메뉴 건너뛰기




Volumn , Issue , 2008, Pages 33-38

Adjusting weights and architecture of neural networks through PSO with time-varying parameters and early stopping

Author keywords

[No Author keywords available]

Indexed keywords

OPTIMIZATION; PARTICLE SWARM OPTIMIZATION (PSO); TIME VARYING CONTROL SYSTEMS; TIME VARYING NETWORKS; TIME VARYING SYSTEMS;

EID: 58049191124     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SBRN.2008.18     Document Type: Conference Paper
Times cited : (7)

References (14)
  • 4
    • 35548944900 scopus 로고    scopus 로고
    • An Improved Particle Swarm Optimization for Evolving Feedforward Artificial Neural Networks
    • J. Yu, L. Xi and S. Wang, "An Improved Particle Swarm Optimization for Evolving Feedforward Artificial Neural Networks", Neural Processing Letter, 2007, pp. 217-231
    • (2007) Neural Processing Letter , pp. 217-231
    • Yu, J.1    Xi, L.2    Wang, S.3
  • 6
    • 0033666935 scopus 로고    scopus 로고
    • Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization
    • San Diego, CA
    • R. C. Eberhart, Y. Shi, "Comparing Inertia Weights and Constriction Factors in Particle Swarm Optimization", Proceedings of IEEE congress evolutionary computation, San Diego, CA, 2000, pp 84-88.
    • (2000) Proceedings of IEEE congress evolutionary computation , pp. 84-88
    • Eberhart, R.C.1    Shi, Y.2
  • 7
    • 58049218713 scopus 로고    scopus 로고
    • Weka Data Mining Software, University of Waikato, http://www.cs.waikato. ac.nz/ml/weka/
    • Weka Data Mining Software, University of Waikato, http://www.cs.waikato. ac.nz/ml/weka/
  • 8
    • 0031143030 scopus 로고    scopus 로고
    • A new evolutionary system for evolving artificial neural networks
    • X. Yao, Y. Liu, "A new evolutionary system for evolving artificial neural networks", IEEE Trans Neural Networks, 1997, pp. 694-713.
    • (1997) IEEE Trans Neural Networks , pp. 694-713
    • Yao, X.1    Liu, Y.2
  • 9
    • 0000646059 scopus 로고
    • Learning internal representation by error propagation
    • MIT Press. Cambridge, MA
    • D. E. Rumelhart, G. E. Hinton. and R.J. Williams. "Learning internal representation by error propagation", Parallel Distributed Processing, MIT Press. Cambridge, MA, 1986, pp. 318-362.
    • (1986) Parallel Distributed Processing , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 10
    • 0004042460 scopus 로고
    • Proben1 - A set of neural network benchmark problems and benchmark rules
    • Technical Report 21/94, Fakultät für Informatik, Universität Karlsruhe, Germany, September
    • L. Prechelt, "Proben1 - A set of neural network benchmark problems and benchmark rules", Technical Report 21/94, Fakultät für Informatik, Universität Karlsruhe, Germany, September, 1994.
    • (1994)
    • Prechelt, L.1
  • 11
    • 0001045808 scopus 로고    scopus 로고
    • Empirical study of particle swarm Opimization
    • Y. Shi, R. C. Eberhart, "Empirical study of particle swarm Opimization". Proc. IEEE Conf., 1999, pp. 101-106
    • (1999) Proc. IEEE Conf , pp. 101-106
    • Shi, Y.1    Eberhart, R.C.2
  • 14
    • 3142768423 scopus 로고    scopus 로고
    • Self-organizing hierarchical particle swarm optimizer with time-varing acceleration coefficients
    • A. Ratnaweera, Saman K. Halgamuge, H. C. Watson, "Self-organizing hierarchical particle swarm optimizer with time-varing acceleration coefficients". IEEE Trans. Evol. Comput., 2004, pp. 240-25
    • (2004) IEEE Trans. Evol. Comput , pp. 240-325
    • Ratnaweera, A.1    Saman, K.2    Halgamuge, H.3    Watson, C.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.