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Keywords: Neural networks
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Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. July 2024, 24(7): 071002.
Paper No: JCISE-23-1152
Published Online: February 5, 2024
...] Wang , Y. , Gu , M. , Ma , J. , and Jin , Q. , 2019 , “ DNN-DP: Differential Privacy Enabled Deep Neural Network Learning Framework for Sensitive Crowdsourcing Data ,” IEEE Trans. Comput. Social Syst. , 7 ( 1 ), pp. 215 – 224 . 10.1109/TCSS.2019.2950017 [27] Kang , Y...
Journal Articles
Publisher: ASME
Article Type: Research Papers
J. Comput. Inf. Sci. Eng. January 2024, 24(1): 011008.
Paper No: JCISE-23-1067
Published Online: October 27, 2023
...Anar Nurizada; Anurag Purwar This paper focuses on the representation and synthesis of coupler curves of planar mechanisms using a deep neural network. While the path synthesis of planar mechanisms is not a new problem, the effective representation of coupler curves in the context of neural...
Journal Articles
Publisher: ASME
Article Type: Review Articles
J. Comput. Inf. Sci. Eng. December 2023, 23(6): 060811.
Paper No: JCISE-23-1055
Published Online: June 5, 2023
...Anurag Purwar; Nilanjan Chakraborty In this paper, we discuss the convergence of recent advances in deep neural networks (DNNs) with the design of robotic mechanisms, which entails the conceptualization of the design problem as a learning problem from the space of design specifications...
Journal Articles
Publisher: ASME
Article Type: Review Articles
J. Comput. Inf. Sci. Eng. March 2018, 18(1): 010801.
Paper No: JCISE-16-1045
Published Online: November 13, 2017
... manuscript received October 11, 2017; published online November 13, 2017. Assoc. Editor: Charlie C. L. Wang. 28 01 2016 11 10 2017 Neural networks Estimates suggest that ten million people on the earth at any one point in time suffer from the effects of a missing limb or body...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Comput. Inf. Sci. Eng. September 2017, 17(3): 031017.
Paper No: JCISE-16-2069
Published Online: July 26, 2017
... neural networks (ANNs) were used to predict assembly time and market value from assembly models. These models were converted into bipartite graphs from which 29 graph complexity metrics were extracted to train 18,900 ANN prediction models. The size of the training set, order of the bipartite graph...
Journal Articles
Publisher: ASME
Article Type: Technical Briefs
J. Comput. Inf. Sci. Eng. December 2009, 9(4): 044502.
Published Online: November 2, 2009
.... The progression of the “monitoring index” is predicted using the CI techniques, namely, recursive neural network (RNN), adaptive neurofuzzy inference system (ANFIS), and support vector regression (SVR). The proposed procedures have been evaluated through benchmark data sets for one-step-ahead prediction...
Journal Articles
Publisher: ASME
Article Type: Technical Papers
J. Comput. Inf. Sci. Eng. March 2002, 2(1): 38–44.
Published Online: June 5, 2002
... parameters for minimum springback. Currently, a vast majority of such applications in practice are guided by trial and error and user experience. In this paper, we present two useful designer aids; an evolutionary algorithm and a neural network integrated evolutionary algorithm. We have taken a simple...