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Application of Neural Networks to Higgs Boson Search
- 1.0404924 - UIVT-O 20030051 RIV NL eng J - Journal Article
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
R&D Projects: GA MPO RP-4210/69/97
Institutional research plan: AV0Z1030915
Keywords : neural networks * Higgs search * genetic optimization
Subject RIV: BA - General Mathematics
Impact factor: 1.166, year: 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.
Permanent Link: http://hdl.handle.net/11104/0125144
Number of the records: 1