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Relevant bibliographies by topics / Optimal estimation of parameters

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Academic literature on the topic 'Optimal estimation of parameters'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Optimal estimation of parameters"

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Bashier, Eihab B. M. "Estimation of the Optimal Regularization Parameters in Optimal Control Problems with time delay." JOURNAL OF ADVANCES IN MATHEMATICS 12, no. 9 (September 21, 2016): 6589–602. http://dx.doi.org/10.24297/jam.v12i9.129.

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In this paper we use the L-curve method and the Morozov discrepancy principle for the estimation of the regularization parameter in the regularization of time-delayed optimal control computation. Zeroth order, first order and second order differential operators are considered. Two test examples show that the L-curve method and the two discrepancy principles give close estimations for the regularization parameters.

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Banks, H. T., and K. L. Rehm. "PARAMETER ESTIMATION IN DISTRIBUTED SYSTEMS: OPTIMAL DESIGN." Eurasian Journal of Mathematical and Computer Applications 2, no. 1 (2014): 70–80. http://dx.doi.org/10.32523/2306-3172-2014-2-1-70-80.

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Jin, Hanqing, and Shige Peng. "Optimal unbiased estimation for maximal distribution." Probability, Uncertainty and Quantitative Risk 6, no. 3 (2021): 189. http://dx.doi.org/10.3934/puqr.2021009.

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<p style='text-indent:20px;'>Unbiased estimation for parameters of maximal distribution is a fundamental problem in the statistical theory of sublinear expectations. In this paper, we proved that the maximum estimator is the largest unbiased estimator for the upper mean and the minimum estimator is the smallest unbiased estimator for the lower mean.</p>

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Brack, A. "Optimal Estimation of a Subset of Integers with Application to GNSS." Artificial Satellites 51, no. 4 (December 1, 2016): 123–34. http://dx.doi.org/10.1515/arsa-2016-0011.

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Abstract The problem of integer or mixed integer/real valued parameter estimation in linear models is considered. It is a well-known result that for zero-mean additive Gaussian measurement noise the integer least-squares estimator is optimal in the sense of maximizing the probability of correctly estimating the full vector of integer parameters. In applications such as global navigation satellite system ambiguity resolution, it can be beneficial to resolve only a subset of all integer parameters. We derive the estimator that leads to the highest possible success rate for a given integer subset and compare its performance to suboptimal integer mappings via numerical studies. Implementation aspects of the optimal estimator as well as subset selection criteria are discussed.

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Cummins, Donald P., David B. Stephenson, and Peter A. Stott. "Optimal Estimation of Stochastic Energy Balance Model Parameters." Journal of Climate 33, no. 18 (September 15, 2020): 7909–26. http://dx.doi.org/10.1175/jcli-d-19-0589.1.

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AbstractThis study has developed a rigorous and efficient maximum likelihood method for estimating the parameters in stochastic energy balance models (with any k > 0 number of boxes) given time series of surface temperature and top-of-the-atmosphere net downward radiative flux. The method works by finding a state-space representation of the linear dynamic system and evaluating the likelihood recursively via the Kalman filter. Confidence intervals for estimated parameters are straightforward to construct in the maximum likelihood framework, and information criteria may be used to choose an optimal number of boxes for parsimonious k-box emulation of atmosphere–ocean general circulation models (AOGCMs). In addition to estimating model parameters the method enables hidden state estimation for the unobservable boxes corresponding to the deep ocean, and also enables noise filtering for observations of surface temperature. The feasibility, reliability, and performance of the proposed method are demonstrated in a simulation study. To obtain a set of optimal k-box emulators, models are fitted to the 4 × CO2 step responses of 16 AOGCMs in CMIP5. It is found that for all 16 AOGCMs three boxes are required for optimal k-box emulation. The number of boxes k is found to influence, sometimes strongly, the impulse responses of the fitted models.

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Kates, James M. "Optimal estimation of hearing‐aid compression parameters." Journal of the Acoustical Society of America 94, no. 1 (July 1993): 1–12. http://dx.doi.org/10.1121/1.407078.

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NAKAMURA, Masahide. "Estimation of Optimal Parameters in Tchebychev Iteration." Transactions of the Japan Society of Mechanical Engineers Series C 65, no. 636 (1999): 3181–88. http://dx.doi.org/10.1299/kikaic.65.3181.

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Abdul Jalil, Nur Raihan, Nur Anisah Mohamed, and Rossita Mohamad Yunus. "Estimation in regret-regression using quadratic inference functions with ridge estimator." PLOS ONE 17, no. 7 (July 21, 2022): e0271542. http://dx.doi.org/10.1371/journal.pone.0271542.

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In this paper, we propose a new estimation method in estimating optimal dynamic treatment regimes. The quadratic inference functions in myopic regret-regression (QIF-MRr) can be used to estimate the parameters of the mean response at each visit, conditional on previous states and actions. Singularity issues may arise during computation when estimating the parameters in ODTR using QIF-MRr due to multicollinearity. Hence, the ridge penalty was introduced in rQIF-MRr to tackle the issues. A simulation study and an application to anticoagulation dataset were conducted to investigate the model’s performance in parameter estimation. The results show that estimations using rQIF-MRr are more efficient than the QIF-MRr.

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Sugiyama, Takatoshi, and Toru Ogura. "Parameters Estimation for Wear-out Failure Period of Three-Parameter Weibull Distribution." International Journal of Statistics and Probability 11, no. 1 (December 26, 2021): 40. http://dx.doi.org/10.5539/ijsp.v11n1p40.

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The shape parameter estimation using the minimum-variance linear estimator with hyperparameter (MVLE-H) method is believed to be effective for a wear-out failure period in a small sample. In the process of the estimation, our method uses the hyperparameter and estimate shape parameters of the MVLE-H method. To obtain the optimal hyperparameter c, it takes a long time, even in the case of the small sample. The main purpose of this paper is to remove the restriction of small samples. We observed that if we set the shape parameters, for sample size n and c, we can use the regression equation to infer the optimal c from n. So we searched in five increments and complemented the hyperparameter for the remaining sample sizes with a linear regression line. We used Monte Carlo simulations (MCSs) to determine the optimal hyperparameter for various sample sizes and shape parameters of the MVLE-H method. Intrinsically, we showed that the MVLE-H method performs well by determining the hyperparameter. Further, we showed that the location and scale parameter estimations are improved using the shape parameter estimated by the MVLE-H method. We verified the validity of the MVLE-H method using MCSs and a numerical example.

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Ran, Mengfei, and Yihe Yang. "Optimal Estimation of Large Functional and Longitudinal Data by Using Functional Linear Mixed Model." Mathematics 10, no. 22 (November 17, 2022): 4322. http://dx.doi.org/10.3390/math10224322.

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The estimation of large functional and longitudinal data, which refers to the estimation of mean function, estimation of covariance function, and prediction of individual trajectory, is one of the most challenging problems in the field of high-dimensional statistics. Functional Principal Components Analysis (FPCA) and Functional Linear Mixed Model (FLMM) are two major statistical tools used to address the estimation of large functional and longitudinal data; however, the former suffers from a dramatically increasing computational burden while the latter does not have clear asymptotic properties. In this paper, we propose a computationally effective estimator of large functional and longitudinal data within the framework of FLMM, in which all the parameters can be automatically estimated. Under certain regularity assumptions, we prove that the mean function estimation and individual trajectory prediction reach the minimax lower bounds of all nonparametric estimations. Through numerous simulations and real data analysis, we show that our new estimator outperforms the traditional FPCA in terms of mean function estimation, individual trajectory prediction, variance estimation, covariance function estimation, and computational effectiveness.

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Dissertations / Theses on the topic "Optimal estimation of parameters"

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Cheung, Man-Fung. "On optimal algorithms for parameter set estimation." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1302628544.

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Iolov, Alexandre V. "Parameter Estimation, Optimal Control and Optimal Design in Stochastic Neural Models." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34866.

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This thesis solves estimation and control problems in computational neuroscience, mathematically dealing with the first-passage times of diffusion stochastic processes. We first derive estimation algorithms for model parameters from first-passage time observations, and then we derive algorithms for the control of first-passage times. Finally, we solve an optimal design problem which combines elements of the first two: we ask how to elicit first-passage times such as to facilitate model estimation based on said first-passage observations. The main mathematical tools used are the Fokker-Planck partial differential equation for evolution of probability densities, the Hamilton-Jacobi-Bellman equation of optimal control and the adjoint optimization principle from optimal control theory. The focus is on developing computational schemes for the solution of the problems. The schemes are implemented and are tested for a wide range of parameters.

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Agaba, Peter. "Optimal Control Theory and Estimation of Parameters in a Differential Equation Model for Patients with Lupus." TopSCHOLAR®, 2019. https://digitalcommons.wku.edu/theses/3118.

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System Lupus Erythematosus (SLE) is a chronic inflammatory autoimmune disorder that affects many parts of the body including skin, joints, kidneys, brains and other organs. Lupus Nephritis (LN) is a disease caused by SLE. Given the complexity of LN, we establish an optimal treatment strategy based on a previously developed mathematical model.For our thesis work, the model variables are: Immune Complexes (I), Pro-inflammatory mediators (P), Damaged tissue (D), and Anti-inflammatory mediators (A). The analysis in this research project focuses on analyzing therapeutic strategies to control damage using both parameter estimation techniques (integration of data to quantify any uncertainties associated with parameters) and optimal control with the goal of minimizing time spent on therapy for treating damaged tissue by LN.

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Alana, Jorge Enrique. "Optimal measurement locations for parameter estimation of distributed parameter systems." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/optimal-measurement-locations-for-parameter-estimation-of-distributed-parameter-systems(fffa31d8-2b19-434b-a2b6-7809e314bb55).html.

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Identifying the parameters with the largest influence on the predicted outputs of a model revealswhich parameters need to be known more precisely to reduce the overall uncertainty on themodel output. A large improvement of such models would result when uncertainties in the keymodel parameters are reduced. To achieve this, new experiments could be very helpful,especially if the measurements are taken at the spatio-temporal locations that allow estimate the parameters in an optimal way. After evaluating the methodologies available for optimal sensor location, a few observations were drawn. The method based on the Gram determinant evolution can report results not according to what should be expected. This method is strongly dependent of the sensitivity coefficients behaviour. The approach based on the maximum angle between subspaces, in some cases, produced more that one optimal solution. It was observed that this method depends on the magnitude of outputs values and report the measurement positions where the outputs reached their extrema values. The D-optimal design method produces number and locations of the optimal measurements and it depends strongly of the sensitivity coefficients, but mostly of their behaviours. In general it was observed that the measurements should be taken at the locations where the extrema values (sensitivity coefficients, POD modes and/or outputs values) are reached. Further improvements can be obtained when a reduced model of the system is employed. This is computationally less expensive and the best estimation of the parameter is obtained, even with experimental data contaminated with noise. A new approach to calculate the time coefficients belonging to an empirical approximator based on the POD-modes derived from experimental data is introduced. Additionally, an artificial neural network can be used to calculate the derivatives but only for systems without complex nonlinear behaviour. The latter two approximations are very valuable and useful especially if the model of the system is unknown.

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Chan, Chun-wang Aaron, and 陳俊弘. "Statistical estimation of haemodynamic parameters in optical coherence tomography." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/206460.

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Optical coherence tomography (OCT) is an imaging modality analogous to ultrasound. By using the interference properties of light, one may image to micrometer resolutions using interferometric methods. Most modern systems can acquire A-scans at kHz to MHz speeds, and are capable of real-time 3D imaging. OCT has been used extensively in ophthalmology and has been used in angiography to quantify blood flow. The aim of this research has been to develop statistically optimal estimators for blood flow estimation to take advantage of these hardware advances. This is achieved through a deeper understanding of the noise characteristics of OCT. Through mathematical derivations and simulations, the noise characteristics of OCT Doppler and flow imaging were accurately modelled as additive white noise and multiplicative decorrelation noise. Decorrelation arises due to relative motion of tissue relative to the OCT region of interest and adversely affects Doppler estimation. From these models maximum likelihood estimators (MLEs) that statistically outperform the commonly used Kasai autocorrelation estimator were derived. The Cramer-Rao lower bound (CRLB), which gives the theoretical lowest estimator variance for an unbiased estimator was derived for different noise regimes. It is shown that the AWGN MLE achieves the CRLB for additive white noise dominant conditions, and the decorrelation noise MLE achieves the CRLB under more general noise conditions. The use of computational algorithms that enhance the capabilities of OCT are demonstrated. This shows that this approach for determining parametric estimators may be used in a more general medical imaging context. In addition, the use of decorrelation as a measure of speed is explored, as it is itself proportional to flow speed.
published_or_final_version
Electrical and Electronic Engineering
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Doctor of Philosophy

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Helin, Mikael. "Inverse Parameter Estimation using Hamilton-Jacobi Equations." Thesis, KTH, Numerisk analys, NA, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-123092.

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Inthis degree project, a solution on a coarse grid is recovered by fitting apartial differential equation to a few known data points. The PDE to consideris the heat equation and the Dupire’s equation with their synthetic data,including synthetic data from the Black-Scholes formula. The approach to fit aPDE is by optimal control to derive discrete approximations to regularized Hamiltoncharacteristic equations to which discrete stepping schemes, and parameters forsmoothness, are examined. By non-parametric numerical implementation thedervied method is tested and then a few suggestions on possible improvementsare given
I detta examensarbete återskapas en lösning på ett glest rutnät genom att anpassa en partiell differentialekvation till några givna datapunkter. De partiella differentialekvationer med deras motsvarande syntetiska data som betraktas är värmeledningsekvationen och Dupires ekvation inklusive syntetiska data från Black-Scholes formel. Tillvägagångssättet att anpassa en PDE är att med hjälp av optimal styrning härleda diskreta approximationer på ett system av regulariserade Hamilton karakteristiska ekvationer till vilka olika diskreta stegmetoder och parametrar för släthet undersöks. Med en icke-parametrisk numerisk implementation prövas den härledda metoden och slutligen föreslås möjliga förbättringar till metoden.

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Fraleigh, Lisa Marie. "Optimal sensor selection and parameter estimation for real-time optimization." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ40050.pdf.

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Lee, Dong Jin. "Essays on optimal tests for parameter instability." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3304195.

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Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed June 16, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 158-164).

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Said, Munzir. "Computational optimal control modeling and smoothing for biomechanical systems." University of Western Australia. Dept. of Mathematics and Statistics, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0082.

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[Truncated abstract] The study of biomechanical system dynamics consists of research to obtain an accurate model of biomechanical systems and to find appropriate torques or forces that reproduce motions of a biomechanical subject. In the first part of this study, specific computational models are developed to maintain relative angle constraints for 2-dimensional segmented bodies. This is motivated by the fact that there is a possibility of models of segmented bodies, moving under gravitational acceleration and joint torques, for its segments to move past the natural relative angle limits. Three models to maintain angle constraints between segments are proposed and compared. These models are: all-time angle constraints, a restoring torque in the state equations and an exponential penalty model. The models are applied to a 2-D three segment body to test the behaviour of each model when optimizing torques to minimize an objective. The optimization is run to find torques so that the end effector of the body follows the trajectory of a half circle. The result shows the behavior of each model in maintaining the angle constraints. The all-time constraints case exhibits a behaviour of not allowing torques (at a solution) which make segments move past the constraints, while the other two show a flexibility in handling the angle constraints more similar to a real biomechanical system. With three computational methods to represent the angle contraint, a workable set of initial torques for the motion of a segmented body can be obtained without causing integration failure in the ordinary differential equation (ODE) solver and without the need to use the “blind man method” that restarts the optimal control many times. ... With one layer of penalty weight balancing between trajectory compliance penalty and other optimal control objectives (minimizing torque/smoothing torque) already difficult to obtain (as explained by the L-curve phenomena), adding the second layer penalty weight for the closeness of fit for each of the body segments will further complicate the weight balancing and too much trial and error computation may be needed to get a reasonably good set of weighting values. Second order regularization is also added to the optimal control objective and the optimization has managed to obtain smoother torques for all body joints. To make the current approach more competitive with the inverse dynamic, an algorithm to speed up the computation of the optimal control is required as a potential future work.

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Hendriko, ? "Advanced virtual simulation for optimal cutting parameters control in five axis milling." Thesis, Clermont-Ferrand 2, 2014. http://www.theses.fr/2014CLF22464/document.

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La thèse concerne l’usinage à 5 axes de formes complexes. Le but est d’estimer le plus précisément possible les efforts induits par la coupe pour ajuster la vitesse d’avance et gagner en performance. Pour cela, il est nécessaire d’estimer les engagements radial et axial de la fraise à chaque instant. Ce calcul est rendu particulièrement complexe à cause de la forme de la pièce, de la forme du brut et de la complexité de la géométrie de l’outil. Les méthodes usuelles par Zbuffer sont particulièrement couteuses en temps de calcul. Dans ces travaux nous proposons une méthode de calcul rapide à partir d’une modélisation du contact dans toutes les situations envisageables. Différentes simulations et expérimentations ont permis de valider la précision expérimentalement
This study presents a simple method to define the Cutter Workpiece Engagement (CWE) during sculptured surface machining in five-axis milling. The instantaneous CWE was defined by determining two engagement points, lowermost engagement (LE)-point and uppermost engagement (UE)-point. LE-point was calculated using a method called grazing method. Meanwhile the UE-point was calculated using a combination of discretization and analytical method. During rough milling and semi-finish milling, the workpiece surface was represented by vertical vector. The method called Toroidal–boundary was employed to obtain the UE-point when it was located on cutting tool at toroidal side. On the other hand, the method called Cylindrical-boundary was used to calculate the UE-point for flat-end cutter and cylindrical side of toroidal cutter. For a free-form workpiece surface, a hybrid method, which is a combination of analytical method and discrete method, was used. All the CWE models proposed in this study were verified and the results proved that the proposed method were accurate. The efficiency of the proposed model in generating CWE was also compared with Z-mapping method. The result confirmed that the proposed model was more efficient in term of computational time. The CWE model was also applied for supporting the method to predict cutting forces. The test results showed that the predicted cutting force has a good agreement with the cutting force generated from the experimental work

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Books on the topic "Optimal estimation of parameters"

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Optimal estimation of parameters. Cambridge: Cambridge University Press, 2012.

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Chen, Youyi. Extended quasi-likelihoods and optimal estimating functions. Toronto: University of Toronto, Dept. of Statistics, 1991.

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Cheung, Man-Fung. On optimal algorithms for parameter set estimation. [Ohio]: Ohio State University, 1991.

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Quasi-likelihood and its application: A general approach to optimal parameter estimation. New York: Springer, 1997.

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Di qiu zi zhuan can shu di chong xin gui suan: Gen ju 1962.0-1982.0 guang xue tian wen guan ce = New determination of the earth rotation parameters from optical astrometry observations, 1962.0-1982.0. Shanghai: Shanghai ke xue ji shu chu ban she, 1986.

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Bock, Hans Georg. Model Based Parameter Estimation: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Bukata, R. P. Application of direct measurements of optical parameters to the estimation of lake water quality indicators. Burlington, Ont: Inland Waters Directorate, 1985.

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Directorate, Canada Environment Canada Inland Waters. Application of Direct Measurements of Optical Parameters to the Estimation of Lake Water Quality Indicators. S.l: s.n, 1985.

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Giraitis, Liudas. Rate optimal semiparametric estimation of the memory parameter of the gaussian time series withlong range dependence. London: Suntory and Toyota International Centres for Economics and Related Disciplines, 1997.

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Simon, Dan. Optimal State Estimation. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/0470045345.

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Book chapters on the topic "Optimal estimation of parameters"

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Marchini, Stefania, and N. Alberto Borghese. "Optimal Local Estimation of RBF Parameters." In ICANN ’94, 463–66. London: Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-2097-1_109.

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Sun, Ne-Zheng, and Alexander Sun. "Optimal Experimental Design." In Model Calibration and Parameter Estimation, 459–507. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2323-6_11.

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Sinha, B. K., N. K. Mandal, Manisha Pal, and P. Das. "Optimal Mixture Designs for Estimation of Natural Parameters in Scheffé’s Models." In Optimal Mixture Experiments, 43–61. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1786-2_4.

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Skala, Vaclav, Samsul Ariffin Abdul Karim, and Marek Zabran. "Radial Basis Function Approximation Optimal Shape Parameters Estimation." In Lecture Notes in Computer Science, 309–17. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50433-5_24.

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Pardalos, Panos M., Pavel S. Knopov, Stanislav P. Uryasev, and Vitaliy A. Yatsenko. "Optimal Estimation of Signal Parameters Using Bilinear Observations." In Applied Optimization, 103–17. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-6099-6_8.

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Sinha, B. K., N. K. Mandal, Manisha Pal, and P. Das. "Optimal Mixture Designs for Estimation of Natural Parameters in Other Mixture Models." In Optimal Mixture Experiments, 75–85. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1786-2_6.

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Cui, Yuntao, John Weng, and Herbert Reynolds. "Optimal parameter estimation of ellipses." In Image Analysis and Processing, 471–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60298-4_300.

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Poon, C. S. "Optimal Regulation of Ventilation During Exercise." In Modeling and Parameter Estimation in Respiratory Control, 25–37. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-0621-4_3.

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Sinha, B. K., N. K. Mandal, Manisha Pal, and P. Das. "Parameter Estimation in Linear and Quadratic Mixture Models." In Optimal Mixture Experiments, 23–42. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1786-2_3.

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Sinha, B. K., N. K. Mandal, Manisha Pal, and P. Das. "Optimal Mixture Designs for Estimation of Natural Parameters in Scheffé’s Model Under Constrained Factor Space." In Optimal Mixture Experiments, 63–73. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1786-2_5.

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Conference papers on the topic "Optimal estimation of parameters"

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Church, Eugene L., and Peter Z. Takacs. "Optimal estimation of finish parameters." In San Diego, '91, San Diego, CA, edited by John C. Stover. SPIE, 1991. http://dx.doi.org/10.1117/12.50498.

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Burke, Daniel, Nicholas Devaney, Szymon Gladysz, Harrisson H. Barrett, Meredith K. Whitaker, and Luca Caucci. "Optimal linear estimation of binary star parameters." In SPIE Astronomical Telescopes + Instrumentation, edited by Norbert Hubin, Claire E. Max, and Peter L. Wizinowich. SPIE, 2008. http://dx.doi.org/10.1117/12.788973.

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SAVANI, V. "OPTIMAL ESTIMATION OF PARAMETERS IN MARKET RESEARCH MODELS." In Computer Aided Methods in Optimal Design and Operations. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772954_0009.

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Yilmaz, Yasin, George V. Moustakides, and Xiaodong Wang. "Optimal sequential parameter estimation." In 2013 IEEE International Symposium on Information Theory (ISIT). IEEE, 2013. http://dx.doi.org/10.1109/isit.2013.6620696.

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Loulou, Tahar, and Elaine P. Scott. "Multi-Parameter Estimation in Hyperthermia Problem by Using an Optimal Choice of Descent Parameters in Iterative Methods." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-33693.

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This paper describes a numerical procedure conducted to estimate thermo-physical properties of the human tissue during hyperthermia treatment of a cancerous region. The estimation algorithm is based on the solution of an inverse heat conduction problem. The Gauss-Newton method is used to estimate simultaneously the volumetric heat capacity, the thermal conductivity, and the volumetric blood rate (blood perfusion) in the bio-heat transfer equation during a hyperthermia treatment cycle. The treatment quality of hyperthermia is analyzed by the computation of the thermal dose which is obtained from the resulting temperature field in the tissue. The importance of an accurate estimation of the thermo-physical properties of the tissue lies in that they are the most important factors for achieving a high precision heating cycle which results in an optimized treatment. The inverse analysis is based on the temperature measurements taken inside the cancerous tissue region during the transient heating process. An experimental optimization procedure is conducted to make the estimated parameters as accurate as possible. Several numerical tests were performed and show that the developed method provides an accurate estimation of thermo-physical properties in a very short practical time. As the blood perfusion is very sensitive to the temperature variation in the tissue, this estimation tool can be implemented during one cycle treatment which results in an on-line thermo-physical parameter correction while the treatment is performed.

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Sultanov, Mahsud M., Ilya A. Boldyrev, Kirill V. Evseev, and Nikita S. Khlyustov. "Estimation of the optimal record interval of the technological parameters." In 2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). IEEE, 2023. http://dx.doi.org/10.1109/reepe57272.2023.10086827.

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Cafarelli, Sergio, Anthony Hebert, and Jonathan Shaver. "An Investigation into Optimal Estimation of Open Architecture Performance Parameters." In 2018 AIAA Information Systems-AIAA Infotech @ Aerospace. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2018. http://dx.doi.org/10.2514/6.2018-1803.

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Molzahn, Daniel K., Zev B. Friedman, Bernard C. Lesieutre, Christopher L. DeMarco, and Michael C. Ferris. "Estimation of constraint parameters in optimal power flow data sets." In 2015 North American Power Symposium (NAPS). IEEE, 2015. http://dx.doi.org/10.1109/naps.2015.7335092.

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Vaccaro, R. J., and Y. Ding. "Optimal subspace-based parameter estimation." In Proceedings of ICASSP '93. IEEE, 1993. http://dx.doi.org/10.1109/icassp.1993.319671.

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Simon, Donald L., and Sanjay Garg. "Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation." In ASME Turbo Expo 2009: Power for Land, Sea, and Air. ASMEDC, 2009. http://dx.doi.org/10.1115/gt2009-59684.

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A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy.

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Reports on the topic "Optimal estimation of parameters"

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Yaroshchuk, Svitlana O., Nonna N. Shapovalova, Andrii M. Striuk, Olena H. Rybalchenko, Iryna O. Dotsenko, and Svitlana V. Bilashenko. Credit scoring model for microfinance organizations. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3683.

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The purpose of the work is the development and application of models for scoring assessment of microfinance institution borrowers. This model allows to increase the efficiency of work in the field of credit. The object of research is lending. The subject of the study is a direct scoring model for improving the quality of lending using machine learning methods. The objective of the study: to determine the criteria for choosing a solvent borrower, to develop a model for an early assessment, to create software based on neural networks to determine the probability of a loan default risk. Used research methods such as analysis of the literature on banking scoring; artificial intelligence methods for scoring; modeling of scoring estimation algorithm using neural networks, empirical method for determining the optimal parameters of the training model; method of object-oriented design and programming. The result of the work is a neural network scoring model with high accuracy of calculations, an implemented system of automatic customer lending.

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Bonfil, David J., Daniel S. Long, and Yafit Cohen. Remote Sensing of Crop Physiological Parameters for Improved Nitrogen Management in Semi-Arid Wheat Production Systems. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7696531.bard.

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To reduce financial risk and N losses to the environment, fertilization methods are needed that improve NUE and increase the quality of wheat. In the literature, ample attention is given to grid-based and zone-based soil testing to determine the soil N available early in the growing season. Plus, information is available on in-season N topdressing applications as a means of improving GPC. However, the vast majority of research has focused on wheat that is grown under N limiting conditions in sub-humid regions and irrigated fields. Less attention has been given to wheat in dryland that is water limited. The objectives of this study were to: (1) determine accuracy in determining GPC of HRSW in Israel and SWWW in Oregon using on-combine optical sensors under field conditions; (2) develop a quantitative relationship between image spectral reflectance and effective crop physiological parameters; (3) develop an operational precision N management procedure that combines variable-rate N recommendations at planting as derived from maps of grain yield, GPC, and test weight; and at mid-season as derived from quantitative relationships, remote sensing, and the DSS; and (4) address the economic and technology-transfer aspects of producers’ needs. Results from the research suggest that optical sensing and the DSS can be used for estimating the N status of dryland wheat and deciding whether additional N is needed to improve GPC. Significant findings include: 1. In-line NIR reflectance spectroscopy can be used to rapidly and accurately (SEP <5.0 mg g⁻¹) measure GPC of a grain stream conveyed by an auger. 2. On-combine NIR spectroscopy can be used to accurately estimate (R² < 0.88) grain test weight across fields. 3. Precision N management based on N removal increases GPC, grain yield, and profitability in rainfed wheat. 4. Hyperspectral SI and partial least squares (PLS) models have excellent potential for estimation of biomass, and water and N contents of wheat. 5. A novel heading index can be used to monitor spike emergence of wheat with classification accuracy between 53 and 83%. 6. Index MCARI/MTVI2 promises to improve remote sensing of wheat N status where water- not soil N fertility, is the main driver of plant growth. Important features include: (a) computable from commercial aerospace imagery that include the red edge waveband, (b) sensitive to Chl and resistant to variation in crop biomass, and (c) accommodates variation in soil reflectance. Findings #1 and #2 above enable growers to further implement an efficient, low cost PNM approach using commercially available on-combine optical sensors. Finding #3 suggests that profit opportunities may exist from PNM based on information from on-combine sensing and aerospace remote sensing. Finding #4, with its emphasis on data retrieval and accuracy, enhances the potential usefulness of a DSS as a tool for field crop management. Finding #5 enables land managers to use a DSS to ascertain at mid-season whether a wheat crop should be harvested for grain or forage. Finding #6a expands potential commercial opportunities of MS imagery and thus has special importance to a majority of aerospace imaging firms specializing in the acquisition and utilization of these data. Finding #6b on index MCARI/MVTI2 has great potential to expand use of ground-based sensing and in-season N management to millions of hectares of land in semiarid environments where water- not N, is the main determinant of grain yield. Finding #6c demonstrates that MCARI/MTVI2 may alleviate the requirement of multiple N-rich reference strips to account for soil differences within farm fields. This simplicity will be less demanding of grower resources, promising substantially greater acceptance of sensing technologies for in-season N management.

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Ramos, Nuno M. M., Joana Maia, Rita Carvalho Veloso, Andrea Resende Souza, Catarina Dias, and João Ventura. Envelope systems with high solar reflectance by the inclusion of nanoparticles – an overview of the EnReflect Project. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541621982.

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High reflectance materials constitute an attractive idea to reduce cooling loads, which is crucial for attaining the Nearly Zero Energy Buildings goal, also presenting the benefit of broadening the range of colours applicable in building facades. The EnReflect project intended to re-design envelope systems by increasing their solar reflectance through nanotechnology. The main idea was to produce novel nanomaterial-based coatings with high near-infrared (NIR) reflectance by tuning their optical properties and testing their compatibility with typical insulation technologies such as ETICS. As such, this project focused on the synthesis of nanoparticles with improved NIR reflectance, the evaluation of the hygrothermal-mechanical behaviour of thermal insulation systems with the application of the improved coating solutions, the characterization of the more relevant material properties and the durability assessment. One of the main achievements was the development of a facile synthesis of a nanocomposite with improved performance in the NIR region that allowed the reflectance improvement of a dark-finishing coating. Also, the incorporation of such nanoparticles had a positive effect on keeping their optical properties after accelerated ageing cycles. The development of numerical simulations allowed the estimation of the maximum surface temperature in Mediterranean climates under different optical parameters. The study of the hygrothermal behaviour of thermal enhanced façades led to the development of a new durability assessment methodology which contributed to closing a standardization gap.

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Ljung, Lennart, Sanjoy K. Mitter, and Jose M. Moura. Optimal Recursive Maximum Likelihood Estimation,. Fort Belvoir, VA: Defense Technical Information Center, March 1987. http://dx.doi.org/10.21236/ada187980.

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Yu, Bin. Optimal Universal Coding and Density Estimation. Fort Belvoir, VA: Defense Technical Information Center, November 1994. http://dx.doi.org/10.21236/ada290694.

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Evans, James, David Kretschmann, and David Green. Procedures for estimation of Weibull parameters. Madison, WI: U.S. Department of Agriculture, Forest Service, Forest Products Laboratory, 2019. http://dx.doi.org/10.2737/fpl-gtr-264.

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Liu, Jing, Channing Arndt, and Thomas Hertel. Parameter Estimation and Measures of Fit in A Global, General Equilibrium Model. GTAP Working Paper, March 2003. http://dx.doi.org/10.21642/gtap.wp24.

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Computable General Equilibrium (CGE) models have been widely used for quantitative analysis of global economic issues. However, CGE models are frequently criticized for resting on weak empirical foundations. This paper builds on recent work in macro-econometric estimation, developing an approach to parameter estimation for a widely employed global CGE model, the Global Trade Analysis Project (GTAP) model. An approximate likelihood function is developed and the set of optimum elasticity values is obtained by maximizing this approximate likelihood function in the context of a back casting exercise. In addition, two statistical tests are performed. The first of these tests compares the standard GTAP elasticity vector with the estimated trade elasticity vector. It rejects the null hypothesis of equality between the two sets of trade elasticities. The second test examines the widely maintained hypothesis known as the “rule of two”, by which the elasticity of substitution across imports by sources is set equal to twice the elasticity of substitution between domestic goods and imports. We fail to reject this common rule of thumb. We conclude that there is much to be gained by nesting CGE models within an estimation framework as this opens the way for formal evaluation of model performance and parameterization.

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Egbert, G. D. New approaches to estimation of magnetotelluric parameters. Office of Scientific and Technical Information (OSTI), January 1991. http://dx.doi.org/10.2172/7269806.

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Canavan, G. H. Estimation of Damage Preference From Strike Parameters. Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/763149.

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Craver, Scott A. Estimation of Information Hiding Algorithms and Parameters. Fort Belvoir, VA: Defense Technical Information Center, February 2007. http://dx.doi.org/10.21236/ada464991.

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