The axial selection of tunnels constructed in the interlayered soft-hard rock mass affects the stability and safety during construction.Previous optimization is primarily based on experience or comparison and selectio...The axial selection of tunnels constructed in the interlayered soft-hard rock mass affects the stability and safety during construction.Previous optimization is primarily based on experience or comparison and selection of alternative values under specific geological conditions.In this work,an intelligent optimization framework has been proposed by combining numerical analysis,machine learning(ML)and optimization algorithm.An automatic and intelligent numerical analysis process was proposed and coded to reduce redundant manual intervention.The conventional optimization algorithm was developed from two aspects and applied to the hyperparameters estimation of the support vector machine(SVM)model and the axial orientation optimization of the tunnel.Finally,the comprehensive framework was applied to a numerical case study,and the results were compared with those of other studies.The results of this study indicate that the determination coefficients between the predicted and the numerical stability evaluation indices(STIs)on the training and testing datasets are 0.998 and 0.997,respectively.For a given geological condition,the STI that changes with the axial orientation shows the trend of first decreasing and then increasing,and the optimal tunnel axial orientation is estimated to be 87.This method provides an alternative and quick approach to the overall design of the tunnels.展开更多
A new method integrating support vector machine (SVM),particle swarm optimization (PSO) and chaotic mapping (CPSO-SVM) was proposed to predict the deformation of tunnel surrounding rock mass.Since chaotic mapping was ...A new method integrating support vector machine (SVM),particle swarm optimization (PSO) and chaotic mapping (CPSO-SVM) was proposed to predict the deformation of tunnel surrounding rock mass.Since chaotic mapping was featured by certainty,ergodicity and stochastic property,it was employed to improve the convergence rate and resulting precision of PSO.The chaotic PSO was adopted in the optimization of the appropriate SVM parameters,such as kernel function and training parameters,improving substantially the generalization ability of SVM.And finally,the integrating method was applied to predict the convergence deformation of the Xiakeng tunnel in China.The results indicate that the proposed method can describe the relationship of deformation time series well and is proved to be more efficient.展开更多
We investigate the massive vector particles' Hawking radiation from the neutral rotating Anti-de Sitter(AdS) black holes in conformal gravity by using the tunneling method.It is well known that the dynamics of mas...We investigate the massive vector particles' Hawking radiation from the neutral rotating Anti-de Sitter(AdS) black holes in conformal gravity by using the tunneling method.It is well known that the dynamics of massive vector particles are governed by the Proca field equation.Applying WKB approximation to the Proca equation,the tunneling probabilities and radiation spectrums of the emitted particles are derived.Hawking temperature of the neutral rotating AdS black holes in conformal gravity is recovered,which is consistent with the previous result in the literature.展开更多
The tunneling behavior of the Néel vector out of metastable easy directions or between degenerate easy directions is studied for a small single\|domain antiferromagnetic particle at low temperature. The quantum t...The tunneling behavior of the Néel vector out of metastable easy directions or between degenerate easy directions is studied for a small single\|domain antiferromagnetic particle at low temperature. The quantum tunneling rates for these processes are evaluated for two examples of macroscopic quantum tunneling and one example of macroscopic quantum coherence. The calculations are performed by using the two sublattice model and the instanton method in the spin coherent state path integral. Quantum interference or the spin parity effect is also discussed for each case.展开更多
The rapid detection of microparticles exhibits a broad range of applications in the field of science and technology. The proposed method differentiates and identifies the 2 μm and 5 μm sized particles using a laser ...The rapid detection of microparticles exhibits a broad range of applications in the field of science and technology. The proposed method differentiates and identifies the 2 μm and 5 μm sized particles using a laser light scattering. The detection method is based on measuring forward light scattering from the particles and then classifying the acquired data using support vector machines. The device is composed of a microfluidic chip linked with photosensors and a laser device using optical fiber. Connecting the photosensors and laser device using optical fibers makes the device more diminutive in size and portable. The prepared sample containing microspheres was passed through the channel, and the surrounding photosensors measured the scattered light. The time-domain features were evaluated from the acquired scattered light, and then the SVM classifier was trained to distinguish the particle’s data. The real-time detection of the particles was performed with an overall classification accuracy of 96.06%. The optimum conditions were evaluated to detect the particles with a minimum concentration of 0.2 μg/m L. The developed system is anticipated to be helpful in developing rapid testing devices for detecting pathogens ranging between 2 μm to 10 μm.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.51991392 and 51922104).
文摘The axial selection of tunnels constructed in the interlayered soft-hard rock mass affects the stability and safety during construction.Previous optimization is primarily based on experience or comparison and selection of alternative values under specific geological conditions.In this work,an intelligent optimization framework has been proposed by combining numerical analysis,machine learning(ML)and optimization algorithm.An automatic and intelligent numerical analysis process was proposed and coded to reduce redundant manual intervention.The conventional optimization algorithm was developed from two aspects and applied to the hyperparameters estimation of the support vector machine(SVM)model and the axial orientation optimization of the tunnel.Finally,the comprehensive framework was applied to a numerical case study,and the results were compared with those of other studies.The results of this study indicate that the determination coefficients between the predicted and the numerical stability evaluation indices(STIs)on the training and testing datasets are 0.998 and 0.997,respectively.For a given geological condition,the STI that changes with the axial orientation shows the trend of first decreasing and then increasing,and the optimal tunnel axial orientation is estimated to be 87.This method provides an alternative and quick approach to the overall design of the tunnels.
基金Project(NCET-08-0662)supported by Program for New Century Excellent Talents in University of ChinaProject(2010CB732006)supported by the Special Funds for the National Basic Research Program of ChinaProjects(51178187,41072224)supported by the National Natural Science Foundation of China
文摘A new method integrating support vector machine (SVM),particle swarm optimization (PSO) and chaotic mapping (CPSO-SVM) was proposed to predict the deformation of tunnel surrounding rock mass.Since chaotic mapping was featured by certainty,ergodicity and stochastic property,it was employed to improve the convergence rate and resulting precision of PSO.The chaotic PSO was adopted in the optimization of the appropriate SVM parameters,such as kernel function and training parameters,improving substantially the generalization ability of SVM.And finally,the integrating method was applied to predict the convergence deformation of the Xiakeng tunnel in China.The results indicate that the proposed method can describe the relationship of deformation time series well and is proved to be more efficient.
基金Supported by the National Natural Science Foundation of China under Grant No.11205048the Foundation for Young Key Teacher of Henan Normal University
文摘We investigate the massive vector particles' Hawking radiation from the neutral rotating Anti-de Sitter(AdS) black holes in conformal gravity by using the tunneling method.It is well known that the dynamics of massive vector particles are governed by the Proca field equation.Applying WKB approximation to the Proca equation,the tunneling probabilities and radiation spectrums of the emitted particles are derived.Hawking temperature of the neutral rotating AdS black holes in conformal gravity is recovered,which is consistent with the previous result in the literature.
文摘The tunneling behavior of the Néel vector out of metastable easy directions or between degenerate easy directions is studied for a small single\|domain antiferromagnetic particle at low temperature. The quantum tunneling rates for these processes are evaluated for two examples of macroscopic quantum tunneling and one example of macroscopic quantum coherence. The calculations are performed by using the two sublattice model and the instanton method in the spin coherent state path integral. Quantum interference or the spin parity effect is also discussed for each case.
基金supported by the Natural Science Youth Foundation of China (No. 61801307)the Scientific ResearchFund of the Shenzhen International Cooperation Projects (No.GJHZ20190819151403615)。
文摘The rapid detection of microparticles exhibits a broad range of applications in the field of science and technology. The proposed method differentiates and identifies the 2 μm and 5 μm sized particles using a laser light scattering. The detection method is based on measuring forward light scattering from the particles and then classifying the acquired data using support vector machines. The device is composed of a microfluidic chip linked with photosensors and a laser device using optical fiber. Connecting the photosensors and laser device using optical fibers makes the device more diminutive in size and portable. The prepared sample containing microspheres was passed through the channel, and the surrounding photosensors measured the scattered light. The time-domain features were evaluated from the acquired scattered light, and then the SVM classifier was trained to distinguish the particle’s data. The real-time detection of the particles was performed with an overall classification accuracy of 96.06%. The optimum conditions were evaluated to detect the particles with a minimum concentration of 0.2 μg/m L. The developed system is anticipated to be helpful in developing rapid testing devices for detecting pathogens ranging between 2 μm to 10 μm.
