메뉴 건너뛰기




Volumn 15, Issue 1, 2009, Pages 83-88

Study on the meteorological prediction model using the learning algorithm of neural ensemble based on PSO algorithms

Author keywords

Neural network ensemble; Optimal combination; Particle swarm optimization

Indexed keywords


EID: 77956447069     PISSN: 10068775     EISSN: 10044965     Source Type: Journal    
DOI: 10.3969/j.issn.1006-8775.2009.01.014     Document Type: Article
Times cited : (22)

References (20)
  • 1
    • 77958060483 scopus 로고    scopus 로고
    • An exploration of heavy rain forecasting technique based on artificial neural networks [J]
    • HU Jian-lin, TU Song-bo, FENG Guang-liu. An exploration of heavy rain forecasting technique based on artificial neural networks [J]. J. Trop. Meteor., 2003, 19(4): 422-428.
    • (2003) J. Trop. Meteor. , vol.19 , Issue.4 , pp. 422-428
    • Hu, J.-L.1    Tu, S.-B.2    Feng, G.-L.3
  • 2
    • 0035877455 scopus 로고    scopus 로고
    • Nonlinear canonical correlation analysis of the tropical pacific climate
    • HSIEH W W. Nonlinear canonical correlation analysis of the tropical Pacific climate variability using Neural Network Approach [J]. J. Climate, 2001, 14(12): 2528-2539. (Pubitemid 33050334)
    • (2001) Journal of Climate , vol.14 , Issue.12 , pp. 2528-2539
    • Hsieh, W.W.1
  • 4
    • 77952844947 scopus 로고    scopus 로고
    • The back propagation neural network meteorological forecast model research evolved and designed by genetic algorithms [J]
    • WU Jian-sheng, JIN Long, WANG Ling-zhi. The back propagation neural network meteorological forecast model research evolved and designed by genetic algorithms [J]. J. Trop. Meteor., 2006, 22(4): 411-416.
    • (2006) J. Trop. Meteor. , vol.22 , Issue.4 , pp. 411-416
    • Wu, J.-S.1    Jin, L.2    Wang, L.-Z.3
  • 5
    • 70349177447 scopus 로고    scopus 로고
    • Downscaling forecast for the monthly precipitation over Guangxi based on the BP neural network model [J]
    • HE Hui, JIN Long, QING Zhi-nian, et al. Downscaling forecast for the monthly precipitation over Guangxi based on the BP neural network model [J]. J. Trop. Meteor., 2007, 23(1): 72-77.
    • (2007) J. Trop. Meteor. , vol.23 , Issue.1 , pp. 72-77
    • He, H.1    Jin, L.2    Qing, Z.-N.3
  • 6
    • 33745897381 scopus 로고    scopus 로고
    • Study on the over-fitting of the artificial neural network forecasting model [J]
    • JIN Long, KUANG Xue-yuan, et al. Study on the over-fitting of the artificial neural network forecasting model [J]. Acta Meteor. Sinica, 2004, 62(1): 62-69.
    • (2004) Acta Meteor. Sinica , vol.62 , Issue.1 , pp. 62-69
    • Jin, L.1    Kuang, X.-Y.2
  • 8
    • 85127438349 scopus 로고    scopus 로고
    • Learning with Ensembles: How Over-fitting can be useful [C]
    • Cambridge: MIT Press
    • SOLLICH P, KROGH A. Learning with Ensembles: How Over-fitting can be useful [C]//Advances in Neural Information Processing Systems 8, Cambridge: MIT Press, 1996: 190-196.
    • (1996) Advances in Neural Information Processing Systems , vol.8 , pp. 190-196
    • Sollich, P.1    Krogh, A.2
  • 9
    • 0038532960 scopus 로고    scopus 로고
    • Neural network ensemble [J]
    • ZHOU Zhi-hua, CHEN Shi-fu. Neural network ensemble [J]. Chin. J. Comput., 2002, 25(1): 1-8.
    • (2002) Chin. J. Comput. , vol.25 , Issue.1 , pp. 1-8
    • Zhou, Z.-H.1    Chen, S.-F.2
  • 12
    • 0032073506 scopus 로고    scopus 로고
    • Classification of seismic signals by integrating ensembles of neural networks [J]
    • SOLLICH P, INTRATOR N. Classification of seismic signals by integrating ensembles of neural networks [J]. IEEE Trans. Signal Process., 1998, 46(5): 1194-1021.
    • (1998) IEEE Trans. Signal Process. , vol.46 , Issue.5 , pp. 1194-1021
    • Sollich, P.1    Intrator, N.2
  • 13
    • 24944531630 scopus 로고    scopus 로고
    • Spiculated lesion detection in digital mammogram based on artificial neural network ensemble
    • Advances in Neural Networks - ISNN 2005: Second International Symposium on Neural Networks. Proceedings
    • LI NING, ZHOU HUA-JIE, LING JIN-JIANG, et al. Speculated lesion detection in digital mammogram based on artificial neural network ensemble [J]. Adv. Neural Networks ISNN, Springer Press, 2005, 3: 790-795. (Pubitemid 41315178)
    • (2005) Lecture Notes in Computer Science , vol.3498 , Issue.3 , pp. 790-795
    • Li, N.1    Zhou, H.2    Ling, J.3    Zhou, Z.4
  • 14
    • 0034612523 scopus 로고    scopus 로고
    • Inspiration for optimization from social insect behaviour
    • DOI 10.1038/35017500
    • BONABEAU E, DORIGO M, THERAULAZ G. Inspiration for optimization from social insect behavior [J]. Nature, 2000, 406(6): 39-42. (Pubitemid 30460201)
    • (2000) Nature , vol.406 , Issue.6791 , pp. 39-42
    • Bonabeau, E.1    Dorigo, M.2    Theraulaz, G.3
  • 15
    • 84901470581 scopus 로고    scopus 로고
    • Multi-objective optimization using dynamic neighborhood particle swarm optimization [C]
    • Hawaii: Congress on Evolutionary Computation
    • XIAOHUI H, EBERHART R. Multi-objective optimization using dynamic neighborhood particle swarm optimization [C]// Proceeding of Congress on Evolutionary Computation. Hawaii: Congress on Evolutionary Computation, 2002: 1677-1681.
    • (2002) Proceeding of Congress on Evolutionary Computation , pp. 1677-1681
    • Xiaohui, H.1    Eberhart, R.2
  • 18
    • 19044361940 scopus 로고
    • SSA a toolkit for noisy chaotic signals [J]
    • VAUTARD
    • VAUTARD. SSA: a toolkit for noisy chaotic signals [J]. Physical D, 1992, 58: 95-126.
    • (1992) Physical D , vol.58 , pp. 95-126


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.