors in a variety of experimental conditions. The algorithm, based on Artificial Neural Networks, has been developed and tested on the CMS RPC gas gain monito...

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Detalles Bibliográficos
Autores principales: Benussi, L, Bianco, S, Colafranceschi, S, Fabbri, F L, Giardoni, M, Passamonti, L, Piccolo, D, Pierluigi, D, Russo, A, Saviano, G, Buontempo, S, Cimmino, A, de Gruttola, M, Fabozzi, F, Iorio, A O M, Lista, L, Paolucci, P, Baesso, P, Belli, G, Pagano, D, Ratti, S P, Vicini, A, Vitulo, P, Viviani, C, Sharma, A, Bhattacharyya, A K
Lenguaje:eng
Publicado: 2010
Materias:
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1016/j.nima.2010.09.172
http://cds.cern.ch/record/1317992
Descripción
Sumario:The response of RPC detectors is highly sensitive to environmental variables. A novel approach is presented to model the response of RPC detectors in a variety of experimental conditions. The algorithm, based on Artificial Neural Networks, has been developed and tested on the CMS RPC gas gain monitoring system during commissioning.

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