## What is/are Dynamic Estimation?

Dynamic Estimation - However, few studies have focused on the dynamic estimation of multi-level spatial distribution (city, county and its urban, suburban, and rural areas) of inter-regional migrant populations.^{[1]}Considering reliable external visual stimulus decoding in the perceptual noise channel and visual characteristics, dynamic estimation of visual dither quantization is performed based on a message passing algorithm on a factor graph.

^{[2]}A novel square root unscented Kalman iterative algorithm based on the dynamic state-of -charge of the lithium battery is designed, and the SOC estimation effect of the combined dynamic estimation algorithm and the unscented Kalman algorithm (UKF) is compared.

^{[3]}Simple, yet powerful experiments were conducted, subsequently validated the thermodynamic estimations in current study.

^{[4]}In the proposed controller, the VDC equations are rearranged using the combination of regressor technique, and TDE for unknown dynamic estimations.

^{[5]}These are then used, in combination with an innovative technique to evaluate the building’s weather dependency, to design a model able to provide accurate dynamic estimations of the achieved energy savings.

^{[6]}The simulation results show that the optimized SOC estimation and SOP prediction algorithm has higher accuracy and is applicable to the dynamic estimation of the actual driving cycles of hybrid electric vehicles.

^{[7]}The adaptive Wiener filtering method is considered with application to dynamic estimation of low-coherence interference fringe parameters.

^{[8]}Then, according to the product operation of wavelet transform and short-term monitoring support vector machine, the precipitation dynamic estimation method of rainfall radar multiplier in mountainous area is proposed.

^{[9]}This paper proposes a model-free approach for a single input, dynamic estimation of the available power using recurrent neural networks.

^{[10]}Then with the assumption that a part of system dynamic is uncertain Radial basis function (RBF) network is applied for uncertain dynamic estimation of system based on input-output data and a new controller is proposed for chaotic systems.

^{[11]}The dynamic estimation of epidemic spreading on networks is essential for controlling morbidity.

^{[12]}There is a big difference between the traditional aerodynamic estimation grid and the grid used for capture the main parameters of the trailing vortex in the far field.

^{[13]}It enables efficient multi-tenancy on SmartNIC JBOFs using the following techniques: a delay-based SSD congestion control algorithm, dynamic estimation of SSD write costs, a fair scheduler that operates at the granularity of a virtual slot, and an end-to-end credit-based flow control channel.

^{[14]}We also examine the impact of these variables on each index through long-run dynamic estimation.

^{[15]}More precisely, we compare a static slicing strategy to dynamic estimation and prediction-based algorithms.

^{[16]}Both dynamic estimation and terrain classification can be achieved concurrently with the same reservoir computing structure, which serves as a soft sensor device.

^{[17]}By using dynamic estimation, it ensures that the model is always updated to the plant and the steady-state optimization can be scheduled at any desired rate without needing to wait for steady-state.

^{[18]}We present a modified algorithm for adaptive Wiener filtering using two quadrature reference signals for a dynamic estimation of the phase and amplitude of interferometric signals.

^{[19]}This study performed an efficient flight simulation based on the Kriging model-assisted aerodynamic estimation to carry out global optimization.

^{[20]}Design/methodology/approachThe study employs the ordinary least squares estimation method with standard errors clustered at the firm level for preliminary analysis, besides the study employs the two-step GMM dynamic estimation method to deal with potential endogeneity issues.

^{[21]}The results show that the method proposed in this paper can minimize the effect of accuracy of initial alignment on strapdown gravimetric measurement and shows a better dynamic estimation performance.

^{[22]}The algorithm selects measurement spots and allocates the RSN accordingly to carry out the dynamic estimation of DNI.

^{[23]}It comprises of three modules: 1) Dynamic estimation of the temporal response functions (TRF) in every trial using a sequential linear minimum mean squared error (LMMSE) estimator, 2) Extract the N1-P2 peak of the estimated TRF that serves as a marker related to the attentional state and 3) Obtain a probabilistic measure of the attentional state using a support vector machine followed by a logistic regression.

^{[24]}Aiming at the problem of incomplete measurement data in the power system state estimation process, the missing data reconstructed by the residual generative adversarial network (RGAN) was introduced for the power system dynamic estimation.

^{[25]}Therefore, this paper proposes a method based on robust adaptive H∞ extended Kalman fileter (RAHEKF) for dynamic estimation of active distribution network.

^{[26]}A Restricted Boltzmann Machine with Dynamic Estimation of Distribution Algorithm (TwoRBM) constructs an interactive decision-making environment that helps in the classification of patients based on their symptoms and to identify people with a high chance of getting infected by a coronavirus.

^{[27]}This study is a dynamic estimation that avoids using average values adopted from literature that are not country specific.

^{[28]}The proposed scheme shows high potential for real-time dynamic estimation of the strain and stress state of complex structures at unmeasured locations.

^{[29]}Dynamic estimations also uncovered a long-run relationship among technical assistance, income per capita, openness, and tax revenues.

^{[30]}It defines tissue mechanical deformation as a nonlinear filtering process for dynamic estimation of nonlinear deformation behaviours of biological tissues.

^{[31]}In this paper, based on the characteristics of inertial data collected by smart terminals carried by pedestrians, a dynamic estimation algorithm of stride length using motion mode recognition is proposed.

^{[32]}ABSTRACT A dynamic estimation and control problem with a strategic sensor is considered.

^{[33]}It was determined that the computational cost was reduced by ~20 times for the complete hydrodynamic estimation of a pulsed sieve-plate column.

^{[34]}Our proposed LRME-4DCT method fully meets the practical clinical requirements for rapid dynamic estimation of lung respiratory motion.

^{[35]}First, a functional filtering technique is presented, then we show that the dynamic of estimation error can be modeled in the descriptor system form, this formulation makes it possible to describe the dynamic estimation error free of the derivative of the disturbances.

^{[36]}Considering the above challenges, dynamic estimation of SINR distribution is one possible way out.

^{[37]}A dynamic estimation algorithm of stochastic antenna orientation parameters invariant to characteristics of the mast basis movement is proposed.

^{[38]}To overcome this issue, a hybrid RTO (HRTO) approach has been proposed in the literature in which a dynamic estimation is carried out, followed by economic optimization.

^{[39]}The proposed method of dynamic estimation results in significant improvements of the accuracy of RSSI values when compared with the experimental measurements.

^{[40]}It achieves scalability and efficiency through a dynamic estimation of the set of data that are most beneficial to the current exploration.

^{[41]}Then, we optimized the ordinary time series InSAR processing procedure by a “dynamic estimation of digital elevation model (DEM) errors” step added before displacement inversion to avoid the false displacement signals caused by DEM errors.

^{[42]}However, little research has been conducted on the dynamic estimation of 2-D deformation time series for new SAR acquisitions, which has increasing demand with the availability of SAR data.

^{[43]}The study employed panel data analysis and utilised a dynamic estimation technique called the generalised method of moments.

^{[44]}These findings are supported by thermodynamic estimation of the saturation index.

^{[45]}The experimental results showed that the application of the dynamic estimation in the diversity parameter (λ) produced good results in most scenarios, i.

^{[46]}This study reports the results using both static and dynamic estimation techniques.

^{[47]}This approach allows a dynamic estimation of the traits, free from all time-related issues inherent to the traditional RFI methodology, and can easily be adapted and used in a genetic or genomic selection context.

^{[48]}This paper proposes a joint input and state dynamic estimation scheme for power networks in microgrids and active distribution systems with unknown inputs.

^{[49]}This method discretises the susceptible-exposed-infected-recovered-dead (SEIRD) epidemiological model in time domain to construct the nonlinear state-space equation for dynamic estimation of COVID-19 spread.

^{[50]}

## dynamic estimation method

Then, according to the product operation of wavelet transform and short-term monitoring support vector machine, the precipitation dynamic estimation method of rainfall radar multiplier in mountainous area is proposed.^{[1]}Design/methodology/approachThe study employs the ordinary least squares estimation method with standard errors clustered at the firm level for preliminary analysis, besides the study employs the two-step GMM dynamic estimation method to deal with potential endogeneity issues.

^{[2]}In this paper, a new method called as dynamic estimation method is proposed that improves the resolution of standard 8K Multichannel analyzer.

^{[3]}Extending popular “two-step” dynamic estimation methods, these policy functions then identify a set of structural parameters that are consistent with the dynamic model, the IV restrictions and the data.

^{[4]}The existing code analysis method considers the energy cost of software operations to minimize the energy estimation overhead of dynamic estimation methods.

^{[5]}To reduce the time of aircraft passenger evacuation in an unplanned emergency and improve passenger safety, this article proposed a dynamic estimation method of an aircraft emergency evacuation process; optimal performance statistics can be estimated eﬃciently.

^{[6]}In order to ensure the accuracy of weapon systems and the safety of taking off and landing of carrier aircraft, a dynamic estimation method combining the main inertial navigation systems (INS) and the sub-inertial navigation systems (SINS) is designed to estimate the curvature and torsion of any trajectory on the deck.

^{[7]}

## dynamic estimation model

Our dynamic estimation model to simulate death occurrence in changing environments can quickly estimate the earthquake death totals in Chinese earthquakes and accurately define the earthquake scale to facilitate post-earthquake emergency rescue.^{[1]}We develop static and dynamic estimation models using state-level data in the U.

^{[2]}To be specific, firstly, a mixed-logic-dynamic estimation model of DC-link voltage is established.

^{[3]}Considering the particularity, complexity and uncertainty of influencing factors, a dynamic estimation model of reservation registration service time based on binary attribute similarity in the hospital is proposed to solve the problem of hospital reservation registration service time estimation.

^{[4]}The models aim at presenting an analytical process for obtaining dynamic estimation model that takes account of the nonlinear effects in the analysis of the motors, e.

^{[5]}

## dynamic estimation algorithm

A novel square root unscented Kalman iterative algorithm based on the dynamic state-of -charge of the lithium battery is designed, and the SOC estimation effect of the combined dynamic estimation algorithm and the unscented Kalman algorithm (UKF) is compared.^{[1]}In this paper, based on the characteristics of inertial data collected by smart terminals carried by pedestrians, a dynamic estimation algorithm of stride length using motion mode recognition is proposed.

^{[2]}A dynamic estimation algorithm of stochastic antenna orientation parameters invariant to characteristics of the mast basis movement is proposed.

^{[3]}This paper develops new compressive sensing (CS)-based dynamic estimation algorithm to address the dynamic estimation problem in spaceborne intensity modulation direct detection (IMDD)-based laser TTC systems.

^{[4]}State of charge (SOC) estimation of lithium-ion batteries has been extensively studied and the estimation accuracy was mainly investigated through the development of various battery models and dynamic estimation algorithms.

^{[5]}

## dynamic estimation error

First, a functional filtering technique is presented, then we show that the dynamic of estimation error can be modeled in the descriptor system form, this formulation makes it possible to describe the dynamic estimation error free of the derivative of the disturbances.^{[1]}The advantage of proposed method is that the step-size can be adaptively adjusted based on the dynamic estimation errors.

^{[2]}The test results show that the

^{[3]}

## dynamic estimation performance

The results show that the method proposed in this paper can minimize the effect of accuracy of initial alignment on strapdown gravimetric measurement and shows a better dynamic estimation performance.^{[1]}As the real-time performance of the algorithm is guaranteed, it is possible to overcome the hysteretic nature of the traditional EKF and improve the dynamic estimation performance.

^{[2]}

## dynamic estimation technique

The study employed panel data analysis and utilised a dynamic estimation technique called the generalised method of moments.^{[1]}This study reports the results using both static and dynamic estimation techniques.

^{[2]}