풍동실험 데이터의 해석을 위한 중요한 기법들

  • 정승환 (연세대학교 산업기술연구소 토목연구부, 전문연구원)
  • 발행 : 1999.12.01

초록

키워드

참고문헌

  1. Internal Report RD/l/N v.114 no.68 Eigencector analysis of pressure Fluctuations on the West Burton instrumented cooling tower Armitt, J.
  2. J .Wind Eng. Ind. Aerodyn v.50 Proper orthogona decomposition of roof pressure Bienkiewicz, B.;Ham, H. J.;Sun, Y.
  3. Thris Asia-Pacifc Symposien on Wind Eng v.1 How can we simplify and generalize wind loads? Davenport, A. G.
  4. Proc. of the 9th Int. Conf. on Wind Eng. Proper orthogonal decomposition study of approach wind-building pressure correlation Tamura, Y.;Ueda, H.;Kihuchi, H.;Hibi, K.;Suganuma, S.;Bienkiewicz, B.
  5. Ph.D Dissertation, Dept. of Civil Engr. Colorado State University analysis of Building wind pressure using proper prthogonal decomposition. autoregressive miving average and neural networks Jeong, S. H.
  6. Time series : theory and methods Brockwell, P. J.;Davis, R. A.
  7. Proc. of the 5th int. Conf. on Wind Eng. A cooling tower wind loading midel based on fullscale data Portier, L. J.;Scanlan, R. H.;J. E. Cermak(ed.)
  8. Eng. Struct. v.13 Modeling of wind pressures on monoslope roofs Stathopoulos, T.;Mohannadian, A. R.
  9. Can. J. Civ. Eng. v.22 Prediction of wind load distribution for air-suported structures using naural networks Turkkan, N.;Arivastava, N. K.
  10. Proc. 9th Int. Conf. on Wind Eng. Neural network modeling of wind-induced interference effects Khanduri, A. C.;Bedard, C.;Stathopoulos, T.
  11. Proc. 9th Int. Conf. on Wind Eng. using a backpropagation neural networks for predicting wind induced damage to buildings Sandri, P.;Mehta, K. C.
  12. MATLAB-Neural Network Toolbox Users Guide