Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
The basic ideas in neural networks
Communications of the ACM
Real-Time Prediction of Water Stage with Artificial Neural Network Approach
AI '02 Proceedings of the 15th Australian Joint Conference on Artificial Intelligence: Advances in Artificial Intelligence
River stage forecasting with particle swarm optimization
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Prediction of building energy consumption by using artificial neural networks
Advances in Engineering Software
Simulating the seismic response of embankments via artificial neural networks
Advances in Engineering Software
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Whilst conventional approach in structural design is based on reliability-calibrated factored design formula, performance-based design customizes a solution to the specific circumstance. In this work, an artificial neural network approach is employed to determine implicit limit state functions for reliability evaluations in performance-based design and to optimally evaluate a set of design variables under specified performance criteria and corresponding desired reliability levels in design. Case examples are shown for reliability design. Through the establishment of the response and reliability databases, for specified target reliabilities, structural response computations are integrated with the evaluation of design parameters and design can be accomplished. By employing this methodology, with the same performance requirements, pertinent design parameters can be altered in order to evaluate feasible design alternatives, to explore the usage of various structural materials and to define required material quality control.