Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

An Improved Bald Eagle Search Algorithm with Cauchy Mutation and Adaptive Weight Factor for Engineering Optimization

The Bald Eagle Search algorithm(BES)is an emerging meta-heuristic algorithm.The algorithm simulates the hunting behavior of eagles,and obtains an optimal solution through three stages,namely selection stage,search stage and swooping stage.However,BES tends to drop-in local optimization and the maximum value of search space needs to be improved.To fill this research gap,we propose an improved bald eagle algorithm(CABES)that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima.Firstly,CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage,to select a better search range.Secondly,in the search stage,CABES updates the search position update formula by an adaptive weight factor to further promote the local optimization capability of BES.To verify the performance of CABES,the benchmark function of CEC2017 is used to simulate the algorithm.The findings of the tests are compared to those of the Particle Swarm Optimization algorithm(PSO),Whale Optimization Algorithm(WOA)and Archimedes Algorithm(AOA).The experimental results show that CABES can provide good exploration and development capabilities,and it has strong competitiveness in testing algorithms.Finally,CABES is applied to four constrained engineering problems and a groundwater engineeringmodel,which further verifies the effectiveness and efficiency of CABES in practical engineering problems.

A Novel Color Image Watermarking Method with Adaptive Scaling Factor Using Similarity-Based Edge Region

This study aimed to deal with three challenges:robustness,imperceptibility,and capacity in the image watermarking field.To reach a high capacity,a novel similarity-based edge detection algorithm was developed that finds more edge points than traditional techniques.The colored watermark image was created by inserting a randomly generated message on the edge points detected by this algorithm.To ensure robustness and imperceptibility,watermark and cover images were combined in the high-frequency subbands using Discrete Wavelet Transform and Singular Value Decomposition.In the watermarking stage,the watermark image was weighted by the adaptive scaling factor calculated by the standard deviation of the similarity image.According to the results,the proposed edge-based color image watermarking technique has achieved high payload capacity,imperceptibility,and robustness to all attacks.In addition,the highest performance values were obtained against rotation attack,to which sufficient robustness has not been reached in the related studies.

Designing Adaptive Multiple Dependent State Sampling Plan for Accelerated Life Tests

A novel adaptive multiple dependent state sampling plan(AMDSSP)was designed to inspect products from a continuous manufacturing process under the accelerated life test(ALT)using both double sampling plan(DSP)and multiple dependent state sampling plan(MDSSP)concepts.Under accelerated conditions,the lifetime of a product follows the Weibull distribution with a known shape parameter,while the scale parameter can be determined using the acceleration factor(AF).The Arrhenius model is used to estimate AF when the damaging process is temperature-sensitive.An economic design of the proposed sampling plan was also considered for the ALT.A genetic algorithm with nonlinear optimization was used to estimate optimal plan parameters to minimize the average sample number(ASN)and total cost of inspection(TC)under both producer’s and consumer’s risks.Numerical results are presented to support the AMDSSP for the ALT,while performance comparisons between the AMDSSP,the MDSSP and a single sampling plan(SSP)for the ALT are discussed.Results indicated that the AMDSSP was more flexible and efficient for ASN and TC than the MDSSP and SSP plans under accelerated conditions.The AMDSSP also had a higher operating characteristic(OC)curve than both the existing sampling plans.Two real datasets of electronic devices for the ALT at high temperatures demonstrated the practicality and usefulness of the proposed sampling plan.

An improved displacement-based adaptive pushover procedure based on factor modal combination rule

An accurate estimation of the applied load pattern is an essential component in each pushover procedure. Recently, a number of adaptive pushover methods have been proposed in which the effects of the higher modes as well as the progressive changes in the dynamic characteristics of structures are taken into account to compute the applied load pattern. The basic shortcoming of these advanced pushover methods is related to employing the quadratic modal combination rule, whereby the sign reversals of the modal load vectors are suppressed. In this study, an improved displacement-based adaptive pushover method is developed in which the applied load pattern is computed using the factor modal combination rule(FMC). In the proposed procedure, multiple load patterns, depending on the number of the modes considered, are determined in order to take into account the sign reversals of different modal load vectors. The accuracy of the proposed method is verifi ed for seven moment resisting frame buildings of 3, 9 and 20 stories with regularity or vertically geometric and mass irregularities subjected to 60 earthquake ground motion records. The results showed that the proposed methodology is capable of reproducing the peak dynamic responses with very good accuracy.

Modifed Multifdelity Surrogate Model Based on Radial Basis Function with Adaptive Scale Factor

Multifdelity surrogates(MFSs)replace computationally intensive models by synergistically combining information from diferent fdelity data with a signifcant improvement in modeling efciency.In this paper,a modifed MFS(MMFS)model based on a radial basis function(RBF)is proposed,in which two fdelities of information can be analyzed by adaptively obtaining the scale factor.In the MMFS,an RBF was employed to establish the low-fdelity model.The correlation matrix of the high-fdelity samples and corresponding low-fdelity responses were integrated into an expansion matrix to determine the scaling function parameters.The shape parameters of the basis function were optimized by minimizing the leave-one-out cross-validation error of the high-fdelity sample points.The performance of the MMFS was compared with those of other MFS models(MFS-RBF and cooperative RBF)and single-fdelity RBF using four benchmark test functions,by which the impacts of diferent high-fdelity sample sizes on the prediction accuracy were also analyzed.The sensitivity of the MMFS model to the randomness of the design of experiments(DoE)was investigated by repeating sampling plans with 20 diferent DoEs.Stress analysis of the steel plate is presented to highlight the prediction ability of the proposed MMFS model.This research proposes a new multifdelity modeling method that can fully use two fdelity sample sets,rapidly calculate model parameters,and exhibit good prediction accuracy and robustness.

RLS channel estimation with adaptive forgetting factor in space-time coded MIMO-OFDM systems

Considering that channel estimation plays a crucial role in coherent detection, this paper addresses a method of Recursive-least-squares (RLS) channel estimation with adaptive forgetting factor in wireless space-time coded multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Because there are three different forgetting factor scenarios including adaptive, two-step and conventional ones applied to RLS channel estimation, this paper describes the principle of RLS channel estimation and analyzes the impact of different forgetting factor scenarios on the performances of RLS channel estimation. Simulation results proved that the RLS algorithm with adaptive forgetting factor (RLS-A) outperformed that with two-step forgetting factor (RLS-T) or with conventional forgetting factor (RLS-C) in both estimation accuracy and robustness over the multiple-input multiple-output (MIMO) channel, i.e., a wide-sense stationary uncorrelated scattering (WSSUS) and frequency-selective slowly fading channel. Hence, we can employ the RLS-A method by adjusting forgetting factor adaptively to track and estimate channel state parameters successfully in space-time coded MIMO-OFDM systems.

Minimum variance adaptive beamforming combined with coherence factor weighting applied to ultrafast active cavitation imaging

The ultrafast active cavitation imaging(UACI)based on plane wave transmission and delay-and-sum(DAS)beamforming has been developed to monitor cavitation events with a high frame rate.However,DAS beamforming leads to images with limited resolution and contrast.In this paper,minimum variance(M V)adaptive beamforming and coherence factor(CF)weighting are combined to achieve an MVCF-based UACI,which can improve the cavitation imaging quality.The detailed algorithm evaluation has been investigated from both simulation and experimental data The simulation data include10point targets and a cyst,while the experimental data are obtained by detecting the dissipation of cavitation bubbles in water excited by a single element transducer with frequency of1.2MHz.The advantages of the proposed methodology as well as the comparison with conventional B-mode,DAS?M V,DAS-CF and MV on the basis of compressive sensing(CS)(called MVCS)beamformers are discussed.The results show that MVCF beamformer has a significant improvement in terms of both resolutions and signal-to-noise ratio(SN R).The MVCF-based UACI has a SNR at21.82dB higher,lateral and axial resolution at2.69times and1.93times?respectively,which were compared with those of B-mode active cavitation mapping.The MVCF-based UACI can be used to image the residual cavitation bubbles with a higher SNR and better spatial resolution

Adaptive projective synchronization with different scaling factors in networks

We study projective synchronization with different scaling factors （PSDF） in N coupled chaotic systems networks. By using the adaptive linear control, some sufficient criteria for the PSDF in symmetrical and asymmetrical coupled networks are separately given based on the Lyapunov function method and the left eigenvalue theory. Numerical simulations for a generalized chaotic unified system are illustrated to verify the theoretical results.

Research Progress on Psychosocial Adaptation of Hemodialysis Patients

From the perspective of the biopsychosocial medical model,hemodialysis patients often suffer from psychosocial maladaptation in the face of a series of changes and pressures,which greatly affect their physical and mental health.This paper reviews the concept of psychosocial adaptation of hemodialysis patients,the current research status,influencing factors,measurement tools,and the current status of interventions,aiming to provide a reference for improving the psychosocial adaptation ability of hemodialysis patients.

Chromatin assembly factor 1 suppresses epigenetic reprogramming toward adaptive drug resistance

The long-term effectiveness of targeted cancer therapies is limited by the development of resistance.Although epigenetic reprogramming has been implicated in resistance,the mechanisms remain elusive.Herein,we demonstrate that increased chromatin accessibility is involved in adaptive BRAF inhibitor(BRAFi)-resistance in melanoma cells.We observed loss of chromatin assembly factor 1(CAF-1)and its related histone H3 lysine 9 trimethylation(H3K9me3)with adaptive BRAFi resistance.We further showed that depletion of CAF-1 provides chromatin plasticity for effective reprogramming by AP1 components to promote BRAFi resistance.Our data sug-gest that therapeutic approaches to restore H3K9me3 levels may compensate for the loss of CAF-1 and,in turn,suppress resistance to BRAF inhibitors.

The optimal fractional Gabor transform based on the adaptive window function and its application

We designed the window function of the optimal Gabor transform based on the time-frequency rotation property of the fractional Fourier transform. Thus, we obtained the adaptive optimal Gabor transform in the fractional domain and improved the time-frequency concentration of the Gabor transform. The algorithm first searches for the optimal rotation factor, then performs the p-th FrFT of the signal and, finally, performs time and frequency analysis of the FrFT result. Finally, the algorithm rotates the plane in the fractional domain back to the normal time-frequency plane. This promotes the application of FrFT in the field of high-resolution reservoir prediction. Additionally, we proposed an adaptive search method for the optimal rotation factor using the Parseval principle in the fractional domain, which simplifies the algorithm. We carried out spectrum decomposition of the seismic signal, which showed that the instantaneous frequency slices obtained by the proposed algorithm are superior to the ones obtained by the traditional Gabor transform. The adaptive time frequency analysis is of great significance to seismic signal processing.

adaptive LASSO logistic回归模型应用于老年人养老意愿影响因素研究的探讨

目的探讨adaptive LASSO logistic回归模型在老年人养老意愿影响因素研究中的应用。方法基于厦门市60岁及以上老年人口的多阶段整群抽样调查数据,建立老年人养老意愿影响因素的adaptive LASSO logistic回归模型,通过交叉验证法选择模型中的调和参数λ;通过与全变量和逐步logistic回归结果的比较,探讨adaptive LASSO logistic回归模型的优势。结果共纳入1244名老年人,其养老意愿为家庭养老、社区居家养老和机构养老的比例分别为70.0%、21.1%和8.9%。交叉验证法选择的λ为0.018;此时adaptive LASSO logistic回归模型纳入的自变量为居住地、年龄、婚姻状况、文化程度、子女数、每月退休金收入、公费医疗和住院情况;BIC和AIC分别为1931、1888,均低于全变量logistic回归(2077、1923)和逐步logistic回归(2025、1912)。结论 adaptive LASSO logistic回归模型可用于老年人养老意愿影响因素研究。老年人的养老意愿受多个因素影响。

城市火灾次数与气象因素的Adaptive-Lasso分析

为研究城市火灾次数与气象因素的关系,以天津市的火灾数据为例,建立月度火灾次数与温度、风速、降雨量、日照、湿度等相关的各月气象因素及上月火灾起数间的线性回归模型.通过Adaptive-Lasso方法对上述变量进行选择并估计其参数,并对所得模型进行了分析比较,同时预测分析了2008年上半年火灾发生数.研究表明,通过Adaptive-Lasso方法建立的线性回归模型能够更好地预测火灾次数.

Autonomous navigation method of satellite constellation based on adaptive forgetting factors

To address the problem that model uncertainty and unknown time-varying system noise hinder the filtering accuracy of the autonomous navigation system of satellite constellation,an autonomous navigation method of satellite constellation based on the Unscented Kalman Filter with Adaptive Forgetting Factors(UKF-AFF)is proposed.The process noise covariance matrix is estimated online with the strategy that combines covariance matching and adaptive adjustment of forgetting factors.The adaptive adjustment coefficient based on squared Mahalanobis distance of state residual is employed to achieve online regulation of forgetting factors,equipping this method with more adaptability.The intersatellite direction vector obtained from photographic observations is introduced to determine the constellation satellite orbit together with the distance measurement to avoid rank deficiency issues.Considering that the number of available measurements varies online with intersatellite visibility in practical applications such as time-varying constellation configurations,the smooth covariance matrix of state correction determined by innovation and gain is adopted and constructed recursively.Stability analysis of the proposed method is also conducted.The effectiveness of the proposed method is verified by the Monte Carlo simulation and comparison experiments.The estimation accuracy of constellation position and velocity of UKF-AFF is improved by 30%and 44%respectively compared to those of the extended Kalman filter,and the method proposed is also better than other several adaptive filtering methods in the presence of significant model uncertainty.

COMBINED DELAUNAY TRIANGULATION AND ADAPTIVE FINITE ELEMENT METHOD FOR CRACK GROWTH ANALYSIS

The paper presents the utilization of the adaptive Delaunay triangulation in the finite element modeling of two dimensional crack propagation problems, including detailed description of the proposed procedure which consists of the Delaunay triangulation algorithm and an adaptive remeshing technique. The adaptive remeshing technique generates small elements around crack tips and large elements in the other regions. The resulting stress intensity factors and simulated crack propagation behavior are used to evaluate the effectiveness of the procedure. Three sample problems of a center cracked plate, a single edge cracked plate and a compact tension specimen, are simulated and their results assessed.

Adaptive control for autonomous rendezvous of spacecraft on elliptical orbit

A strategy for spacecraft autonomous rendezvous on an elliptical orbit in situation of no orbit information is developed. Lawden equation is used to describe relative motion of two spacecraft. Then an adaptive gain factor is introduced, and an adaptive control law for auton- omous rendezvous on the elliptical orbit is designed using Lyapunov approach. The relative motion is proved to be ultimately bounded under this control law, and the final relative position error can achieve the expected magnitude. Simulation results indicate that the adaptive control law can realize autonomous rendezvous on the elliptical orbit with relative state information only.

Comparison of Two Fading Filters anc Adaptively Robust Filter

Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling the influences of the kinematic model errors are analyzed. A practical example is given. The results of the fading filter and adaptively robust filter are compared and analyzed.

Spatio-temporal Difference and Influencing Factors of Environmental Adaptability Measurement of Human-sea Economic System in Liaoning Coastal Area

Adaptability theory is an important tool to analyze the degree, mechanism and process of interaction between human and environment, which provides a new perspective for the research of sustainability assessment. Based on the entropy weight-TOPSIS method and the panel Tobit model from the perspective of adaptability, spatio-temporal difference and influencing factors of environmental adaptability assessment of human-sea economic system in Liaoning coastal area was measured by using the city panel data from 2000 to 2014. The results indicate that: 1) The environmental adaptability of human-sea economic system in Liaoning coastal area rose slowly from 2000 to 2014, the developing trend of each city was linearly related, and Dalian was in a leading position. 2) The different adaptability elements and adaptability subsystem show polarization phenomenon and completely different regional evolution characteristics. The adaptability of human-sea environment system and human-sea economic system rose slowly and had the characteristics of linear relationship, and the adaptability of human-sea environment system is the main reason for the difference of environmental adaptability of human-sea economic system. 3) Science and technology, environmental management, marine economic development level, port construction are the driving factors of the healthy development of environmental adaptability of urban human-sea economic system.

A novel algorithm of adaptive IIR lattice notch filter and performance analysis

A novel adaptive algorithm of IIR lattice notch filter realized by all-pass filter is presented. The time-averaged estimation of cross correlation of the present instantaneous input signal and the past output signal is used to update the step-size, leading to a considerably improved convergence rate in a low SNR situation and reduced steady-state bias and MSE. The theoretical expression for steady-state bounds on the step-size is derived, and the influence factors on the stable performance of the algorithm theoretically are analyzed. A normalized power factor is then introduced to control variation of step-size in its steady-state bounds. This technique prevents divergence due to the influence of large power input signal and improves robustness. Numerical experiments are performed to demonstrate superiority of the proposed method.