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Volumn , Issue , 2009, Pages 85-87

Temperature modeling study for high precision gyroscope based on neural network

Author keywords

Back Propagation; Genetic algorithm; Gyroscope; Neural network; Radial basis function

Indexed keywords

BACK-PROPAGATION NEURAL NETWORKS; BP NEURAL NETWORKS; CONTINUOUS TEMPERATURE; HIGH PRECISION; INPUT SAMPLE; MEAN TEMPERATURE; MULTIINPUT; NON-LINEAR MODEL; RADIAL BASIS FUNCTION; RADIAL BASIS FUNCTION NEURAL NETWORKS; RBF NEURAL NETWORK; RELATIVE ERRORS; TEMPERATURE MODELING;

EID: 70350702765     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IUCE.2009.112     Document Type: Conference Paper
Times cited : (2)

References (5)
  • 2
    • 70350719103 scopus 로고    scopus 로고
    • RBF Networks for Temperature Compensation of Gyros in Low-Cost SINS, Ordnances Industry
    • Dec
    • Liang WAN, Xinsheng HUANG, Hongli TAN. "RBF Networks for Temperature Compensation of Gyros in Low-Cost SINS, " Ordnances Industry Automation, vol 26, Dec, 2007. pp.70.
    • (2007) Automation , vol.26 , pp. 70
    • Liang, W.A.N.1    HUANG, X.2    Hongli, T.A.N.3
  • 4
    • 33747878129 scopus 로고    scopus 로고
    • Neural network-based failure rate prediction for De Havilland Dash-8 tires
    • Oct
    • Ahmed Z, Al-Garni, Ahmad Jamala, et al, "Neural network-based failure rate prediction for De Havilland Dash-8 tires, " Engineering Applications of Artificial Intelligence, vol.19, Oct. 2006, pp.681-691.
    • (2006) Engineering Applications of Artificial Intelligence , vol.19 , pp. 681-691
    • Ahmed, Z.1    Al-Garni, A.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.