期刊文献+
共找到419篇文章
< 1 2 21 >
每页显示 20 50 100
Time-varying parameters estimation with adaptive neural network EKF for missile-dual control system
1
作者 YUAN Yuqi ZHOU Di +1 位作者 LI Junlong LOU Chaofei 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第2期451-462,共12页
In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LST... In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LSTM) neural network is nested into the extended Kalman filter(EKF) to modify the Kalman gain such that the filtering performance is improved in the presence of large model uncertainties. To avoid the unstable network output caused by the abrupt changes of system states,an adaptive correction factor is introduced to correct the network output online. In the process of training the network, a multi-gradient descent learning mode is proposed to better fit the internal state of the system, and a rolling training is used to implement an online prediction logic. Based on the Lyapunov second method, we discuss the stability of the system, the result shows that when the training error of neural network is sufficiently small, the system is asymptotically stable. With its application to the estimation of time-varying parameters of a missile dual control system, the LSTM-EKF shows better filtering performance than the EKF and adaptive EKF(AEKF) when there exist large uncertainties in the system model. 展开更多
关键词 long-short-term memory(LSTM)neural network extended Kalman filter(EKF) rolling training time-varying parameters estimation missile dual control system
下载PDF
Runoff Modeling in Ungauged Catchments Using Machine Learning Algorithm-Based Model Parameters Regionalization Methodology 被引量:1
2
作者 Houfa Wu Jianyun Zhang +4 位作者 Zhenxin Bao Guoqing Wang Wensheng Wang Yanqing Yang Jie Wang 《Engineering》 SCIE EI CAS CSCD 2023年第9期93-104,共12页
Model parameters estimation is a pivotal issue for runoff modeling in ungauged catchments.The nonlinear relationship between model parameters and catchment descriptors is a major obstacle for parameter regionalization... Model parameters estimation is a pivotal issue for runoff modeling in ungauged catchments.The nonlinear relationship between model parameters and catchment descriptors is a major obstacle for parameter regionalization,which is the most widely used approach.Runoff modeling was studied in 38 catchments located in the Yellow–Huai–Hai River Basin(YHHRB).The values of the Nash–Sutcliffe efficiency coefficient(NSE),coefficient of determination(R2),and percent bias(PBIAS)indicated the acceptable performance of the soil and water assessment tool(SWAT)model in the YHHRB.Nine descriptors belonging to the categories of climate,soil,vegetation,and topography were used to express the catchment characteristics related to the hydrological processes.The quantitative relationships between the parameters of the SWAT model and the catchment descriptors were analyzed by six regression-based models,including linear regression(LR)equations,support vector regression(SVR),random forest(RF),k-nearest neighbor(kNN),decision tree(DT),and radial basis function(RBF).Each of the 38 catchments was assumed to be an ungauged catchment in turn.Then,the parameters in each target catchment were estimated by the constructed regression models based on the remaining 37 donor catchments.Furthermore,the similaritybased regionalization scheme was used for comparison with the regression-based approach.The results indicated that the runoff with the highest accuracy was modeled by the SVR-based scheme in ungauged catchments.Compared with the traditional LR-based approach,the accuracy of the runoff modeling in ungauged catchments was improved by the machine learning algorithms because of the outstanding capability to deal with nonlinear relationships.The performances of different approaches were similar in humid regions,while the advantages of the machine learning techniques were more evident in arid regions.When the study area contained nested catchments,the best result was calculated with the similarity-based parameter regionalization scheme because of the high catchment density and short spatial distance.The new findings could improve flood forecasting and water resources planning in regions that lack observed data. 展开更多
关键词 parameters estimation Ungauged catchments Regionalization scheme Machine learning algorithms Soil and water assessment tool model
下载PDF
An improved bidirectional generative adversarial network model for multivariate estimation of correlated and imbalanced tunnel construction parameters
3
作者 Yao Xiao Jia Yu +3 位作者 Guoxin Xu Dawei Tong Jiahao Yu Tuocheng Zeng 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2023年第7期1797-1809,共13页
Estimation of construction parameters is crucial for optimizing tunnel construction schedule.Due to the influence of routine activities and occasional risk events,these parameters are usually correlated and imbalanced... Estimation of construction parameters is crucial for optimizing tunnel construction schedule.Due to the influence of routine activities and occasional risk events,these parameters are usually correlated and imbalanced.To solve this issue,an improved bidirectional generative adversarial network(BiGAN)model with a joint discriminator structure and zero-centered gradient penalty(0-GP)is proposed.In this model,in order to improve the capability of original BiGAN in learning imbalanced parameters,the joint discriminator separately discriminates the routine activities and risk event durations to balance their influence weights.Then,the self-attention mechanism is embedded so that the discriminator can pay more attention to the imbalanced parameters.Finally,the 0-GP is adapted for the loss of the discrimi-nator to improve its convergence and stability.A case study of a tunnel in China shows that the improved BiGAN can obtain parameter estimates consistent with the classical Gauss mixture model,without the need of tedious and complex correlation analysis.The proposed joint discriminator can increase the ability of BiGAN in estimating imbalanced construction parameters,and the 0-GP can ensure the stability and convergence of the model. 展开更多
关键词 Multivariate parameters estimation Correlated and imbalanced parameters Bidirectional generative adversarial network(BiGAN) Joint discriminator Zero-centered gradient penalty(0-GP)
下载PDF
Algorithms for automatic measurement of SIS-type hysteretic underdamped Josephson junction’s parameters by current-voltage characteristics
4
作者 Aleksey G.Vostretsov Svetlana G.Filatova 《Journal of Electronic Science and Technology》 EI CSCD 2023年第4期60-74,共15页
Some electrical parameters of the SIS-type hysteretic underdamped Josephson junction(JJ)can be measured by its current-voltage characteristics(IVCs).Currents and voltages at JJ are commensurate with the intrinsic nois... Some electrical parameters of the SIS-type hysteretic underdamped Josephson junction(JJ)can be measured by its current-voltage characteristics(IVCs).Currents and voltages at JJ are commensurate with the intrinsic noise level of measuring instruments.This leads to the need for multiple measurements with subsequent statistical processing.In this paper,the digital algorithms are proposed for the automatic measurement of the JJ parameters by IVC.These algorithms make it possible to implement multiple measurements and check these JJ parameters in an automatic mode with the required accuracy.The complete sufficient statistics are used to minimize the root-mean-square error of parameter measurement.A sequence of current pulses with slow rising and falling edges is used to drive JJ,and synchronous current and voltage readings at JJ are used to realize measurement algorithms.The algorithm performance is estimated through computer simulations.The significant advantage of the proposed algorithms is the independence from current source noise and intrinsic noise of current and voltage meters,as well as the simple implementation in automatic digital measuring systems.The proposed algorithms can be used to control JJ parameters during mass production of superconducting integrated circuits,which will improve the production efficiency and product quality. 展开更多
关键词 Algorithm design and analysis Critical current Current-voltage characteristics(IVCs) Josephson junction(JJ) Measurement errors Parameter estimation
下载PDF
Parameter Estimation of a Valve-Controlled Cylinder System Model Based on Bench Test and Operating Data Fusion
5
作者 Deying Su Shaojie Wang +3 位作者 Haojing Lin Xiaosong Xia Yubing Xu Liang Hou 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第2期247-263,共17页
The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual ... The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder system.Despite the actual load information contained in the operating data of the control valve,its acquisition remains challenging.This paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned problems.The proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating data.Firstly,a system model is established,and the parameters in the model are analysed.Secondly,the bench and operating data of the system are collected.Then,the model parameters and weight coefficients are estimated using the data fusion method.Finally,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are compared.The research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation result.The effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO algorithm.Increasing load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies. 展开更多
关键词 Valve-controlled cylinder system Parameter estimation The Bayesian theory Data fusion method Weight coefficients
下载PDF
A unified Minorization-Maximization approach for estimation of general mixture models
6
作者 HUANG Xi-fen LIU Deng-ge +1 位作者 ZHOU Yun-peng ZHU Fei 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2024年第2期343-362,共20页
The mixed distribution model is often used to extract information from heteroge-neous data and perform modeling analysis.When the density function of mixed distribution is complicated or the variable dimension is high... The mixed distribution model is often used to extract information from heteroge-neous data and perform modeling analysis.When the density function of mixed distribution is complicated or the variable dimension is high,it usually brings challenges to the parameter es-timation of the mixed distribution model.The application of MM algorithm can avoid complex expectation calculations,and can also solve the problem of high-dimensional optimization by decomposing the objective function.In this paper,MM algorithm is applied to the parameter estimation problem of mixed distribution model.The method of assembly and decomposition is used to construct the substitute function with separable parameters,which avoids the problems of complex expectation calculations and the inversion of high-dimensional matrices. 展开更多
关键词 MM algorithm mixed distribution model parameter estimation assembly decomposition tech-nology parameter separation
下载PDF
Model-driven full system dynamics estimation of PMSM-driven chain shell magazine
7
作者 Kai Wei Longmiao Chen Quan Zou 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第9期147-156,共10页
Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is pro... Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals. 展开更多
关键词 Chain shell magazine Full system dynamics estimation Disturbance estimation Parameter estimation Adaptive extended state observer
下载PDF
Parameter estimation in n-dimensional massless scalar field
8
作者 杨颖 荆继良 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第3期231-237,共7页
Quantum Fisher information(QFI)associated with local metrology has been used to parameter estimation in open quantum systems.In this work,we calculated the QFI for a moving Unruh-DeWitt detector coupled with massless ... Quantum Fisher information(QFI)associated with local metrology has been used to parameter estimation in open quantum systems.In this work,we calculated the QFI for a moving Unruh-DeWitt detector coupled with massless scalar fields in n-dimensional spacetime,and analyzed the behavior of QFI with various parameters,such as the dimension of spacetime,evolution time,and Unruh temperature.We discovered that the QFI of state parameter decreases monotonically from 1 to 0 over time.Additionally,we noted that the QFI for small evolution times is several orders of magnitude higher than the QFI for long evolution times.We also found that the value of QFI decreases at first and then stabilizes as the Unruh temperature increases.It was observed that the QFI depends on initial state parameterθ,and Fθis the maximum forθ=0 orθ=π,Fφis the maximum forθ=π/2.We also obtain that the maximum value of QFI for state parameters varies for different spacetime dimensions with the same evolution time. 展开更多
关键词 quantum Fisher information parameter estimation open quantum systems
下载PDF
Intelligent recognition and information extraction of radar complex jamming based on time-frequency features
9
作者 PENG Ruihui WU Xingrui +3 位作者 WANG Guohong SUN Dianxing YANG Zhong LI Hongwen 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第5期1148-1166,共19页
In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise p... In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)situations.In this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging issue.Firstly,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter estimation.Furthermore,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other parameters.Finally,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results. 展开更多
关键词 complex jamming recognition time frequency feature convolutional neural network(CNN) parameter estimation
下载PDF
Coarse-fine joint target parameter estimation method based on AN-RSC in OFDM passive radar
10
作者 WANG Chujun WAN Xianrong +1 位作者 YI Jianxin CHENG Feng 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第2期339-349,共11页
In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to... In this paper,we study the accuracy of delay-Doppler parameter estimation of targets in a passive radar using orthogonal frequency division multiplexing(OFDM)signal.A coarse-fine joint estimation method is proposed to achieve better estimation accuracy of target parameters without excessive computational burden.Firstly,the modulation symbol domain(MSD)method is used to roughly estimate the delay and Doppler of targets.Then,to obtain high-precision Doppler estimation,the atomic norm(AN)based on the multiple measurement vectors(MMV)model(MMV-AN)is used to manifest the signal sparsity in the continuous Doppler domain.At the same time,a reference signal compensation(RSC)method is presented to obtain highprecision delay estimation.Simulation results based on the OFDM signal show that the coarse-fine joint estimation method based on AN-RSC can obtain a more accurate estimation of target parameters compared with other algorithms.In addition,the proposed method also possesses computational advantages compared with the joint parameter estimation. 展开更多
关键词 passive radar orthogonal frequency division multiplexing(OFDM)signal atomic norm(AN) parameter estimation
下载PDF
Non-cooperative Space Target Estimation Algorithm Without Prior Information Dependence Based on Temporal Line of Sight Constraint
11
作者 XIAO Hui ZHU Chongrui +3 位作者 LIU Xinqi YU Yifan SHENG Qinghong YANG Rui 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2024年第4期526-540,共15页
Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a p... Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a parameter estimation model of the boost phase based on trajectory plane parametric cutting.The use of the plane passing through the geo-center and the cutting sequence line of sight(LOS)generates the trajectory-cutting plane.With the coefficient of the trajectory cutting plane directly used as the parameter to be estimated,a motion parameter estimation model in space non-cooperative targets is established,and the Gauss-Newton iteration method is used to solve the flight parameters.The experimental results show that the estimation algorithm proposed in this paper weakly relies on prior information and has higher estimation accuracy,providing a practical new idea and method for the parameter estimation of space non-cooperative targets under single-satellite warning. 展开更多
关键词 motion parameter estimation estimation of impact point infrared early warning boost phase modeling trajectory database construction
下载PDF
Inversion of walkaway VSP data in the presence of lateral velocity heterogeneity
12
作者 Vladimir Grechka Ilya Tsvankin Pedro Contreras 《Energy Geoscience》 EI 2024年第2期304-313,共10页
Multi-azimuth walkaway vertical seismic profiling is an established technique for the estimation of in situ slowness surfaces and inferring anisotropy parameters.Normally,this technique requires the assumption of late... Multi-azimuth walkaway vertical seismic profiling is an established technique for the estimation of in situ slowness surfaces and inferring anisotropy parameters.Normally,this technique requires the assumption of lateral homogeneity,which makes the horizontal slowness components at depths of downhole receivers equal to those measured at the surface.Any violations of this assumption,such as lateral heterogeneity or nonzero dip of intermediate interfaces,lead to distortions in reconstructed slowness surfaces and,consequently,to errors in estimated anisotropic parameters.In this work,we relax the assumption of lateral homogeneity and discuss how to correct vertical seismic profile data for weak lateral heterogeneity.We describe a procedure of downward continuation of recorded traveltimes that accounts for the presence of both vertical inhomogeneity and weak lateral heterogeneity,which produces correct slowness surfaces at depths of downhole receivers,noticing that sufficiently dense receiver coverage along a borehole is required to separate influences of vertical and lateral heterogeneity on measured traveltimes and obtain accurate estimates of the slowness surfaces.Once the slowness surfaces are found and a desired type of anisotropic model to be inverted is selected,the corresponding anisotropic parameters,providing the best fit to the estimated slownesses,can be obtained.We invert the slowness surfaces of P-waves for parameters of the simplest anisotropic model describing dipping fractures(transversely isotropic medium with a tilted symmetry axis).Five parameters of this model,namely,the P-wave velocity V0 in the direction of the symmetry axis,Thomsen's anisotropic coefficients e and d,the tilt n,and the azimuth b of the symmetry axis,can be estimated in a stable manner when maximum source offset is greater than half of receiver depth. 展开更多
关键词 Walkaway vertical seismic profile Lateral velocity heterogeneity Anisotropic parameter estimation Vertical inhomogeneity
下载PDF
Design of a Multifrequency Signal Parameter Estimation Method for the Distribution Network Based on HIpST
13
作者 Bin Liu Shuai Liang +1 位作者 Renjie Ding Shuguang Li 《Energy Engineering》 EI 2024年第3期729-746,共18页
The application of traditional synchronous measurement methods is limited by frequent fluctuations of electrical signals and complex frequency components in distribution networks.Therefore,it is critical to find solut... The application of traditional synchronous measurement methods is limited by frequent fluctuations of electrical signals and complex frequency components in distribution networks.Therefore,it is critical to find solutions to the issues of multifrequency parameter estimation and synchronous measurement estimation accuracy in the complex environment of distribution networks.By utilizing the multifrequency sensing capabilities of discrete Fourier transform signals and Taylor series for dynamic signal processing,a multifrequency signal estimation approach based on HT-IpDFT-STWLS(HIpST)for distribution networks is provided.First,by introducing the Hilbert transform(HT),the influence of noise on the estimation algorithm is reduced.Second,signal frequency components are obtained on the basis of the calculated signal envelope spectrum,and the interpolated discrete Fourier transform(IpDFT)frequency coarse estimation results are used as the initial values of symmetric Taylor weighted least squares(STWLS)to achieve high-precision parameter estimation under the dynamic changes of the signal,and the method increases the number of discrete Fourier.Third,the accuracy of this proposed method is verified by simulation analysis.Data show that this proposed method can accurately achieve the parameter estimation of multifrequency signals in distribution networks.This approach provides a solution for the application of phasor measurement units in distribution networks. 展开更多
关键词 Discrete fourier transform taylor series hilbert transform multifrequency signal parameter estimation
下载PDF
Impacts of Model Mismatch and Array Scale on Channel Estimation for XL-HRIS-Aided Systems
14
作者 LU Zhizheng HAN Yu JIN Shi 《ZTE Communications》 2024年第1期24-33,共10页
Extremely large-scale hybrid reconfigurable intelligence surface(XL-HRIS),an improved version of the RIS,can receive the incident signal and enhance communication performance.However,as the RIS size increases,the phas... Extremely large-scale hybrid reconfigurable intelligence surface(XL-HRIS),an improved version of the RIS,can receive the incident signal and enhance communication performance.However,as the RIS size increases,the phase variations of the received signal across the whole array are nonnegligible in the near-field region,and the channel model mismatch,which will decrease the estimation accuracy,must be considered.In this paper,the lower bound(LB)of the estimated parameter is studied and the impacts of the distance and signal-tonoise ratio(SNR)on LB are then evaluated.Moreover,the impacts of the array scale on LB and spectral efficiency(SE)are also studied.Simulation results verify that even in extremely large-scale array systems with infinite SNR,channel model mismatch can still limit estimation accuracy.However,this impact decreases with increasing distance. 展开更多
关键词 XL-HRIS NEAR-FIELD LB model mismatch parameter estimation
下载PDF
Numerical Simulation and Parameter Estimation of Fractional-Order Dynamic Epidemic Model for COVID-19
15
作者 Rong Kang Tianzeng Li 《Journal of Applied Mathematics and Physics》 2024年第10期3469-3495,共27页
The outbreak of COVID-19 in 2019 resulted in numerous infections and deaths. In order to better study the transmission of COVID-19, this article adopts an improved fractional-order SIR model. Firstly, the properties o... The outbreak of COVID-19 in 2019 resulted in numerous infections and deaths. In order to better study the transmission of COVID-19, this article adopts an improved fractional-order SIR model. Firstly, the properties of the model are studied, including the feasible domain and bounded solutions of the system. Secondly, the stability of the system is discussed, among other things. Then, the GMMP method is introduced to obtain numerical solutions for the COVID-19 system and combined with the improved MH-NMSS-PSO parameter estimation method to fit the real data of Delhi, India from April 1, 2020 to June 30, 2020. The results show that the fitting effect is quite ideal. Finally, long-term predictions were made on the number of infections. We accurately estimate that the peak number of infections in Delhi, India, can reach around 2.1 million. This paper also compares the fitting performance of the integer-order COVID-19 model and the fractional-order COVID-19 model using the real data from Delhi. The results indicate that the fractional-order model with different orders, as we proposed, performs the best. 展开更多
关键词 Parameter Estimation COVID-19 Infectious Disease Model Fractional-Order Derivative
下载PDF
Multi Parameter Adaptive Estimation of Reaction-Diffusion Equation
16
作者 Shujing Wang 《Engineering(科研)》 2024年第7期188-203,共16页
This study addresses the problem of parameter estimation for a one-dimensional reaction-diffusion equation, involving both unknown domain parameters and unknown boundary parameters. The proposed approach utilizes the ... This study addresses the problem of parameter estimation for a one-dimensional reaction-diffusion equation, involving both unknown domain parameters and unknown boundary parameters. The proposed approach utilizes the least-squares method to design an adaptive law for parameter estimation. The convergence analysis demonstrates that under persistent excitation conditions, the adaptive law converges exponentially to zero, indicating that the estimated parameters converge exponentially to their true values. Numerical simulations confirm the effectiveness. Furthermore, it is shown that within a certain range of the reaction coefficient, the auxiliary system acts as a state observer, providing an accurate estimate of the system state at an exponential rate. . 展开更多
关键词 Parameter Estimation Adaptive Law Backstepping Transformation
下载PDF
An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation 被引量:12
17
作者 胡春平 颜学峰 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2009年第2期232-240,共9页
A new version of differential evolution (DE) algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution (ISDE), is proposed to... A new version of differential evolution (DE) algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution (ISDE), is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters' self-adaptation. The .performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm ~nd-other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury. (Hg) oxidation in flue gas, and satisfactory results are obtained. 展开更多
关键词 differential evolution immune system evolutionary computation parameter estimation
下载PDF
UBSS and blind parameters estimation algorithms for synchronous orthogonal FH signals 被引量:11
18
作者 Weihong Fu Yongqiang Hei Xiaohui Li 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2014年第6期911-920,共10页
By using the sparsity of frequency hopping(FH) signals,an underdetermined blind source separation(UBSS) algorithm is presented. Firstly, the short time Fourier transform(STFT) is performed on the mixed signals. ... By using the sparsity of frequency hopping(FH) signals,an underdetermined blind source separation(UBSS) algorithm is presented. Firstly, the short time Fourier transform(STFT) is performed on the mixed signals. Then, the mixing matrix, hopping frequencies, hopping instants and the hooping rate can be estimated by the K-means clustering algorithm. With the estimated mixing matrix, the directions of arrival(DOA) of source signals can be obtained. Then, the FH signals are sorted and the FH pattern is obtained. Finally, the shortest path algorithm is adopted to recover the time domain signals. Simulation results show that the correlation coefficient between the estimated FH signal and the source signal is above 0.9 when the signal-to-noise ratio(SNR) is higher than 0 d B and hopping parameters of multiple FH signals in the synchronous orthogonal FH network can be accurately estimated and sorted under the underdetermined conditions. 展开更多
关键词 frequency hopping(FH) underdetermined blind source separation(UBSS) parameters estimation CLUSTERING
下载PDF
Estimating Hansen solubility parameters of organic pigments by group contribution methods 被引量:2
19
作者 Markus Enekvist Xiaodong Liang +2 位作者 Xiangping Zhang Kim Dam-Johansen Georgios MKontogeorgis 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2021年第3期186-197,共12页
The Hansen solubility parameters(HSP)are frequently used for solvent selection and characterization of polymers,and are directly related to the suspension behavior of pigments in solvent mixtures.The performance of cu... The Hansen solubility parameters(HSP)are frequently used for solvent selection and characterization of polymers,and are directly related to the suspension behavior of pigments in solvent mixtures.The performance of currently available group contribution(GC)methods for HSP were evaluated and found to be insufficient for computer-aided product design(CAPD)of paints and coatings.A revised and,for this purpose,improved GC method is presented for estimating HSP of organic compounds,intended for organic pigments.Due to the significant limitations of GC methods,an uncertainty analysis and parameter confidence intervals are provided in order to better quantify the estimation accuracy of the proposed approach.Compared to other applicable GC methods,the prediction error is reduced significantly with average absolute errors of 0.45 MPa^(1/2),1.35 MPa^(1/2),and 1.09 MPa^(1/2) for the partial dispersion(δD),polar(δP)and hydrogen-bonding(δH)solubility parameters respectively for a database of 1106 compounds.The performance for organic pigments is comparable to the overall method performance,with higher average errors forδD and lower average errors forδP andδH. 展开更多
关键词 Hansen solubility parameters Group contribution method Organic pigments Computer-aided product design Parameter estimation Uncertainty analysis
下载PDF
Observability Analysis in Parameters Estimation of an Uncooperative Space Target 被引量:2
20
作者 Xianghao Hou Gang Qiao 《Computer Modeling in Engineering & Sciences》 SCIE EI 2020年第1期175-205,共31页
To study the parameter estimating effects of a free-floating tumbling space target,the extended Kalman filter(EKF)scheme is utilized with different high-nonlinear translational and rotational coupled kinematic&dyn... To study the parameter estimating effects of a free-floating tumbling space target,the extended Kalman filter(EKF)scheme is utilized with different high-nonlinear translational and rotational coupled kinematic&dynamic models on the LIDAR measurements.Applying the aforementioned models and measurements results in the situation where one single state can be estimated differently with varying accuracies since the EKFs based on different models have different observabilities.In the proposed EKFs,the traditional quaternions based kinematics and dynamics and the dual vector quaternions(DVQ)based kinematics and dynamics are used for the modeling of the relative motions between a chaser satellite and an uncooperative target.In the non-contact estimating scenarios,only highly nonlinear relative attitude and range measurements:the grapple fixture on the target measured from the chaser satellite via vision-based sensors,can be used.By evaluating the results of the EKFs,the observability properties of each EKF are studied analytically and numerically with the the Observability Gramian matrices(OG)and the standard deviations for every estimated parameters.The analysis of observability perform intensive studies and reveal the intrinsic factors that affect the accuracy and stability of the parameters estimation of an uncooperative space target.Finally,the analytical and numerical results show the optimal composition of the kinematic&dynamic models and measurements. 展开更多
关键词 Parameter estimations observability analysis dual quaternions extended Kalman filter
下载PDF
上一页 1 2 21 下一页 到第
使用帮助 返回顶部