On-line outliers detection by neural network with quantum evolutionary algorithm

Tzyy Chyang Lu, Jyh Ching Juang, Gwo Ruey Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper proposes a structure that combines neural networks and quantum evolutionary algorithm, called a neural network with quantum evolutionary algorithm (NN-QEA), for the establishment of a nonlinear map when data are subject to outliers. Neural networks have the advantage of powerful modeling ability. Quantum evolutionary algorithm has the characteristics of rapid convergence and good global search capability. NN-QEA combines the advantages of both and realizes the goal of modeling and outliers rejection simultaneously. The effectiveness and the applicability of NN-QEA are demonstrated by experimental results on the modeling of the compressor characteristic map.

Original languageEnglish
Title of host publicationSecond International Conference on Innovative Computing, Information and Control, ICICIC 2007
PublisherIEEE Computer Society
ISBN (Print)0769528821, 9780769528823
DOIs
Publication statusPublished - 2007 Jan 1
Event2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007 - Kumamoto, Japan
Duration: 2007 Sep 52007 Sep 7

Publication series

NameSecond International Conference on Innovative Computing, Information and Control, ICICIC 2007

Other

Other2nd International Conference on Innovative Computing, Information and Control, ICICIC 2007
CountryJapan
CityKumamoto
Period07-09-0507-09-07

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mechanical Engineering

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