Статті в журналах з теми "Estimability analysis of parameters"

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1

Ngo, Viet V., Abderrazak Latifi, and Marie-Odile Simonnot. "Soil Hydraulic Parameters Characterizing Preferential Water Flow: Estimability Analysis and Identification." Journal of Hydrologic Engineering 19, no. 10 (October 2014): 04014017. http://dx.doi.org/10.1061/(asce)he.1943-5584.0000953.

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2

Bedel, S., C. Vallières, and M. A. Latifi. "Parameters estimability analysis and identification for adsorption equilibrium models of carbon dioxide." Adsorption 23, no. 2-3 (February 6, 2017): 373–80. http://dx.doi.org/10.1007/s10450-017-9864-7.

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3

Ngo, V. V., M. A. Latifi, and M. O. Simonnot. "Estimability Analysis and Optimisation of Soil Hydraulic Parameters from Field Lysimeter Data." Transport in Porous Media 98, no. 2 (April 9, 2013): 485–504. http://dx.doi.org/10.1007/s11242-013-0155-9.

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4

Rikimaru, Yuuki, and Ritei Shibata. "Non-Identifiability of Simultaneous Spatial Autoregressive Model and Singularity of Fisher Information Matrix." International Journal of Statistics and Probability 5, no. 4 (June 15, 2017): 31. http://dx.doi.org/10.5539/ijsp.v6n4p31.

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Simultaneous spatial autoregressive model is widely used for spatial data analysis, observed at a set of grid points in a space. However a problem, not so well known, is that there exists no unique model unlike time series AR model for given autocovariances or spectral density. We show that such a non-identifiability of the model implies existence of multiple maximum likelihood estimates under Gaussianity and causes non-estimability of parameters and the singularity of Fisher information matrix. Several types of necessary and sufficient conditions for the singularity are given.
5

Ngo, Viet V., Horst H. Gerke, and Annika Badorreck. "Estimability Analysis for Optimization of Hysteretic Soil Hydraulic Parameters Using Data of a Field Irrigation Experiment." Transport in Porous Media 103, no. 3 (May 6, 2014): 535–62. http://dx.doi.org/10.1007/s11242-014-0315-6.

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6

Ngo, Viet V., Julien Michel, Valérie Gujisaite, Abderrazak Latifi, and Marie-Odile Simonnot. "Parameters describing nonequilibrium transport of polycyclic aromatic hydrocarbons through contaminated soil columns: Estimability analysis, correlation, and optimization." Journal of Contaminant Hydrology 158 (March 2014): 93–109. http://dx.doi.org/10.1016/j.jconhyd.2014.01.005.

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7

Christopeit, Norbert, and Michael Massmann. "ESTIMATING STRUCTURAL PARAMETERS IN REGRESSION MODELS WITH ADAPTIVE LEARNING." Econometric Theory 34, no. 1 (January 9, 2017): 68–111. http://dx.doi.org/10.1017/s0266466616000529.

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This paper examines the ordinary least squares (OLS) estimator of the structural parameters in a simple macroeconomic model in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous variable. The popularity of learning models has recently increased amongst applied economists and policy makers who seek to estimate them empirically. Yet the econometrics of learning models is largely uncharted territory. We consider two prominent learning algorithms, namely constant gain and decreasing gain learning. For each of the two learning rules, our analysis proceeds in two stages. First, the paper derives the asymptotic properties of agents’ expectations. At the second stage, the paper derives the asymptotics of OLS in the structural model, taking the first stage learning dynamics as given. In the case of constant gain learning, the structural model effectively amounts to a stationary, cointegrating, or co-explosiveness regression. With decreasing gain learning, the regressors are asymptotically collinear such that OLS does not satisfy, in general, the Grenander conditions for consistent estimability. Nevertheless, this paper shows that the OLS estimator remains consistent in all models considered. It also shows, however, that its asymptotic distribution, and hence any inference based upon it, may be nonstandard.
8

Tong, Yao, Duo Zhang, Zhijiang Shao, and Xiaojin Huang. "Global Model Calibration of High-Temperature Gas-Cooled Reactor Pebble-Bed Module Using an Adaptive Experimental Design." Energies 16, no. 12 (June 12, 2023): 4653. http://dx.doi.org/10.3390/en16124653.

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The world’s first high-temperature gas-cooled reactor pebble-bed module (HTR-PM) nuclear power plant adopts an innovative reactor type and a modular structure design. Parameter estimation and model calibration are of great significance prior to the implementation of model-based control and optimization. This paper focuses on identifying the thermal hydraulic parameters of HTR-PM over the global operating domain. The process technology and model mechanism of HTR-PM are reviewed. A parameter submodel named global parameter mapping is presented to quantify the relationship between an unknown model parameter and different operating conditions in a data-driven manner. The ideal construction of such a mapping requires reliable estimates, a well-poised sample set and an appropriate global surrogate. An adaptive model calibration scheme is designed to tackle these three issues correspondingly. First, a systematic parameter estimation approach is developed to ensure reliable estimates via heuristic subset selection consisting of estimability analysis and reliability evaluation. To capture the parameter behavior among the multiple experimental conditions and meanwhile reduce the operating cost, an adaptive experimental design is employed to guide condition testing. Experimental conditions are sequentially determined by comprehensively considering the criteria of sampling density, local nonlinearity and parameter uncertainty. Support vector regression is introduced as the global surrogate due to its capability of small-sample learning. Finally, the effectiveness of the model calibration scheme and its application performance in HTR-PM are validated by the simulation results.
9

Fries, R. H., and N. K. Cooperrider. "Bayesian Estimation of Transit Rail Vehicle Parameters." Journal of Dynamic Systems, Measurement, and Control 107, no. 2 (June 1, 1985): 151–58. http://dx.doi.org/10.1115/1.3149687.

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Bayesian parameter estimation is a powerful and versatile method with good convergence properties. This paper describes the use of the Bayesian method to estimate the parameters of a transit rail vehicle. The paper also addresses several issues of general interest in estimation work: cost function formulation, signal processing methods, parameter linking, and parameter estimability.
10

Xu, Peiliang, Yumei Liu, Yunzhong Shen, and Yoichi Fukuda. "Estimability analysis of variance and covariance components." Journal of Geodesy 81, no. 9 (December 12, 2006): 593–602. http://dx.doi.org/10.1007/s00190-006-0122-0.

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11

Fu, Caihong, and Terrance J. Quinn II. "Estimability of natural mortality and other population parameters in a length-based model: Pandalus borealis in Kachemak Bay, Alaska." Canadian Journal of Fisheries and Aquatic Sciences 57, no. 12 (December 1, 2000): 2420–32. http://dx.doi.org/10.1139/f00-220.

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Because stock-assessment models have become more complex, the question of estimability of population parameters is important. We conducted simulation-estimation experiments with a length-based model of the pink shrimp (Pandalus borealis Krøyer) population in Kachemak Bay, Alaska, to compare the robustness of various modeling approaches to specifications of natural mortality (M), catchability (q), a survey gear selectivity parameter (L50), and data imprecision. Our goal was to determine the estimability of various parameters, particularly M, q, and L50. Simulation results suggest that interannual variations in M and L50 could be estimated, if the underlying values have a trend over time. However, parameter q should be fixed at a chosen value, even when it varies over time. Estimated M for the Kachemak Bay P. borealis population increased in the 1980s, perhaps owing to increased predation mortality by groundfish.
12

Lenth, Russell,V. "Estimability Tools for Package Developers." R Journal 7, no. 1 (2015): 195. http://dx.doi.org/10.32614/rj-2015-016.

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13

Kounias, Stratis, and Miltiadis Chalikias. "Estimability of parameters in a linear model and related characterizations." Statistics & Probability Letters 78, no. 15 (October 2008): 2437–39. http://dx.doi.org/10.1016/j.spl.2008.02.019.

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14

Zaharatos, Brian R., Mark Campanelli, and Luis Tenorio. "On the estimability of the PV single-diode model parameters." Statistical Analysis and Data Mining: The ASA Data Science Journal 8, no. 5-6 (August 14, 2015): 329–39. http://dx.doi.org/10.1002/sam.11286.

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15

Le Cadre, J. P. "Properties of estimability criteria for target motion analysis." IEE Proceedings - Radar, Sonar and Navigation 145, no. 2 (1998): 92. http://dx.doi.org/10.1049/ip-rsn:19981833.

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16

Le Cadre, J. E., and C. Jauffret. "Discrete-time observability and estimability analysis for bearings-only target motion analysis." IEEE Transactions on Aerospace and Electronic Systems 33, no. 1 (January 1997): 178–201. http://dx.doi.org/10.1109/7.570737.

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17

Khodabandeh, Amir, and Peter J. G. Teunissen. "Array-Aided Multifrequency GNSS Ionospheric Sensing: Estimability and Precision Analysis." IEEE Transactions on Geoscience and Remote Sensing 54, no. 10 (October 2016): 5895–913. http://dx.doi.org/10.1109/tgrs.2016.2574809.

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18

Friedman, Alex M., and Carolin Frueh. "Observability and Estimability Analysis of Geosynchronous Objects with Angles-Only Measurements." Journal of the Astronautical Sciences 68, no. 2 (May 28, 2021): 503–34. http://dx.doi.org/10.1007/s40295-021-00261-4.

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19

Koteswara Rao, S. "Comments on "Discrete-time observability and estimability analysis for bearings-only target motion analysis"." IEEE Transactions on Aerospace and Electronic Systems 34, no. 4 (October 1998): 1361–67. http://dx.doi.org/10.1109/7.722722.

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20

LEE, Man Hyung, Jang Hyun LEE, Yung Ho KOH, Hyung Gyu PARK, Jeong Hyun MOON, and Sin Pyo HONG. "Observability and Estimability Analysis of the GPS and INS in the Vehicle." Journal of Mechanical Systems for Transportation and Logistics 3, no. 3 (2010): 537–51. http://dx.doi.org/10.1299/jmtl.3.537.

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21

Xu, Peiliang, and Jingnan Liu. "Variance components in errors-in-variables models: estimability, stability and bias analysis." Journal of Geodesy 88, no. 8 (April 18, 2014): 719–34. http://dx.doi.org/10.1007/s00190-014-0717-9.

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22

Nogueira, Idelfonso B. R., and Karen V. Pontes. "Parameter estimation with estimability analysis applied to an industrial scale polymerization process." Computers & Chemical Engineering 96 (January 2017): 75–86. http://dx.doi.org/10.1016/j.compchemeng.2016.10.013.

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23

Bailey, R. A., Sandra S. Ferreira, Dário Ferreira, and Célia Nunes. "Estimability of variance components when all model matrices commute." Linear Algebra and its Applications 492 (March 2016): 144–60. http://dx.doi.org/10.1016/j.laa.2015.11.002.

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24

Hyun, Saang-Yoon, and Kyuhan Kim. "An evaluation of estimability of parameters in the state-space non-linear logistic production model." Fisheries Research 245 (January 2022): 106135. http://dx.doi.org/10.1016/j.fishres.2021.106135.

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25

Fang, Qiang, and Xin Sheng Huang. "Global Observability Analysis IMU/Camera Integration." Applied Mechanics and Materials 380-384 (August 2013): 1069–72. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1069.

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Vision-aided inertial navigation systems can provide precise state estimates for the 3-D motion of a vehicle. This is achieved by combining inertial measurements from an inertial measurement unit (IMU) with visual observations from a camera. Observability is a key aspect of the state estimation problem of INS/Camera. In most previous research, conservative observability concepts based on Lie derivatives have extensively been used to characterize the estimability properties. In this paper, we present a novel approache to investigate the observability of INS/Camera: global observability. The global observability method directly starts from the basic observability definition. The global observability analysis approach is not only straightforward and comprehensive but also provides us with new insights compared with conventional methods. Some sufficient conditions for the global observability of the system is provided.
26

Saito, Hiroshi, and Hirotada Honda. "Geometric Analysis of Estimability of Target Object Shape Using Location-Unknown Distance Sensors." IEEE Transactions on Control of Network Systems 6, no. 1 (March 2019): 94–103. http://dx.doi.org/10.1109/tcns.2018.2797807.

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27

Bouchkira, Ilias, Abderrazak M. Latifi, Lhachmi Khamar, and Saad Benjelloun. "Global sensitivity based estimability analysis for the parameter identification of Pitzer’s thermodynamic model." Reliability Engineering & System Safety 207 (March 2021): 107263. http://dx.doi.org/10.1016/j.ress.2020.107263.

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28

Shotwell, Matthew S., and Richard A. Gray. "Estimability Analysis and Optimal Design in Dynamic Multi-scale Models of Cardiac Electrophysiology." Journal of Agricultural, Biological, and Environmental Statistics 21, no. 2 (January 21, 2016): 261–76. http://dx.doi.org/10.1007/s13253-016-0244-7.

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29

Chen, Yunxiao, Xiaoou Li, and Siliang Zhang. "Structured Latent Factor Analysis for Large-scale Data: Identifiability, Estimability, and Their Implications." Journal of the American Statistical Association 115, no. 532 (July 22, 2019): 1756–70. http://dx.doi.org/10.1080/01621459.2019.1635485.

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30

Jiang, Bo, Ming Liu, and Yongge Tian. "On two correlated linear models with common and different parameters." Mathematica Slovaca 72, no. 5 (October 1, 2022): 1355–74. http://dx.doi.org/10.1515/ms-2022-0092.

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Abstract A parametric regression model may comprise several correlated individual regression equations, and these equations may have common and different unknown parameters. In such a situation, the common unknown parameter vectors in these equations can be estimated individually or simultaneously according to various available statistical inference methods. The purpose of this paper is to provide an integral account of two classic objects in regression theory: the best linear unbiased predictors (BLUPs) and the best linear unbiased estimators (BLUEs) on common and different unknown parameters in two correlated linear models with common and different parameters. We first introduce some reduced models associated with the two correlated linear models. We then define and characterize predictability and estimability of all unknown parameter vectors in the two correlated models and their reduced models, and derive analytical formulas for calculating the BLUPs and BLUEs of all unknown parameter vectors in these models by means of a constrained quadratic matrix optimization method. We also discuss a variety of theoretical properties of the predictors and estimators.
31

Lei, M., C. Vallieres, G. Grevillot, and M. A. Latifi. "Thermal Swing Adsorption Process for Carbon Dioxide Capture and Recovery: Modeling, Simulation, Parameters Estimability, and Identification." Industrial & Engineering Chemistry Research 52, no. 22 (May 20, 2013): 7526–33. http://dx.doi.org/10.1021/ie3029152.

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32

Wu, Shaohua, Kevin A. P. McLean, Thomas J. Harris, and Kimberley B. McAuley. "Selection of optimal parameter set using estimability analysis and MSE-based model-selection criterion." International Journal of Advanced Mechatronic Systems 3, no. 3 (2011): 188. http://dx.doi.org/10.1504/ijamechs.2011.042615.

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33

Adkison, Milo D., and Zhenming Su. "A comparison of salmon escapement estimates using a hierarchical Bayesian approach versus separate maximum likelihood estimation of each year's return." Canadian Journal of Fisheries and Aquatic Sciences 58, no. 8 (August 1, 2001): 1663–71. http://dx.doi.org/10.1139/f01-100.

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In this simulation study, we compared the performance of a hierarchical Bayesian approach for estimating salmon escapement from count data with that of separate maximum likelihood estimation of each year's escapement. We simulated several contrasting counting schedules resulting in data sets that differed in information content. In particular, we were interested in the ability of the Bayesian approach to estimate escapement and timing in years where few or no counts are made after the peak of escapement. We found that the Bayesian hierarchical approach was much better able to estimate escapement and escapement timing in these situations. Separate estimates for such years could be wildly inaccurate. However, even a single postpeak count could dramatically improve the estimability of escapement parameters.
34

Ngo, Viet V., Julien Michel, Lise Lucas, Abderrazak Latifi, and Marie-Odile Simonnot. "Sensitivity, estimability and correlation of parameters describing equilibrium and nonequilibrium transports of bromide tracer in the field lysimeter." European Journal of Environmental and Civil Engineering 19, no. 4 (August 26, 2014): 445–66. http://dx.doi.org/10.1080/19648189.2014.950759.

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35

Zhang, Chen, Zhijiang Shao, Xi Chen, Zhen Yao, Xueping Gu, and Lorenz T. Biegler. "Kinetic parameter estimation of HDPE slurry process from molecular weight distribution: Estimability analysis and multistep methodology." AIChE Journal 60, no. 10 (June 24, 2014): 3442–59. http://dx.doi.org/10.1002/aic.14527.

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36

Sólymos, Péter, Steven M. Matsuoka, Steven G. Cumming, Diana Stralberg, Patricia Fontaine, Fiona K. A. Schmiegelow, Samantha J. Song, and Erin M. Bayne. "Evaluating time-removal models for estimating availability of boreal birds during point count surveys: Sample size requirements and model complexity." Condor 120, no. 4 (August 29, 2018): 765–86. http://dx.doi.org/10.1650/condor-18-32.1.

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Abstract We used conventional and finite mixture removal models with and without time-varying covariates to evaluate availability given presence for 152 bird species using data from point counts in boreal North America. We found that the choice of model had an impact on the estimability of unknown model parameters and affected the bias and variance of corrected counts. Finite mixture models provided better fit than conventional removal models and better adjusted for count duration. However, reliably estimating parameters and minimizing variance using mixture models required at least 200–1,000 detections. Mixture models with time-varying proportions of infrequent singers were best supported across species, indicating that accounting for date- and time-related heterogeneity is important when combining data across studies over large spatial scales, multiple sampling time frames, or variable survey protocols. Our flexible and continuous time-removal modeling framework can be used to account for such heterogeneity through the incorporation of easily obtainable covariates, such as methods, date, time, and location. Accounting for availability bias in bird surveys allows for better integration of disparate studies at large spatial scales and better adjustment of local, regional, and continental population size estimates.
37

Silva, Felipe, Elder Hemerly, and Waldemar Leite Filho. "On the Error State Selection for Stationary SINS Alignment and Calibration Kalman Filters—Part II: Observability/Estimability Analysis." Sensors 17, no. 3 (February 23, 2017): 439. http://dx.doi.org/10.3390/s17030439.

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38

Fysikopoulos, D., B. Benyahia, A. Borsos, Z. K. Nagy, and C. D. Rielly. "A framework for model reliability and estimability analysis of crystallization processes with multi-impurity multi-dimensional population balance models." Computers & Chemical Engineering 122 (March 2019): 275–92. http://dx.doi.org/10.1016/j.compchemeng.2018.09.007.

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39

Benyahia, B., M. A. Latifi, C. Fonteix, and F. Pla. "Emulsion copolymerization of styrene and butyl acrylate in the presence of a chain transfer agent. Part 2: Parameters estimability and confidence regions." Chemical Engineering Science 90 (March 2013): 110–18. http://dx.doi.org/10.1016/j.ces.2012.12.013.

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40

Takwoingi, Yemisi, Boliang Guo, Richard D. Riley, and Jonathan J. Deeks. "Performance of methods for meta-analysis of diagnostic test accuracy with few studies or sparse data." Statistical Methods in Medical Research 26, no. 4 (June 26, 2015): 1896–911. http://dx.doi.org/10.1177/0962280215592269.

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Hierarchical models such as the bivariate and hierarchical summary receiver operating characteristic (HSROC) models are recommended for meta-analysis of test accuracy studies. These models are challenging to fit when there are few studies and/or sparse data (for example zero cells in contingency tables due to studies reporting 100% sensitivity or specificity); the models may not converge, or give unreliable parameter estimates. Using simulation, we investigated the performance of seven hierarchical models incorporating increasing simplifications in scenarios designed to replicate realistic situations for meta-analysis of test accuracy studies. Performance of the models was assessed in terms of estimability (percentage of meta-analyses that successfully converged and percentage where the between study correlation was estimable), bias, mean square error and coverage of the 95% confidence intervals. Our results indicate that simpler hierarchical models are valid in situations with few studies or sparse data. For synthesis of sensitivity and specificity, univariate random effects logistic regression models are appropriate when a bivariate model cannot be fitted. Alternatively, an HSROC model that assumes a symmetric SROC curve (by excluding the shape parameter) can be used if the HSROC model is the chosen meta-analytic approach. In the absence of heterogeneity, fixed effect equivalent of the models can be applied.
41

Odijk, Dennis, Baocheng Zhang, Amir Khodabandeh, Robert Odolinski, and Peter J. G. Teunissen. "On the estimability of parameters in undifferenced, uncombined GNSS network and PPP-RTK user models by means of $$\mathcal {S}$$ S -system theory." Journal of Geodesy 90, no. 1 (November 5, 2015): 15–44. http://dx.doi.org/10.1007/s00190-015-0854-9.

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42

Liu, Jinhai, Rui Tu, Junqiang Han, Rui Zhang, Pengfei Zhang, and Lihong Fan. "Estimability analysis of differential inter-system biases and differential inter-frequency biases for dual-frequency GPS and BDS combined RTK." Measurement Science and Technology 31, no. 2 (November 29, 2019): 025009. http://dx.doi.org/10.1088/1361-6501/ab4844.

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43

PARIS, MATTEO G. A. "QUANTUM ESTIMATION FOR QUANTUM TECHNOLOGY." International Journal of Quantum Information 07, supp01 (January 2009): 125–37. http://dx.doi.org/10.1142/s0219749909004839.

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Several quantities of interest in quantum information, including entanglement and purity, are nonlinear functions of the density matrix and cannot, even in principle, correspond to proper quantum observables. Any method aimed to determine the value of these quantities should resort to indirect measurements and thus corresponds to a parameter estimation problem whose solution, i.e. the determination of the most precise estimator, unavoidably involves an optimization procedure. We review local quantum estimation theory and present explicit formulas for the symmetric logarithmic derivative and the quantum Fisher information of relevant families of quantum states. Estimability of a parameter is defined in terms of the quantum signal-to-noise ratio and the number of measurements needed to achieve a given relative error. The connections between the optmization procedure and the geometry of quantum statistical models are discussed. Our analysis allows to quantify quantum noise in the measurements of non observable quantities and provides a tools for the characterization of signals and devices in quantum technology.
44

EI Khaldi, Loukmane, Mustapha Sanbi, Rachid Saadani, and Miloud Rahmoune. "Robust Control and Thermal Analysis of a Reduced Model of Kirchhoff Composite Plate with Random Distribution of Thermopiezoelectric Sensors and Actuators." Journal of Composites Science 6, no. 8 (August 18, 2022): 242. http://dx.doi.org/10.3390/jcs6080242.

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This paper presents an implementation of a robust control LQG-Kalman model applied to composite Kirchhoff plate dynamics. A reduced model of a finite element method and control procedure is considered in the modeling of a structure because of the important number of piezoelectric patches used in control. Replacing the full model with a short model reduces the computational and time costs, especially when the number of degrees of freedom is significant. In robust control, the measurement of all states is not necessary and the observability and estimability criteria can be exploited, while conventional LQR control assumes that the data accessibility of all states is available. For this reason, robust control is proposed to control the random external disturbances and is compared to LQR control to illustrate its practicability and efficiency. The sensors and actuators in the thermo-piezoelectric material are randomly distributed on both sides of the plate to establish the control procedure. A Monte Carlo simulation is used in the selection of the degrees of freedom of sensors presenting high electrical outputs. Numerical simulations are performed to demonstrate the effectiveness of the proposed control procedure in a reduced model and under mechanical and thermal disturbances in comparison with the LQR control.
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Chatzinikos, Miltiadis, and Athanasios Dermanis. "A coordinate-invariant model for deforming geodetic networks: understanding rank deficiencies, non-estimability of parameters, and the effect of the choice of minimal constraints." Journal of Geodesy 91, no. 4 (November 30, 2016): 375–96. http://dx.doi.org/10.1007/s00190-016-0970-1.

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46

Wagner, David, and Wolfgang Schlüter. "Model-Based Computation of Critical Operation Points in Biogas Producing Plants." Applied Mechanics and Materials 882 (July 2018): 45–52. http://dx.doi.org/10.4028/www.scientific.net/amm.882.45.

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Reducing the use of fossil fuels for energy production is one of the main objectives in 21st century. In order to achieve this target renewable energy resources (like agricultural waste) in biogas plants can be used. An anaerobic bacterial fermentation process digests the substrates into methane and carbon dioxide. The process itself has strong fluctuations in terms of net methane yield due to different amounts and composition of agricultural influents. For increasing the space time yield two main difficulties are encountered. The first one is system-specific and includes stirrer design and reactor geometry. The second affects the biotechnological fermentation process. The following work is focusing on the fermentation process. The determination of critical parameters for the optimization of the anaerobic microbial digestion is investigated. An economic approach for solving these problems is only feasible by using mathematical models and simulation. Consequently two fermentation models are compared by regarding parameter sensitivity and critical operational points. The first one is based on simple Monod-kinetics while the second one is extended with two steps of fermentation and therefore two different microbial consortia and additive inhibition effects. The complex model is able to describe different phenomena in more detail. But its estimability and therefore its validation is difficult without further investigation of the model structure and the reduction of the model complexity. One important result of the investigation is that stable process conditions with simultaneous high yields are depending on a careful adjustment of the loading rate and therefore requiring precise model parameters.
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Frutuoso, Adriano, Felipe O. Silva, and Ettore A. de Barros. "Influence of Integration Schemes and Maneuvers on the Initial Alignment and Calibration of AUVs: Observability and Degree of Observability Analyses." Sensors 22, no. 9 (April 25, 2022): 3287. http://dx.doi.org/10.3390/s22093287.

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The use of autonomous underwater vehicles (AUV) has increased in a wide range of sectors, including the oil and gas industry, military, and marine research. The AUV capabilities to operate without a direct human operator and untethered to a support vessel are features that have aroused interest in the marine environment. The localization of AUV is significantly affected by the initial alignment and the calibration of the navigation sensors. In this sense, this paper proposes a thorough observability analysis applied to the latter problem. The observability analysis is carried out considering three types of sensor fusion integration and a set of maneuvers, and the results are validated through numerical simulations. As main contribution of this paper, it is shown how the addition of position errors in the observation vector can decouple some gyro and accelerometer biases from the latitude and altitude errors, particularly in the stationary observability analysis. The influence of oscillations in the diving plane and typical AUV maneuvers are analyzed, showing their relative impacts on the degree of observability of the inertial measurement unit (IMU)/Doppler velocity log (DVL) misalignment and DVL scale factor error. Finally, the state’s estimation accuracy is also analyzed, showing the limitation of the degree of observability as an assessment tool for the estimability of the states.
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Frutuoso, Adriano, Felipe O. Silva, and Ettore A. de Barros. "Influence of Integration Schemes and Maneuvers on the Initial Alignment and Calibration of AUVs: Observability and Degree of Observability Analyses." Sensors 22, no. 9 (April 25, 2022): 3287. http://dx.doi.org/10.3390/s22093287.

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The use of autonomous underwater vehicles (AUV) has increased in a wide range of sectors, including the oil and gas industry, military, and marine research. The AUV capabilities to operate without a direct human operator and untethered to a support vessel are features that have aroused interest in the marine environment. The localization of AUV is significantly affected by the initial alignment and the calibration of the navigation sensors. In this sense, this paper proposes a thorough observability analysis applied to the latter problem. The observability analysis is carried out considering three types of sensor fusion integration and a set of maneuvers, and the results are validated through numerical simulations. As main contribution of this paper, it is shown how the addition of position errors in the observation vector can decouple some gyro and accelerometer biases from the latitude and altitude errors, particularly in the stationary observability analysis. The influence of oscillations in the diving plane and typical AUV maneuvers are analyzed, showing their relative impacts on the degree of observability of the inertial measurement unit (IMU)/Doppler velocity log (DVL) misalignment and DVL scale factor error. Finally, the state’s estimation accuracy is also analyzed, showing the limitation of the degree of observability as an assessment tool for the estimability of the states.
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Yagyaev, Elmar. "Determining deviations of output variables from forecast values in system for monitoring external round grinding process." MATEC Web of Conferences 224 (2018): 01127. http://dx.doi.org/10.1051/matecconf/201822401127.

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The article considers the estimability of the deviations of actual output variable values from the forecast ones in the system for monitoring the process of external round grinding. The author proposes the method for determining the deviations and establishing their most probable values as well as for establishing the cause of such output variable value deviations and technological system changes. It is substantiated that the determination of the output variable deviations and the parameters of the technological system state is possible at the control of the output variable change rate as the interruption time intervals are different for different subsystems. The authors managed to determine the dependences of the deviations of actual values (t) from the estimated ones yр(t). To resolve the objective of identifying the causes of output value deviations from the forecast ones, the authors applied the method for determining the indirect measurement errors. The obtained dependences made the authors draw the conclusion that at the control of the change rate of output variable values one is able to find out the disturbance type and the type of the deviation of output variable actual values in the technical system. This provides for the opportunity to correct the control of the external round grinding process as well as to calculate the time intervals at which one needs to take into account some or other changes in the technological system.
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Limberger, M., W. Liang, M. Schmidt, D. Dettmering, M. Hernández-Pajares, and U. Hugentobler. "Correlation studies for B-spline modeled F2 Chapman parameters obtained from FORMOSAT-3/COSMIC data." Annales Geophysicae 32, no. 12 (December 17, 2014): 1533–45. http://dx.doi.org/10.5194/angeo-32-1533-2014.

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Abstract. The determination of ionospheric key quantities such as the maximum electron density of the F2 layer NmF2, the corresponding F2 peak height hmF2 and the F2 scale height HF2 are of high relevance in 4-D ionosphere modeling to provide information on the vertical structure of the electron density (Ne). The Ne distribution with respect to height can, for instance, be modeled by the commonly accepted F2 Chapman layer. An adequate and observation driven description of the vertical Ne variation can be obtained from electron density profiles (EDPs) derived by ionospheric radio occultation measurements between GPS and low Earth orbiter (LEO) satellites. For these purposes, the six FORMOSAT-3/COSMIC (F3/C) satellites provide an excellent opportunity to collect EDPs that cover most of the ionospheric region, in particular the F2 layer. For the contents of this paper, F3/C EDPs have been exploited to determine NmF2, hmF2 and HF2 within a regional modeling approach. As mathematical base functions, endpoint-interpolating polynomial B-splines are considered to model the key parameters with respect to longitude, latitude and time. The description of deterministic processes and the verification of this modeling approach have been published previously in Limberger et al. (2013), whereas this paper should be considered as an extension dealing with related correlation studies, a topic to which less attention has been paid in the literature. Relations between the B-spline series coefficients regarding specific key parameters as well as dependencies between the three F2 Chapman key parameters are in the main focus. Dependencies are interpreted from the post-derived correlation matrices as a result of (1) a simulated scenario without data gaps by taking dense, homogenously distributed profiles into account and (2) two real data scenarios on 1 July 2008 and 1 July 2012 including sparsely, inhomogeneously distributed F3/C EDPs. Moderate correlations between hmF2 and HF2 as well as inverse correlations between NmF2 and HF2 are reflected from the simulation. By means of the real data studies, it becomes obvious that the sparse measurement distribution leads to an increased weighting of the prior information and suppresses the parameter correlations which play an important role regarding the parameter estimability. The currently implemented stochastic model is in need of improvement and does not consider stochastic correlations which consequently cannot occur.

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