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Keywords: neural network
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Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A038, August 17–19, 2021
Paper No: DETC2021-67963
... Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC-CIE2021 August 17-19, 2021, Virtual, Online DETC2021-67963 POINT-CLOUD NEURAL NETWORK USING TRANSFER LEARNING-BASED MULTI-FIDELITY METHOD FOR THERMAL...
Proceedings Papers

Proc. ASME. DETC94, 20th Design Automation Conference: Volume 2 — Robust Design Applications; Decomposition and Design Optimization; Optimization Tools and Applications, 117-123, September 11–14, 1994
Paper No: DETC1994-0119
...Abstract Abstract Artificial Neural Networks, particularly the Hopfield-Tank network, have been effectively applied to the solution of a variety of tasks formulated as large scale combinatorial optimization problems, such as Travelling Salesman Problem and N Queens Problem [1]. The problem...
Proceedings Papers

Proc. ASME. DETC97, Volume 1D: 16th Biennial Conference on Mechanical Vibration and Noise, V01DT18A001, September 14–17, 1997
Paper No: DETC97/VIB-4233
... proposal which intent is to exploit the capability of model updating techniques associated to neural networks to reduce the amount of measured data. The updating procedure supplies a reliable model that permits to simulate any damage condition, which allows to establish a direct correlation between...
Proceedings Papers

Proc. ASME. DETC97, Volume 1C: 16th Biennial Conference on Mechanical Vibration and Noise, V01CT11A004, September 14–17, 1997
Paper No: DETC97/VIB-3775
...Abstract Abstract One of the major difficulties in neural network applications is the selection of the parameters in network configuration and the coefficients in learning rule for fast convergence as well as best system performance. This paper developed a network design methodology so...
Proceedings Papers

Proc. ASME. DETC99, Volume 6: International Symposium on Motion and Vibration Control, 161-167, September 12–16, 1999
Paper No: DETC99/MOVIC-8401
...Proceedings of the 1999 ASME Design Engineering Technical Conferences September 12-15,1999, Las Vegas, Nevada DETC99/WIOVIC-8401 STRUCTURAL DAMAGE DETECTION AND IDENTIFICATION USING LEARNING VECTOR QUANTIZATION NEURAL NETWORK Qinzhong Shi/Dept. of Mechanical Engineering and Science, Tokyo Institute...
Proceedings Papers

Proc. ASME. DETC99, Volume 1: 25th Design Automation Conference, 489-501, September 12–16, 1999
Paper No: DETC99/DAC-8559
...Proceedings of the 1999 ASME Design Engineering Technical Conferences September 12-15,1999, Las Vegas, Nevada DETC99/DAC-8559 NEURAL NETWORK-BASED FUZZY REASONING FOR CONCEPTUAL DESIGN EVALUATION J. Sun\ D. K. Kalenchuk^ D. Xue\ and P. Gu 1 Department of Mechanical and Manufacturing Engineering...
Proceedings Papers

Proc. ASME. DETC99, Volume 2: 19th Computers and Information in Engineering Conference, 483-489, September 12–16, 1999
Paper No: DETC99/CIE-9062
...Proceedings of DETC 99 1999 ASME Design Engineering Technical Conferences September 12-15, 1999, Las Vegas, Nevada DETC99/CIE-9062 ASSOCIATIVE TRANSFORMATION OF QUERY WORDS FOR CASE RETRIEVAL SYSTEM BASED ON NEURAL NETWORK Shigeru Nagasawa, Yasushi FUKUZAWA, Yasunori MiYATA, Hiroshi HASEGAWA...
Proceedings Papers

Proc. ASME. DETC99, Volume 1: 25th Design Automation Conference, 139-147, September 12–16, 1999
Paper No: DETC99/DAC-8635
...Abstract Abstract In this study, to find the global optimum efficiently, holographic neural network is introduced to be an activate function of response surface methodology. Since the accuracy of approximation function near the global optimal design is merely important, techniques to search...
Proceedings Papers

Proc. ASME. IDETC-CIE2000, Volume 6: 8th International Power Transmission and Gearing Conference, 339-345, September 10–13, 2000
Paper No: DETC2000/PTG-14398
.... A neural network is trained by a batch of computer simulated transmission error curves and respective contact patterns belonging to systematically varied geometrical deviations. Taking advantage of the generalization capability of the neural network, it can be used to yield tooth flank topography errors...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 10: 44th Mechanisms and Robotics Conference (MR), V010T10A093, August 17–19, 2020
Paper No: DETC2020-22508
...NEURAL NETWORK BASED TRANSFER LEARNING OF MANIPULATOR INVERSE DISPLACEMENT ANALYSIS Houcheng Tang1, Leila Notash Queen s University, Kingston, ON, Canada ABSTRACT In this paper, a neural network based transfer learning approach of inverse displacement analysis of robot manipulators is studied...
Proceedings Papers

Proc. ASME. IDETC-CIE2019, Volume 10: 2019 International Power Transmission and Gearing Conference, V010T11A016, August 18–21, 2019
Paper No: DETC2019-97137
... dynamic response with optimal machine tool setting parameters for manufacturing hypoid gears is discussed. A neural network, named Feed-Forward Back Propagation (FFBP), with Particle Swarm Optimization (PSO) and Gradient Descent (GD) training algorithms are used to predict the TE. With the optimal machine...
Proceedings Papers

Proc. ASME. IDETC-CIE2013, Volume 2A: 33rd Computers and Information in Engineering Conference, V02AT02A068, August 4–7, 2013
Paper No: DETC2013-13088
... An artificial neural network has been implemented and trained with clinical data from 23088 patients. The aim was to predict a patient’s body circumferences and ligament thickness from patient data. A fully connected feed-forward neural network is used, containing no loops and one hidden layer...
Proceedings Papers

Proc. ASME. IDETC-CIE2008, Volume 3: 28th Computers and Information in Engineering Conference, Parts A and B, 1143-1152, August 3–6, 2008
Paper No: DETC2008-49702
... relationship network, in addition to the deterministic parameters and relationships, non-deterministic parameters (e.g., random parameters and fuzzy parameters) and non-deterministic relationships (e.g., neural network relationships and fuzzy relationships) can also be modeled. Propagation of parameter values...
Proceedings Papers

Proc. ASME. IDETC-CIE2008, Volume 3: 28th Computers and Information in Engineering Conference, Parts A and B, 1107-1114, August 3–6, 2008
Paper No: DETC2008-50078
... 24 07 2009 A neural network capable of solving the inverse kinematics of a four degree of freedom biologically inspired robotic cat leg (qualified as a serial linkage system) within its effective 3-D workspace is presented in this paper. The workspace consists of layers of similar...
Proceedings Papers

Proc. ASME. IDETC-CIE2007, Volume 1: 21st Biennial Conference on Mechanical Vibration and Noise, Parts A, B, and C, 1335-1338, September 4–7, 2007
Paper No: DETC2007-34126
... 22 05 2009 The paper studies the application of neural network in chaotic vibration isolation system. Because the dynamical characteristics of the isolation system change with working state of the isolated object, the control system must have the ability to adjust the system parameters...
Proceedings Papers

Proc. ASME. IDETC-CIE2003, Volume 1: 23rd Computers and Information in Engineering Conference, Parts A and B, 767-774, September 2–6, 2003
Paper No: DETC2003/CIE-48254
... extract ports are to be used instead of the hypothetical complete floor extract as a practical solution. Ventilation effectiveness Operating theatre Neural network IAQ assessment HVAC design 3URFHHGLQJV RI7 $60HVLJQ (QJLQHHULQJ 7HFKQLFDO &RQIHUHQFHV DQG &RPSXWHUV DQG ,QIRUPDWLRQ LQ...
Proceedings Papers

Proc. ASME. IDETC-CIE2006, Volume 1: 32nd Design Automation Conference, Parts A and B, 291-300, September 10–13, 2006
Paper No: DETC2006-99189
... algorithm combining simulated annealing and a neural network is employed for collaborative optimization. The simulated annealing and neural network take turns in controlling the optimization processes, not only for maximizing the efficiency of global exploration, but also for minimizing the risks...