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Keywords: artificial neural networksClose
Proc. ASME. IDETC-CIE2000, Volume 3: 5th Design for Manufacturing Conference, 177-185, September 10–13, 2000
Paper No: DETC2000/DFM-14026
... products allow the environmental impacts of new products to be approximated quickly during conceptual design. Artificial neural networks train on product attributes and environmental impact data from pre-existing life-cycle assessment studies. The product design team queries the trained artificial model...
Proc. ASME. IDETC-CIE2019, Volume 3: 21st International Conference on Advanced Vehicle Technologies; 16th International Conference on Design Education, V003T01A005, August 18–21, 2019
Paper No: DETC2019-97906
... four-wheel drive vehicle by means of Artificial Neural Networks. The proposed architecture relies on the combination of a pattern recognition neural classifier with two stages of cascaded regression neural networks. The classifier allows identifying the road condition and the regression stages perform...
Proc. ASME. IDETC-CIE2012, Volume 3: 38th Design Automation Conference, Parts A and B, 745-752, August 12–15, 2012
Paper No: DETC2012-71098
... the optimization process. CFD Artificial Neural Networks Optimization PREDICTING THE THERMAL PERFORMANCE FOR THE MULTI- OBJECTIVE VEHICLE UNDERHOOD PACKING OPTIMIZATION PROBLEM Ravi Teja Katragadda Graduate Student Department of Mechanical Engineering Clemson University Clemson, South Carolina 29634...
Proc. ASME. IDETC-CIE2012, Volume 3: 38th Design Automation Conference, Parts A and B, 99-109, August 12–15, 2012
Paper No: DETC2012-71337
... the possibility that the assembly time estimation process can be automated while reducing the level of design detail required. The approach presented here trains artificial neural networks (ANNs) to estimate the assembly times of vehicle sub-assemblies at various stages using properties of the connectivity graph...