Application of artificial neural network for determination of wind induced pressures on gable roofs

被引:0
|
作者
Kwatra, N [1 ]
Godbole, PN [1 ]
Krishna, P [1 ]
机构
[1] Univ Roorkee, Dept Civil Engn, Roorkee 247667, Uttar Pradesh, India
关键词
D O I
暂无
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Artificial Neural Networks (ANN) have the capability to develop functional relationships between input-output patterns obtained from any source. Thus ANN can be conveniently used to develop a generalised relationship from limited and sometimes inconsistent data. Thus ANN can be applied to tackle the data obtained from the wind tunnel tests on building models with large member of variables. In this paper ANN model has been developed for predicting wind induced pressures in various zones of a Gable Building from limited test data. The procedure can also be extended to account for the interference effects.
引用
收藏
页码:1825 / 1829
页数:5
相关论文
共 50 条
  • [21] Experimental studies of wind-induced snowdrifts on typical single-span low-slope gable roofs
    Liu Z.
    Yu Z.
    He H.
    Chen Y.
    Xie D.
    Jianzhu Jiegou Xuebao/Journal of Building Structures, 2024, 45 (05): : 136 - 144
  • [22] A neural network application in estimating wind induced shallow lake motions
    Fulop, IA
    Jozsa, J
    Kramer, T
    HYDROINFORMATICS '98, VOLS 1 AND 2, 1998, : 753 - 758
  • [23] Artificial Neural Network Application for Parameter Prediction of Heat Induced Distortion
    Pinzon, Cesar
    Hasewaga, Kazuhiko
    Murakawa, Hidekazu
    TRENDS IN APPLIED KNOWLEDGE-BASED SYSTEMS AND DATA SCIENCE, 2016, 9799 : 599 - 608
  • [24] Application of artificial neural network for performance evaluation of vertical axis wind turbine rotor
    Biswas, A.
    Sarkar, S.
    Gupta, R.
    International Journal of Ambient Energy, 2016, 37 (02): : 209 - 218
  • [25] Application of S-Transform-based Artificial Neural Network to Wind Speed Forecasting
    Mori, Hiroyuki
    Okura, Soichiro
    2017 IEEE MANCHESTER POWERTECH, 2017,
  • [26] Application of artificial neural network for performance evaluation of vertical axis wind turbine rotor
    Biswas, A.
    Sarkar, S.
    Gupta, R.
    INTERNATIONAL JOURNAL OF AMBIENT ENERGY, 2016, 37 (02) : 209 - 218
  • [27] Application of Artificial Neural Network Method in the Determination of Natural Frequencies of Cantilever Beams
    Sharan, Anand M.
    Legge, James
    ADVANCES IN VIBRATION ENGINEERING, 2008, 7 (03): : 293 - 299
  • [28] Artificial neural network and genetic algorithm for the design optimization of industrial roofs - A comparison
    Ramasamy, JV
    Rajasekaran, S
    COMPUTERS & STRUCTURES, 1996, 58 (04) : 747 - 755
  • [29] Application of artificial neural network to simultaneous spectrophotometric determination of Cu, Co and Ni
    He, CY
    Sun, YM
    Wu, GH
    Chen, R
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2001, 21 (05) : 719 - 722
  • [30] Application of artificial neural network to simultaneous spectrophotometric determination of three components dyestuff
    Lin, SL
    Xie, CS
    Wang, JD
    Chen, ZR
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2003, 23 (06) : 1135 - 1138