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Wind and Structures
  Volume 5, Number 1, January 2002, pages 1-14

Application of artificial neural network for determination of wind induced pressures on gable roof
Naveen Kwatra, P.N. Godbole and Prem Krishna(India)

    Artificial Neural Networks (ANN) have the capability to develop functional relationshipsrnbetween input-output patterns obtained from any source. Thus ANN can be conveniently used to developrna generalised relationship from limited and sometimes inconsistent data, and can therefore also be appliedrnto tackle the data obtained from wind tunnel tests on building models with large number of variables. Inrnthis paper ANN model has been developed for predicting wind induced pressures in various zones of arnGable Building from limited test data. The procedure is also extended to a case wherein interference effectsrnon a gable roof building by a similar building are studied. It is found that the Artificial Neural Networkrnmodelling is seen to predict successfully, the pressure coefficients for any roof slope that has not beenrncovered by the experimental study. It is seen that ANN modelling can lead to a reduction of the windrntunnel testing effort for interference studies to almost half.
Key Words
    wind pressure coefficients; artificial neural network; interference factors and training data
Naveen Kwatra, Department of Civil Engineering, Thapar Institute of Engineering & Technology, Patiala, IndiarnP. N. Godbole and Prem Krishna, Department of Civil Engineering, University of Roorkee, Roorkee, India

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