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Adomian decomposition method simulation of von Kármán swrling bioconvection nanofluid flow 被引量:2
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作者 M D SHAMSHUDDIN S R MISHRA +1 位作者 O ANWAR BEG A KADIR 《Journal of Central South University》 SCIE EI CAS CSCD 2019年第10期2797-2813,共17页
The study reveals analytically on the 3-dimensional viscous time-dependent gyrotactic bioconvection in swirling nanofluid flow past from a rotating disk.It is known that the deformation of the disk is along the radial... The study reveals analytically on the 3-dimensional viscous time-dependent gyrotactic bioconvection in swirling nanofluid flow past from a rotating disk.It is known that the deformation of the disk is along the radial direction.In addition to that Stefan blowing is considered.The Buongiorno nanofluid model is taken care of assuming the fluid to be dilute and we find Brownian motion and thermophoresis have dominant role on nanoscale unit.The primitive mass conservation equation,radial,tangential and axial momentum,heat,nano-particle concentration and micro-organism density function are developed in a cylindrical polar coordinate system with appropriate wall(disk surface)and free stream boundary conditions.This highly nonlinear,strongly coupled system of unsteady partial differential equations is normalized with the classical von Kármán and other transformations to render the boundary value problem into an ordinary differential system.The emerging 11th order system features an extensive range of dimensionless flow parameters,i.e.,disk stretching rate,Brownian motion,thermophoresis,bioconvection Lewis number,unsteadiness parameter,ordinary Lewis number,Prandtl number,mass convective Biot number,Péclet number and Stefan blowing parameter.Solutions of the system are obtained with developed semi-analytical technique,i.e.,Adomian decomposition method.Validation of the said problem is also conducted with earlier literature computed by Runge-Kutta shooting technique. 展开更多
关键词 nanofluids BIOCONVECTION rotating disk bioreactors von Kármán swirling flow Stefan blowing Adomian decomposition method(ADM)
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Efficient hybrid method for time reversal superresolution imaging 被引量:1
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作者 Xiaohua Wang Wei Gao Bingzhong Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2015年第1期32-37,共6页
An efficient hybrid time reversal(TR) imaging method based on signal subspace and noise subspace is proposed for electromagnetic superresolution detecting and imaging. First, the locations of targets are estimated b... An efficient hybrid time reversal(TR) imaging method based on signal subspace and noise subspace is proposed for electromagnetic superresolution detecting and imaging. First, the locations of targets are estimated by the transmitting-mode decomposition of the TR operator(DORT) method employing the signal subspace. Then, the TR multiple signal classification(TR-MUSIC)method employing the noise subspace is used in the estimated target area to get the superresolution imaging of targets. Two examples with homogeneous and inhomogeneous background mediums are considered, respectively. The results show that the proposed hybrid method has advantages in CPU time and memory cost because of the combination of rough and fine imaging. 展开更多
关键词 time reversal(TR) decomposition of the time-reversal operator(DORT) method multiple signal classification(MUSIC) method SUPERRESOLUTION IMAGING
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Solving large-scale multiclass learning problems via an efficient support vector classifier 被引量:1
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作者 Zheng Shuibo Tang Houjun +1 位作者 Han Zhengzhi Zhang Haoran 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2006年第4期910-915,共6页
Support vector machines (SVMs) are initially designed for binary classification. How to effectively extend them for multiclass classification is still an ongoing research topic. A multiclass classifier is constructe... Support vector machines (SVMs) are initially designed for binary classification. How to effectively extend them for multiclass classification is still an ongoing research topic. A multiclass classifier is constructed by combining SVM^light algorithm with directed acyclic graph SVM (DAGSVM) method, named DAGSVM^light A new method is proposed to select the working set which is identical to the working set selected by SVM^light approach. Experimental results indicate DAGSVM^light is competitive with DAGSMO. It is more suitable for practice use. It may be an especially useful tool for large-scale multiclass classification problems and lead to more widespread use of SVMs in the engineering community due to its good performance. 展开更多
关键词 support vector machines (SVMs) multiclass classification decomposition method SVM^light sequential minimal optimization (SMO).
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