Matches in SemOpenAlex for { <https://semopenalex.org/work/W1992003809> ?p ?o ?g. }
Showing items 1 to 64 of
64
with 100 items per page.
- W1992003809 abstract "Feed-Forward Neural Networks have shown to be a useful tool for the automatic classification of events in High Energy Physics. A shortcoming of the method is anyway given by the large value of simulated events to be used for training the classifier. In this paper, we describe an alternative Neural Network architecture that allows a substantial reduction of the CPU time spent in the training phase. This architecture has been tested on a complex problem, such as the classification of the hadronic decays of the Z0, and its performance has been compared with that of a Feed-Forward Neural Network." @default.
- W1992003809 created "2016-06-24" @default.
- W1992003809 creator A5053210927 @default.
- W1992003809 creator A5091454672 @default.
- W1992003809 date "1993-10-01" @default.
- W1992003809 modified "2023-09-24" @default.
- W1992003809 title "A HYBRID NEURAL NETWORK ARCHITECTURE FOR THE CLASSIFICATION OF THE HADRONIC DECAYS OF THE Z0" @default.
- W1992003809 doi "https://doi.org/10.1142/s0129183193000756" @default.
- W1992003809 hasPublicationYear "1993" @default.
- W1992003809 type Work @default.
- W1992003809 sameAs 1992003809 @default.
- W1992003809 citedByCount "0" @default.
- W1992003809 crossrefType "journal-article" @default.
- W1992003809 hasAuthorship W1992003809A5053210927 @default.
- W1992003809 hasAuthorship W1992003809A5091454672 @default.
- W1992003809 hasConcept C109214941 @default.
- W1992003809 hasConcept C119857082 @default.
- W1992003809 hasConcept C121332964 @default.
- W1992003809 hasConcept C123657996 @default.
- W1992003809 hasConcept C142362112 @default.
- W1992003809 hasConcept C153349607 @default.
- W1992003809 hasConcept C154945302 @default.
- W1992003809 hasConcept C19694890 @default.
- W1992003809 hasConcept C41008148 @default.
- W1992003809 hasConcept C50644808 @default.
- W1992003809 hasConcept C95623464 @default.
- W1992003809 hasConceptScore W1992003809C109214941 @default.
- W1992003809 hasConceptScore W1992003809C119857082 @default.
- W1992003809 hasConceptScore W1992003809C121332964 @default.
- W1992003809 hasConceptScore W1992003809C123657996 @default.
- W1992003809 hasConceptScore W1992003809C142362112 @default.
- W1992003809 hasConceptScore W1992003809C153349607 @default.
- W1992003809 hasConceptScore W1992003809C154945302 @default.
- W1992003809 hasConceptScore W1992003809C19694890 @default.
- W1992003809 hasConceptScore W1992003809C41008148 @default.
- W1992003809 hasConceptScore W1992003809C50644808 @default.
- W1992003809 hasConceptScore W1992003809C95623464 @default.
- W1992003809 hasLocation W19920038091 @default.
- W1992003809 hasOpenAccess W1992003809 @default.
- W1992003809 hasPrimaryLocation W19920038091 @default.
- W1992003809 hasRelatedWork W1935095018 @default.
- W1992003809 hasRelatedWork W2003817407 @default.
- W1992003809 hasRelatedWork W2035274986 @default.
- W1992003809 hasRelatedWork W2066354724 @default.
- W1992003809 hasRelatedWork W2120299300 @default.
- W1992003809 hasRelatedWork W2125226930 @default.
- W1992003809 hasRelatedWork W2128777882 @default.
- W1992003809 hasRelatedWork W2130585864 @default.
- W1992003809 hasRelatedWork W2162974126 @default.
- W1992003809 hasRelatedWork W2165421663 @default.
- W1992003809 hasRelatedWork W2167191594 @default.
- W1992003809 hasRelatedWork W2360526047 @default.
- W1992003809 hasRelatedWork W2363542937 @default.
- W1992003809 hasRelatedWork W2370728731 @default.
- W1992003809 hasRelatedWork W2493224314 @default.
- W1992003809 hasRelatedWork W2611888800 @default.
- W1992003809 hasRelatedWork W3008638874 @default.
- W1992003809 hasRelatedWork W3016866710 @default.
- W1992003809 hasRelatedWork W84607321 @default.
- W1992003809 hasRelatedWork W92921645 @default.
- W1992003809 isParatext "false" @default.
- W1992003809 isRetracted "false" @default.
- W1992003809 magId "1992003809" @default.
- W1992003809 workType "article" @default.