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.
Quantum-inspired evolutionary classification of driving sequences in vehicle emission factor measurement
Meccariello G;Rapone M;
2007
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.File in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
F155.pdf
solo utenti autorizzati
Tipologia:
Versione Editoriale (PDF)
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
252.67 kB
Formato
Adobe PDF
|
252.67 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.