Quantum-inspired evolutionary classification of driving sequences in vehicle emission factor measurement (Contributo in atti di convegno)

Type
Label
  • Quantum-inspired evolutionary classification of driving sequences in vehicle emission factor measurement (Contributo in atti di convegno) (literal)
Anno
  • 2007-01-01T00:00:00+01:00 (literal)
Alternative label
  • Arpaia P. 1, Meccariello G. 2, Rapone M. 2, Zanesco A. 1 (2007)
    Quantum-inspired evolutionary classification of driving sequences in vehicle emission factor measurement
    in International Measurement Confederation, Iasi (Romania)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Arpaia P. 1, Meccariello G. 2, Rapone M. 2, Zanesco A. 1 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • Paper F155. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1) Università del Sannio, Benevento. 2) Istituto Motori, CNR, Napoli. (literal)
Titolo
  • Quantum-inspired evolutionary classification of driving sequences in vehicle emission factor measurement (literal)
Abstract
  • A heuristic procedure of classification, the quantum-inspired classifier (QIC), exploiting search space exploration and resource exploitation of quantum computing on a software basis is proposed. The application to the problem of speed sequence classification for vehicle emission factor determination based on drive styles is shown. Experimental results are discussed by showing the QIC capability of converging better and faster than classical evolutionary algorithms. (literal)
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