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Comparing the linear and logarithm normalized artificial neural networks in inverse design of aircraft cabin environment
Abstract When the indoor environment is designed by genetic algorithm (GA) and computational fluid dynamics (CFD), the artificial neural network (ANN) plays a role of surrogate model of CFD to reduce the computational cost. To improve the performance of ANN, a self-updating logarithm normalized method was proposed to enhance the local prediction of ANN in the inverse design based on GA and ANN. An MD-82 aircraft cabin was used to test the performance of the proposed method, and different environmental parameters were chosen to be the objectives of the cabin environment. The success rate (SR) was used to evaluate the local prediction ability of ANN. Instead of linear normalized ANN, SR was found to be increased by 10.5% with the logarithm normalized ANN and the computational cost was reduced by 23.2% for the same quality of solution.
Comparing the linear and logarithm normalized artificial neural networks in inverse design of aircraft cabin environment
Abstract When the indoor environment is designed by genetic algorithm (GA) and computational fluid dynamics (CFD), the artificial neural network (ANN) plays a role of surrogate model of CFD to reduce the computational cost. To improve the performance of ANN, a self-updating logarithm normalized method was proposed to enhance the local prediction of ANN in the inverse design based on GA and ANN. An MD-82 aircraft cabin was used to test the performance of the proposed method, and different environmental parameters were chosen to be the objectives of the cabin environment. The success rate (SR) was used to evaluate the local prediction ability of ANN. Instead of linear normalized ANN, SR was found to be increased by 10.5% with the logarithm normalized ANN and the computational cost was reduced by 23.2% for the same quality of solution.
Comparing the linear and logarithm normalized artificial neural networks in inverse design of aircraft cabin environment
Zhang, Tian-hu (author) / You, Xue-yi (author)
Building Simulation ; 9 ; 729-734
2016-06-13
6 pages
Article (Journal)
Electronic Resource
English
genetic algorithm , artificial neural network , normalized method , aircraft cabin environment , inverse design Engineering , Building Construction and Design , Engineering Thermodynamics, Heat and Mass Transfer , Atmospheric Protection/Air Quality Control/Air Pollution , Monitoring/Environmental Analysis
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A simulation-based inverse design of preset aircraft cabin environment
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A simulation-based inverse design of preset aircraft cabin environment
| British Library Online Contents | 2014