While the random errors are a function of Gaussian random variables that are stationary and long dependent, we investigate a partially linear errors-in-variables（EV） model by the wavelet method. Under general condit...While the random errors are a function of Gaussian random variables that are stationary and long dependent, we investigate a partially linear errors-in-variables（EV） model by the wavelet method. Under general conditions, we obtain asymptotic representation of the parametric estimator, and asymptotic distributions and weak convergence rates of the parametric and nonparametric estimators. At last, the validity of the wavelet method is illuminated by a simulation example and a real example.展开更多
In this paper, we consider the partially nonlinear errors-in-variables models when the non- parametric component is measured with additive error. The profile nonlinear least squares estimator of unknown parameter and ...In this paper, we consider the partially nonlinear errors-in-variables models when the non- parametric component is measured with additive error. The profile nonlinear least squares estimator of unknown parameter and the estimator of nonparametric component are constructed, and their asymptotic properties are derived under general assumptions. Finite sample performances of the proposed statistical inference procedures are illustrated by Monte Carlo simulation studies.展开更多
The authors propose a V_(N,p) test statistic for testing finite-order serial correlation in asemiparametric varying coefficient partially linear errors-in-variables model.The test statistic is shownto have asymptotic ...The authors propose a V_(N,p) test statistic for testing finite-order serial correlation in asemiparametric varying coefficient partially linear errors-in-variables model.The test statistic is shownto have asymptotic normal distribution under the null hypothesis of no serial correlation.Some MonteCarlo experiments are conducted to examine the finite sample performance of the proposed V_(N,p) teststatistic.Simulation results confirm that the proposed test performs satisfactorily in estimated sizeand power.展开更多
The multivariate linear errors-in-variables model when the regressors are missing at random in the sense of Rubin （1976） is considered in this paper. A constrained empirical likelihood confidence region for a parame...The multivariate linear errors-in-variables model when the regressors are missing at random in the sense of Rubin （1976） is considered in this paper. A constrained empirical likelihood confidence region for a parameter β0 in this model is proposed, which is constructed by combining the score function corresponding to the weighted squared orthogonal distance based on inverse probability with a constrained region of β0. It is shown that the empirical log-likelihood ratio at the true parameter converges to the standard chi-square distribution. Simulations show that the coverage rate of the proposed confidence region is closer to the nominal level and the length of confidence interval is narrower than those of the normal approximation of inverse probability weighted adjusted least square estimator in most cases. A real example is studied and the result supports the theory and simulation＇s conclusion.展开更多
The purpose of this paper is two fold. First, we investigate estimation for varying coefficient partially linear models in which covariates in the nonparametric part are measured with errors. As there would be some sp...The purpose of this paper is two fold. First, we investigate estimation for varying coefficient partially linear models in which covariates in the nonparametric part are measured with errors. As there would be some spurious covariates in the linear part, a penalized profile least squares estimation is suggested with the assistance from smoothly clipped absolute deviation penalty. However, the estimator is often biased due to the existence of measurement errors, a bias correction is proposed such that the estimation consistency with the oracle property is proved. Second, based on the estimator, a test statistic is constructed to check a linear hypothesis of the parameters and its asymptotic properties are studied. We prove that the existence of measurement errors causes intractability of the limiting null distribution that requires a Monte Carlo approximation and the absence of the errors can lead to a chi-square limit. Furthermore, confidence regions of the parameter of interest can also be constructed. Simulation studies and a real data example are conducted to examine the performance of our estimators and test statistic.展开更多
A kind of partially linear errors-in-variables models with replicated net points of observation are studied in this paper. Estimators of unknown parameters are given. Under certain regular conditions, it is shown that...A kind of partially linear errors-in-variables models with replicated net points of observation are studied in this paper. Estimators of unknown parameters are given. Under certain regular conditions, it is shown that the estimators of the unknown parameters are strongly consistent and their a.s. convergence rates are achieved.展开更多
The authors consider the partially linear model relating a response Y to predictors （x, T） with a mean function x^Tβ0 ＋ g（T） when the x＇s are measured with an additive error. The estimators of parameter β0 are...The authors consider the partially linear model relating a response Y to predictors （x, T） with a mean function x^Tβ0 ＋ g（T） when the x＇s are measured with an additive error. The estimators of parameter β0 are derived by using the nearest neighbor-generalized randomly weighted least absolute deviation （LAD for short） method. The resulting estimator of the unknown vector 30 is shown to be consistent and asymptotically normal. In addition, the results facilitate the construction of confidence regions and the hypothesis testing for the unknown parameters. Extensive simulations are reported, showing that the proposed method works well in practical settings. The proposed methods are also applied to a data set from the study of an AIDS clinical trial group.展开更多
This paper studies the parameter estimation of multiple dimensional linear errors-in-variables (EV) models in the case where replicated observations are available in some experimental points. Asymptotic normality is e...This paper studies the parameter estimation of multiple dimensional linear errors-in-variables (EV) models in the case where replicated observations are available in some experimental points. Asymptotic normality is established under mild conditions, and the parameters entering the asymptotic variance are consistently estimated to render the result useable in the construction of large-sample confidence regions.展开更多
Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression mo...Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression model and the least squares （LS） method will result in bias. Based on the models of inertial navigation platform error and observation error, the errors-in-variables （EV） model and the total least squares （TLS） method axe proposed to identify the error model of the inertial navigation platform. The estimation precision is improved and the result is better than the conventional regression model based LS method. The simulation results illustrate the effectiveness of the proposed method.展开更多
The study of the mechanical property and damage state of coal materials under compression is a fundamental area of research in underground mining engineering.Drawing upon the compaction effect and linear energy dissip...The study of the mechanical property and damage state of coal materials under compression is a fundamental area of research in underground mining engineering.Drawing upon the compaction effect and linear energy dissipation(LED)law,a novel compressive damage constitutive model for brittle coal is proposed.Utilizing the energy-defined damage method for mate-rials,the LED law is innovatively introduced to accurately characterize the energy dissipation during the loading process,and a novel formula for characterizing the damage variable of brittle coal is proposed.On this basis,considering that the constitutive model based on the hypothesis of strain equivalence is incapable of accurately describing the compaction effect exhibited by coal material during the compression process,a correction coefficient is proposed and apply it in the novel damage constitutive model.The established conventional monotone loading and single-cyclic loading-unloading uniaxial compression damage constitutive models have been validated using experimental data from cylindrical and cuboid coal specimens.In addition,compared with the constitutive model obtained via the traditional energy calculation method based on the hypothesis that the unloading curve is a straight line,the constitutive model employing LED law can describe the stress-strain state of brittle coal more precisely.This approach introduces a new perspective and enhances the convenience for constructing the constitutive model based on energy theory.展开更多
The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of ...The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.展开更多
Linear flux-switching permanent magnet motors(LFSPMs) have been proposed for long stator applications such as rail transit. However, the conventional linear permanent magnet synchronous motor(LPMSM) suffers from thrus...Linear flux-switching permanent magnet motors(LFSPMs) have been proposed for long stator applications such as rail transit. However, the conventional linear permanent magnet synchronous motor(LPMSM) suffers from thrust ripple, which degrades the motor performance. The thrust ripple in LFSPMs is mainly caused by detent force and asymmetric electromagnetic parameters, excluding external disturbances. Moreover, the 12/13 slot-pole LFSPM exhibits unique inductance characteristics, which lead to different effects on thrust ripple. First, the detent force in the LFSPM is analyzed through finite element method(FEM). In addition, new finite element(FE) models are proposed for further analysis of the cogging force in LFSPMs. Second, the unique inductance characteristics of the 12/13 slot-pole LFSPM are investigated, and then the thrust ripple caused by asymmetric electromagnetic parameters is calculated by the virtual displacement method. Third, the mathematical model considering the thrust ripple is established for the LFSPM, which provides a foundation for subsequent research on thrust ripple suppression control strategies. Finally, the thrust ripple analysis is validated by comparing FEM results, modeling simulations, and experimental data.展开更多
We study the thermodynamic properties of the classical one-dimensional generalized nonlinear Klein-Gordon lattice model(n≥2)by using the cluster variation method with linear response theory.The results of this method...We study the thermodynamic properties of the classical one-dimensional generalized nonlinear Klein-Gordon lattice model(n≥2)by using the cluster variation method with linear response theory.The results of this method are exact in the thermodynamic limit.We present the single-site reduced densityρ^((1))(z),averages such as(z^(2)),<|z^(n)|>,and<(z_(1)-z_(2))^(2)>,the specific heat C_(v),and the static correlation functions.We analyze the scaling behavior of these quantities and obtain the exact scaling powers at the low and high temperatures.Using these results,we gauge the accuracy of the projective truncation approximation for theφ^(4)lattice model.展开更多
Natural soil generally exhibits significant transverse isotropy(TI)due to weathering and sedimentation,meaning that horizontal moduli differ from their vertical counterpart.The TI mechanical model is more appropriate ...Natural soil generally exhibits significant transverse isotropy(TI)due to weathering and sedimentation,meaning that horizontal moduli differ from their vertical counterpart.The TI mechanical model is more appropriate for actual situations.Although soil exhibits material nonlinearity under earthquake excitation,existing research on the TI medium is limited to soil linearity and neglects the nonlinear response of TI sites.A 2D equivalent linear model for a layered TI half-space subjected to seismic waves is derived in the transformed wave number domain using the exact dynamic stiffness matrix of the TI medium.This study introduces a method for determining the effective shear strain of TI sites under oblique wave incidence,and further describes a systematic study on the effects of TI parameters and soil nonlinearity on site responses.Numerical results indicate that seismic responses of the TI medium significantly differ from those of isotropic sites and that the responses are highly dependent on TI parameters,particularly in nonlinear cases,while also being sensitive to incident angle and excitation intensity.Moreover,the differences in peak acceleration and waveform for various TI materials may also be amplified due to the strong nonlinearity.The study provides valuable insights for improving the accuracy of seismic response analysis in engineering applications.展开更多
Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol ...Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).展开更多
The FRF estimator based on the errors-in-variables(EV)model of multi-input multi-output(MIMO)system is presented to reduce the bias error of FRF HI estimator.The FRF HI estimator is influenced by the noises in the inp...The FRF estimator based on the errors-in-variables(EV)model of multi-input multi-output(MIMO)system is presented to reduce the bias error of FRF HI estimator.The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF.The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation.The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF(degree-of-freedom)hydraulic vibration table.The result shows that it is favorable to improve the control precision of the MIMO vibration control system.展开更多
Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, incl...Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, including ACID-compliant, concurrency support, data sharing, and efficient access. Each block model is organized by linear octree, stored in LMDB（lightning memory-mapped database）. Geological attribute can be queried at any point of 3D space by comparison algorithm of location code and conversion algorithm from address code of geometry space to location code of storage. The performance and robustness of querying geological attribute at 3D spatial region are enhanced greatly by the transformation from 3D to 2D and the method of 2D grid scanning to screen the inner and outer points. Experimental results showed that this method can access the massive data of block model, meeting the database characteristics. The method with LMDB is at least 3 times faster than that with etree, especially when it is used to read. In addition, the larger the amount of data is processed, the more efficient the method would be.展开更多
A unified breakdown model of SOI RESURF device with uniform,step,or linear drift region doping profile is firstly proposed.By the model,the electric field distribution and breakdown voltage are researched in detail fo...A unified breakdown model of SOI RESURF device with uniform,step,or linear drift region doping profile is firstly proposed.By the model,the electric field distribution and breakdown voltage are researched in detail for the step numbers from 0 to infinity.The critic electric field as the function of the geometry parameters and doping profile is derived.For the thick film device,linear doping profile can be replaced by a single or two steps doping profile in the drift region due to a considerable uniformly lateral electric field,almost ideal breakdown voltage,and simplified design and fabrication.The availability of the proposed model is verified by the good accordance among the analytical results,numerical simulations,and reported experiments.展开更多
In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias es...In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.展开更多
基金Supported by the National Natural Science Foundation of China(No.11471105,11471223)Scientific Research Item of Education Office,Hubei(No.D20172501)
文摘While the random errors are a function of Gaussian random variables that are stationary and long dependent, we investigate a partially linear errors-in-variables（EV） model by the wavelet method. Under general conditions, we obtain asymptotic representation of the parametric estimator, and asymptotic distributions and weak convergence rates of the parametric and nonparametric estimators. At last, the validity of the wavelet method is illuminated by a simulation example and a real example.
基金Supported by National Natural Science Foundation of China(Grant Nos.11101014 and 11002005)the Beijing Natural Science Foundation(Grant No.1142002)+2 种基金the Doctoral Fund of Innovation of Beijing Universityof Technologythe Science and Technology Project of Beijing Municipal Education Commission(Grant No.KM201410005010)the Training Programme Foundation for the Beijing Municipal Excellent Talents(GrantNo.2013D005007000005)
文摘In this paper, we consider the partially nonlinear errors-in-variables models when the non- parametric component is measured with additive error. The profile nonlinear least squares estimator of unknown parameter and the estimator of nonparametric component are constructed, and their asymptotic properties are derived under general assumptions. Finite sample performances of the proposed statistical inference procedures are illustrated by Monte Carlo simulation studies.
基金supported by the National Natural Science Foundation of China under Grant Nos. 10871217 and 40574003the Science and Technology Project of Chongqing Education Committee under Grant No. KJ080609+1 种基金the Doctor's Start-up Research Fund under Grant No. 08-52204the Youth Science Research Fund of Chongging Technology and Business University under Grant No. 0852008
文摘The authors propose a V_(N,p) test statistic for testing finite-order serial correlation in asemiparametric varying coefficient partially linear errors-in-variables model.The test statistic is shownto have asymptotic normal distribution under the null hypothesis of no serial correlation.Some MonteCarlo experiments are conducted to examine the finite sample performance of the proposed V_(N,p) teststatistic.Simulation results confirm that the proposed test performs satisfactorily in estimated sizeand power.
基金supported by the Natural Science Foundation of China under Grant Nos.10771017 and 11071022Key Project of MOE,PRC under Grant No.309007
文摘The multivariate linear errors-in-variables model when the regressors are missing at random in the sense of Rubin （1976） is considered in this paper. A constrained empirical likelihood confidence region for a parameter β0 in this model is proposed, which is constructed by combining the score function corresponding to the weighted squared orthogonal distance based on inverse probability with a constrained region of β0. It is shown that the empirical log-likelihood ratio at the true parameter converges to the standard chi-square distribution. Simulations show that the coverage rate of the proposed confidence region is closer to the nominal level and the length of confidence interval is narrower than those of the normal approximation of inverse probability weighted adjusted least square estimator in most cases. A real example is studied and the result supports the theory and simulation＇s conclusion.
基金supported by National Natural Science Foundation of China (Grant Nos. 11401006, 11671299 and 11671042)a grant from the University Grants Council of Hong Kong+1 种基金the China Postdoctoral Science Foundation (Grant No. 2017M611083)the National Statistical Science Research Program of China (Grant No. 2015LY55)
文摘The purpose of this paper is two fold. First, we investigate estimation for varying coefficient partially linear models in which covariates in the nonparametric part are measured with errors. As there would be some spurious covariates in the linear part, a penalized profile least squares estimation is suggested with the assistance from smoothly clipped absolute deviation penalty. However, the estimator is often biased due to the existence of measurement errors, a bias correction is proposed such that the estimation consistency with the oracle property is proved. Second, based on the estimator, a test statistic is constructed to check a linear hypothesis of the parameters and its asymptotic properties are studied. We prove that the existence of measurement errors causes intractability of the limiting null distribution that requires a Monte Carlo approximation and the absence of the errors can lead to a chi-square limit. Furthermore, confidence regions of the parameter of interest can also be constructed. Simulation studies and a real data example are conducted to examine the performance of our estimators and test statistic.
基金Supported by the National Natural Science Foundation of China(No.90104034,No.60373041).
文摘A kind of partially linear errors-in-variables models with replicated net points of observation are studied in this paper. Estimators of unknown parameters are given. Under certain regular conditions, it is shown that the estimators of the unknown parameters are strongly consistent and their a.s. convergence rates are achieved.
文摘The authors consider the partially linear model relating a response Y to predictors （x, T） with a mean function x^Tβ0 ＋ g（T） when the x＇s are measured with an additive error. The estimators of parameter β0 are derived by using the nearest neighbor-generalized randomly weighted least absolute deviation （LAD for short） method. The resulting estimator of the unknown vector 30 is shown to be consistent and asymptotically normal. In addition, the results facilitate the construction of confidence regions and the hypothesis testing for the unknown parameters. Extensive simulations are reported, showing that the proposed method works well in practical settings. The proposed methods are also applied to a data set from the study of an AIDS clinical trial group.
基金This project is supported by the National Natural Science Foundation of China (No.19631040)
文摘This paper studies the parameter estimation of multiple dimensional linear errors-in-variables (EV) models in the case where replicated observations are available in some experimental points. Asymptotic normality is established under mild conditions, and the parameters entering the asymptotic variance are consistently estimated to render the result useable in the construction of large-sample confidence regions.
基金supported by the National Security Major Basic Research Project of China (973-61334).
文摘Because the real input acceleration cannot be obtained during the error model identification of inertial navigation platform, both the input and output data contain noises. In this case, the conventional regression model and the least squares （LS） method will result in bias. Based on the models of inertial navigation platform error and observation error, the errors-in-variables （EV） model and the total least squares （TLS） method axe proposed to identify the error model of the inertial navigation platform. The estimation precision is improved and the result is better than the conventional regression model based LS method. The simulation results illustrate the effectiveness of the proposed method.
基金supported by the National Science Fund for Distinguished Young Scholars(52225403)the National Natural Science Foundation of China(42077244).
文摘The study of the mechanical property and damage state of coal materials under compression is a fundamental area of research in underground mining engineering.Drawing upon the compaction effect and linear energy dissipation(LED)law,a novel compressive damage constitutive model for brittle coal is proposed.Utilizing the energy-defined damage method for mate-rials,the LED law is innovatively introduced to accurately characterize the energy dissipation during the loading process,and a novel formula for characterizing the damage variable of brittle coal is proposed.On this basis,considering that the constitutive model based on the hypothesis of strain equivalence is incapable of accurately describing the compaction effect exhibited by coal material during the compression process,a correction coefficient is proposed and apply it in the novel damage constitutive model.The established conventional monotone loading and single-cyclic loading-unloading uniaxial compression damage constitutive models have been validated using experimental data from cylindrical and cuboid coal specimens.In addition,compared with the constitutive model obtained via the traditional energy calculation method based on the hypothesis that the unloading curve is a straight line,the constitutive model employing LED law can describe the stress-strain state of brittle coal more precisely.This approach introduces a new perspective and enhances the convenience for constructing the constitutive model based on energy theory.
基金supported by the National Key Program for Developing Basic Science(Nos.2022YFF0801702 and 2022YFE0106600)the National Natural Science Foundation of China(Nos.42175060 and 42175021)the Jiangsu Province Science Foundation(No.BK20250200302).
文摘The Madden-Julian Oscillation(MJO)is a key atmospheric component connecting global weather and climate.It func-tions as a primary source for subseasonal forecasts.Previous studies have highlighted the vital impact of oceanic processes on MJO propagation.However,few existing MJO prediction approaches adequately consider these factors.This study determines the critical region for the oceanic processes affecting MJO propagation by utilizing 22-year Climate Forecast System Reanalysis data.By intro-ducing surface and subsurface oceanic temperature within this critical region into a lagged multiple linear regression model,the MJO forecasting skill is considerably optimized.This optimization leads to a 12 h enhancement in the forecasting skill of the first principal component and efficiently decreases prediction errors for the total predictions.Further analysis suggests that,during the years in which MJO events propagate across the Maritime Continent over a more southerly path,the optimized statistical forecasting model obtains better improvements in MJO prediction.
基金partly supported by the CAS Project for Young Scientists in Basic Research under Grant YSBR-045the National Natural Science Foundation of China under Grant 52307071。
文摘Linear flux-switching permanent magnet motors(LFSPMs) have been proposed for long stator applications such as rail transit. However, the conventional linear permanent magnet synchronous motor(LPMSM) suffers from thrust ripple, which degrades the motor performance. The thrust ripple in LFSPMs is mainly caused by detent force and asymmetric electromagnetic parameters, excluding external disturbances. Moreover, the 12/13 slot-pole LFSPM exhibits unique inductance characteristics, which lead to different effects on thrust ripple. First, the detent force in the LFSPM is analyzed through finite element method(FEM). In addition, new finite element(FE) models are proposed for further analysis of the cogging force in LFSPMs. Second, the unique inductance characteristics of the 12/13 slot-pole LFSPM are investigated, and then the thrust ripple caused by asymmetric electromagnetic parameters is calculated by the virtual displacement method. Third, the mathematical model considering the thrust ripple is established for the LFSPM, which provides a foundation for subsequent research on thrust ripple suppression control strategies. Finally, the thrust ripple analysis is validated by comparing FEM results, modeling simulations, and experimental data.
基金supported by the National Natural Science Foundation of China(Grant No.11974420).
文摘We study the thermodynamic properties of the classical one-dimensional generalized nonlinear Klein-Gordon lattice model(n≥2)by using the cluster variation method with linear response theory.The results of this method are exact in the thermodynamic limit.We present the single-site reduced densityρ^((1))(z),averages such as(z^(2)),<|z^(n)|>,and<(z_(1)-z_(2))^(2)>,the specific heat C_(v),and the static correlation functions.We analyze the scaling behavior of these quantities and obtain the exact scaling powers at the low and high temperatures.Using these results,we gauge the accuracy of the projective truncation approximation for theφ^(4)lattice model.
基金National Natural Science Foundation of China under Grant No.U2139208。
文摘Natural soil generally exhibits significant transverse isotropy(TI)due to weathering and sedimentation,meaning that horizontal moduli differ from their vertical counterpart.The TI mechanical model is more appropriate for actual situations.Although soil exhibits material nonlinearity under earthquake excitation,existing research on the TI medium is limited to soil linearity and neglects the nonlinear response of TI sites.A 2D equivalent linear model for a layered TI half-space subjected to seismic waves is derived in the transformed wave number domain using the exact dynamic stiffness matrix of the TI medium.This study introduces a method for determining the effective shear strain of TI sites under oblique wave incidence,and further describes a systematic study on the effects of TI parameters and soil nonlinearity on site responses.Numerical results indicate that seismic responses of the TI medium significantly differ from those of isotropic sites and that the responses are highly dependent on TI parameters,particularly in nonlinear cases,while also being sensitive to incident angle and excitation intensity.Moreover,the differences in peak acceleration and waveform for various TI materials may also be amplified due to the strong nonlinearity.The study provides valuable insights for improving the accuracy of seismic response analysis in engineering applications.
基金supported by the National Nature Science Foundation of China(U21A20166)the Science and Technology Development Foundation of Jilin Province(20230508095RC)+2 种基金the Major Science and Technology Projects of Jilin Province and Changchun City(20220301033GX)the Development and Reform Commission Foundation of Jilin Province(2023C034-3)the Interdisciplinary Integration and Innovation Project of JLU(JLUXKJC2020202).
文摘Dear Editor,Aiming at the consensus tracking problem of a class of unknown heterogeneous nonlinear multiagent systems(MASs)with input constraints,a novel data-driven iterative learning consensus control(ILCC)protocol based on zeroing neural networks(ZNNs)is proposed.First,a dynamic linearization data model(DLDM)is acquired via dynamic linearization technology(DLT).
基金This project is supported by Program for New Century Excellent Talents in University,China(No.NCET-04-0325).
文摘The FRF estimator based on the errors-in-variables(EV)model of multi-input multi-output(MIMO)system is presented to reduce the bias error of FRF HI estimator.The FRF HI estimator is influenced by the noises in the inputs of the system and generates an under-estimation of the true FRF.The FRF estimator based on the EV model takes into account the errors in both the inputs and outputs of the system and would lead to more accurate FRF estimation.The FRF estimator based on the EV model is applied to the waveform replication on the 6-DOF(degree-of-freedom)hydraulic vibration table.The result shows that it is favorable to improve the control precision of the MIMO vibration control system.
基金Projects(41572317,51374242)supported by the National Natural Science Foundation of ChinaProject(2015CX005)supported by the Innovation Driven Plan of Central South University,China
文摘Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, including ACID-compliant, concurrency support, data sharing, and efficient access. Each block model is organized by linear octree, stored in LMDB（lightning memory-mapped database）. Geological attribute can be queried at any point of 3D space by comparison algorithm of location code and conversion algorithm from address code of geometry space to location code of storage. The performance and robustness of querying geological attribute at 3D spatial region are enhanced greatly by the transformation from 3D to 2D and the method of 2D grid scanning to screen the inner and outer points. Experimental results showed that this method can access the massive data of block model, meeting the database characteristics. The method with LMDB is at least 3 times faster than that with etree, especially when it is used to read. In addition, the larger the amount of data is processed, the more efficient the method would be.
文摘A unified breakdown model of SOI RESURF device with uniform,step,or linear drift region doping profile is firstly proposed.By the model,the electric field distribution and breakdown voltage are researched in detail for the step numbers from 0 to infinity.The critic electric field as the function of the geometry parameters and doping profile is derived.For the thick film device,linear doping profile can be replaced by a single or two steps doping profile in the drift region due to a considerable uniformly lateral electric field,almost ideal breakdown voltage,and simplified design and fabrication.The availability of the proposed model is verified by the good accordance among the analytical results,numerical simulations,and reported experiments.
文摘In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.
