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

Wind and Structures, An International Journal

Volumn 5, Issue 1, 2002, Pages 1-14

  Kwatra, Naveen ^a   Godbole, P N ^a   Krishna, Prem ^a  

^a THAPAR UNIVERSITY   (India)

Author keywords

Artificial neural network; Interference factors and training data; Wind pressure coefficients

Indexed keywords

BUILDINGS; NEURAL NETWORKS; PRESSURE EFFECTS; WIND TUNNELS;

WIND INDUCED PRESSURES;

WIND EFFECTS;

EID: 0036182162     PISSN: 12266116     EISSN: None     Source Type: Journal    
DOI: 10.12989/was.2002.5.1.001     Document Type: Article

References (12)

1. An analysis of transformation
2. Physical modelling of atmospheric surface layer
3. Application of cascade-correlation learning network for determination of wind pressure distribution in buildings
4. Application of artificial neural network for determination of wind induced pressures on gable roofs
5. Neural network modelling of wind-induced interference effects
6. Selection of local peak pressure coefficients for wind tunnel studies of buildings
7. Using a backpropagation neural network for predicting wind induced damage to buildings
8. Wind tunnel simulation requirements to assess wind loads on low-rise buildings
9. Pressure characteristics for separated flows
10. Fatigue of metal roof cladding subject to wind loading. Part I: Fatigue-related characteristics of roof pressures