Earticle

초록

영어

Electronic nose (EN) is a equipment with ability of identification of simple or complex odors. Because of its low cost and accurate identification rate, the researches of it attract more attention and it develops quickly. Firstly, through Gas Sensor Array, we get large amount sample data and all data which is preprocessed. Secondly, modified Bp algorithm and RBF algorithm combining nearest neighbor - clustering algorithm and K-means clustering algorithm is proposed to realize the identification. Principal component analysis (PCA) method wipes off redundant sensor from the sensor array. Principle components and brief sensor signals are tested by above two algorithms. The test result indicated that the rapid and exact identification measure of ANN combining PCA is provided to the pattern identification with sensor information fusion.

목차

Abstract
 1. Introduction
 2. Experiment System Model
 3. PCA and Modified ANN Algorithm
  3.1. PCA (Principal Component Analysis)
  3.2. Modified BP and RBF Algorithm
  3.3. Nearest K-means Clustering Algorithm
 4. Experiment and Result Analysis
  4.1. Data Preprocessing and Data Sample
  4.2. PCA Research
  4.3. Modified ANN Research
  4.4. Result Reduce the Data Dimension of PCA
 5. Conclusions
 Acknowledgements
 References

키워드

저자

• Liang Zhao [ Dept of Info and Automation, Xi’an Univ. of Arch.＆Tech., Xi’an 710055, China ]
• Jun Lu [ School of Automation and Information Engineering, Xi’an University of Technology, Xi’an 710048, China ]
• Deng-Feng Chen [ Dept of Info and Automation, Xi’an Univ. of Arch.＆Tech., Xi’an 710055, China ]
• Wei Wang [ Schoolt of Civil Engineering, Xi’an Univ. of Arch.＆Tech., Xi’an 710055, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605