메뉴 건너뛰기




Volumn 8, Issue 10, 2008, Pages 6203-6224

GACEM: Genetic algorithm based classifier ensemble in a multi-sensor system

Author keywords

Classifier ensemble; Fusion; Genetic algorithm; Multi sensor system; Optimization

Indexed keywords

CLASSIFICATION ABILITY; CLASSIFIER ENSEMBLES; EMPIRICAL STUDIES; FEATURE VECTORS; LEARNING PARADIGMS; MULTI-SENSOR SYSTEMS; OPTIMAL CLASSIFICATION; ROBUST PERFORMANCE;

EID: 55249111579     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s8106203     Document Type: Article
Times cited : (10)

References (37)
  • 6
    • 4844228284 scopus 로고    scopus 로고
    • Distributed Target Classification and Tracking in Sensor Networks
    • Brooks, R. R.; Ramanathan P.; Sayeed A. M. Distributed Target Classification and Tracking in Sensor Networks. Proceedings of the IEEE 2003, 91, 1163-1171.
    • (2003) Proceedings of the IEEE , vol.91 , pp. 1163-1171
    • Brooks, R.R.1    Ramanathan, P.2    Sayeed, A.M.3
  • 7
    • 0142163128 scopus 로고    scopus 로고
    • Multisensor Fusion and Integration: Approaches, Applications, and Future Research Directions
    • Luo, R. C.; Yih C.-C.; Su K. L. Multisensor Fusion and Integration: Approaches, Applications, and Future Research Directions. IEEE Sensors Journal 2002, 2, 107-119.
    • (2002) IEEE Sensors Journal , vol.2 , pp. 107-119
    • Luo, R.C.1    Yih, C.-C.2    Su, K.L.3
  • 8
    • 0030735959 scopus 로고    scopus 로고
    • An Introduction to Multisensor Data Fusion
    • Hall, D. L.; Llinas J. An Introduction to Multisensor Data Fusion. Proceedings of the IEEE 1997, 85, 6-23.
    • (1997) Proceedings of the IEEE , vol.85 , pp. 6-23
    • Hall, D.L.1    Llinas, J.2
  • 9
    • 0013092453 scopus 로고    scopus 로고
    • Proc. 4th Ann. Conf. on Information Fusion
    • TuC2/25-TuC22/30
    • Clouqueur, T.; Ramanathan P.; Saluja K. K.; Wang K.-C. Value-Fusion versus Decision-Fusion for Fault-Tolerance in Collaborative Target Detection in Sensor Networks. Proc. 4th Ann. Conf. on Information Fusion 2001, TuC2/25-TuC22/30.
    • (2001)
    • Clouqueur, T.1    Ramanathan, P.2    Saluja, K.K.3    Wang, K.-C.4
  • 12
    • 0037403516 scopus 로고    scopus 로고
    • Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy
    • Kuncheva, L. I.; Whitaker C. J. Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy. Machine Learning 2003, 51, 181-207.
    • (2003) Machine Learning , vol.51 , pp. 181-207
    • Kuncheva, L.I.1    Whitaker, C.J.2
  • 14
    • 0033893813 scopus 로고    scopus 로고
    • Optimal Linear Combination of Neural Networks for Improving Classification Performance
    • Ueda, N. Optimal Linear Combination of Neural Networks for Improving Classification Performance. IEEE Transactions on Pattern Analysis and Machine Intelligence 2000, 22, 207-215.
    • (2000) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.22 , pp. 207-215
    • Ueda, N.1
  • 18
    • 0031361611 scopus 로고    scopus 로고
    • Machine learning research: Four current directions
    • Dietterich, T. G. Machine learning research: Four current directions. AI Magazine 1997, 18, 97-136.
    • (1997) AI Magazine , vol.18 , pp. 97-136
    • Dietterich, T.G.1
  • 19
    • 0030211964 scopus 로고    scopus 로고
    • Bagging Predictors
    • Breiman, L. Bagging Predictors. Machine Learning 1996, 24, 123-140.
    • (1996) Machine Learning , vol.24 , pp. 123-140
    • Breiman, L.1
  • 23
    • 0036567392 scopus 로고    scopus 로고
    • Ensembling Neural Networks: Many Could Be Better Than All
    • Zhou, Z.-H.; Wu J.; Tang W. Ensembling Neural Networks: Many Could Be Better Than All. Artificial Intelligence 2002, 137, 239-263.
    • (2002) Artificial Intelligence , vol.137 , pp. 239-263
    • Zhou, Z.-H.1    Wu, J.2    Tang, W.3
  • 24
  • 25
    • 0031238275 scopus 로고    scopus 로고
    • Application of majority voting to pattern recognition: An analysis of the behavior and performance
    • Lam, L.; Suen C. Y. Application of majority voting to pattern recognition: An analysis of the behavior and performance. IEEE Transactions on Systems, Man, and Cybernetics 1997, 27, 553-567.
    • (1997) IEEE Transactions on Systems, Man, and Cybernetics , vol.27 , pp. 553-567
    • Lam, L.1    Suen, C.Y.2
  • 26
    • 0038667775 scopus 로고    scopus 로고
    • Performance analysis of pattern classifier combination by plurality voting
    • Lin, X.; Yacoub S.; Burns J.; Simske S. Performance analysis of pattern classifier combination by plurality voting. Pattern Recognition Letters 2003, 24, 1959-1969.
    • (2003) Pattern Recognition Letters , vol.24 , pp. 1959-1969
    • Lin, X.1    Yacoub, S.2    Burns, J.3    Simske, S.4
  • 28
    • 33744793789 scopus 로고    scopus 로고
    • Multi-sensor fusion: An Evolutionary algorithm approach
    • Maslov, I. V.; Gertner I. Multi-sensor fusion: an Evolutionary algorithm approach. Information Fusion 2006, 7, 304-330.
    • (2006) Information Fusion , vol.7 , pp. 304-330
    • Maslov, I.V.1    Gertner, I.2
  • 29
    • 0030242844 scopus 로고    scopus 로고
    • Hybrid Fuzzy-Genetic Technique for Multisensor Fusion
    • Buczak, A. L.; Uhrig R. E. Hybrid Fuzzy-Genetic Technique for Multisensor Fusion. Information Sciences 1996, 93, 265-281.
    • (1996) Information Sciences , vol.93 , pp. 265-281
    • Buczak, A.L.1    Uhrig, R.E.2
  • 30
    • 10444224737 scopus 로고    scopus 로고
    • Classifier Selection for Majority Voting
    • Ruta, D.; Gabrys B. Classifier Selection for Majority Voting. Information Fusion 2005, 6, 63-81.
    • (2005) Information Fusion , vol.6 , pp. 63-81
    • Ruta, D.1    Gabrys, B.2
  • 32
    • 55249102000 scopus 로고    scopus 로고
    • Ship Signatures Management System - Towards increased warship survivability
    • Seto, M. L.; Hutt D. Ship Signatures Management System - Towards increased warship survivability. Underwater Defence Technology 2004, 1-10.
    • (2004) Underwater Defence Technology , pp. 1-10
    • Seto, M.L.1    Hutt, D.2
  • 35
    • 0035679049 scopus 로고    scopus 로고
    • Rule-based Classification Systems Using Classification And Regression Tree (CART) Analysis
    • Lawrence, R. L.; Wright A. Rule-based Classification Systems Using Classification And Regression Tree (CART) Analysis Photogrammetric Engineering & Remote Sensing 2001, 67, 1137-1142.
    • (2001) Photogrammetric Engineering & Remote Sensing , vol.67 , pp. 1137-1142
    • Lawrence, R.L.1    Wright, A.2
  • 36
    • 16644388588 scopus 로고    scopus 로고
    • Enhancing Electronic Nose Performance by Sensor Selection Using a New Integer-based Genetic Algorithm Approach
    • Gardner, J. W.; Boilot P.; Hines E. L. Enhancing Electronic Nose Performance by Sensor Selection Using a New Integer-based Genetic Algorithm Approach. Sensors and Actuators B 2005, 106, 114-121.
    • (2005) Sensors and Actuators B , vol.106 , pp. 114-121
    • Gardner, J.W.1    Boilot, P.2    Hines, E.L.3
  • 37
    • 0035427280 scopus 로고    scopus 로고
    • Optimal Sensor Placement for Fault Detection
    • Worden, K.; Burrows A. P. Optimal Sensor Placement for Fault Detection. Engineering Structures 2001, 23, 885-901.
    • (2001) Engineering Structures , vol.23 , pp. 885-901
    • Worden, K.1    Burrows, A.P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.