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Application of Artificial Neural Network in Predicting the Thickness of Chromizing Coatings on P110 Steel林乃明1,XIE Faqin2,ZOU Jiaojuan1,WANG Hefeng1,TANG Bin11. Research Institute of Surface... coatings were produced on P110 steel by pack cementation. The orthogonal array design (OAD) was applied to set the experiments. An artificial neural network (ANN) approach is employed to predict......
J. Cent. South Univ. (2016) 23: 2917-2925 DOI: 10.1007/s11771-016-3355-y Decentralized adaptive neural network sliding mode position/force control of constrained reconfigurable manipulators LI Yuan... Central South University Press and Springer-Verlag Berlin Heidelberg 2016 Abstract: A decentralized adaptive neural network sliding mode position/force control scheme is proposed for constrained......
J. Cent. South Univ. Technol. (2008) 15: 726-732 DOI: 10.1007/s11771-008-0134-4 A novel recurrent neural network forecasting model for power intelligence center LIU Ji-cheng(刘吉成), NIU Dong-xiao..., a novel unascertained mathematics based recurrent neural network (UMRNN) for power intelligence center (PIC) was created through three steps. First, by combining with the general project uncertain......
perfect fuel mass [17, 18]. The successful applications of artificial neural network in the combustion and emission control of the engines [19-21] provide a new way to solve these problems. It is well.... An artificial neural network developed for predicting of performance and emissions of a spark ignition engine fueled with butanol–gasoline blends [J]. Advances in Mechanical Engineering, 2018, 10(1......
data-mining ability of artificial neural network, the neural network model of the self-learning factor was used to investigate the effect of input parameters on heat transfer coefficient. By changing...J. Cent. South Univ. Technol. (2008) 15: 136-140 DOI: 10.1007/s11771-008-0027-6 Application of neural network to prediction of plate finish cooling temperature WANG Bing-xing......
Artificial neural network approach for prediction of stress–strain curve of near b titanium alloySrinivasu Gangi Setti,R.N.RaoMechanical Engineering, National Institute of Technology摘 要:In the present study, artificial neural network(ANN) approach was used to predict the stress–strain curve of near beta titanium alloy as a function of volume fractions......
Artificial neural network approach to assess selective flocculation on hematite and kaoliniteLopamudra Panda1,P.K.Banerjee1,Surendra Kumar Biswal2,R.Venugopal3,N.R.Mandre31. R&D Tata Steel Limited2... was investigated by Fourier transform infrared(FTIR) spectroscopy.A three-layer artificial neural network(ANN)model(4-4-3) was used to predict the separation performance of the process in terms of grade,Fe......
that of conventional back-propagation neural network with low mean absolute error.Key words:energy demand; artificial neural network; back-propagation algorithm; imperialist competitive algorithm... in an optimal manner without having accurate demand value. A new energy forecasting model was proposed based on the back-propagation (BP) type neural network and imperialist competitive algorithm. The proposed......
J. Cent. South Univ. (2018) 25: 2654-2663 DOI: https://doi.org/10.1007/s11771-018-3943-0 Adaptive neural network based sliding mode altitude control for a quadrotor UAV Hadi RAZMI Department... that the controller design for these quadrotors is considered the challenging issue of the day. In this work, an adaptive sliding mode controller based on neural network is proposed to control the altitude......
bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained...: 386-396. [38] RAMEZANI F, NIKOO M, NIKOO M. Artificial neural network weights optimization based on social-based algorithm to realize sediment over the river [J]. Soft Comput, 2015, 19(2): 375-387. [39......
