Application of Neural Networks to Higgs Boson Search

0404924 - UIVT-O 20030051 RIV NL eng J - Článek v odborném periodiku
Hakl, František - Hlaváček, M. - Kalous, R.
Application of Neural Networks to Higgs Boson Search.
Nuclear Instruments & Methods in Physics Research Section A. Roč. 502, - (2003), s. 489-491. ISSN 0168-9002. E-ISSN 1872-9576
Grant CEP: GA MPO RP-4210/69/97
Výzkumný záměr: AV0Z1030915
Klíčová slova: neural networks * Higgs search * genetic optimization
Kód oboru RIV: BA - Obecná matematika
Impakt faktor: 1.166, rok: 2003

This paper describes an application of a neural network approach to SM Higgs search in the top quark decay. A neural network model with a special type of data flow is used to separate background from Higgs events. This neural network combines a classical neural network and linear decision tree. Parameters of these neural networks are randomly generated and a population of predefined size of those networks is trained as an initial generation for a subsequent genetic algorithm optimization.
Trvalý link: http://hdl.handle.net/11104/0125144