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Relevant bibliographies by topics / Least Squares Adjustment (LSA)

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Academic literature on the topic 'Least Squares Adjustment (LSA)'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 January 2023

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Journal articles on the topic "Least Squares Adjustment (LSA)"

1

Ravi, Radhika, and Ayman Habib. "Least Squares Adjustment with a Rank-Deficient Weight Matrix and Its Applicability to Image/Lidar Data Processing." Photogrammetric Engineering & Remote Sensing 87, no. 10 (2021): 717–33. http://dx.doi.org/10.14358/pers.20-00081r3.

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This article proposes a solution to special least squares adjustment (LSA) models with a rank-deficient weight matrix, which are commonly encountered in geomatics. The two sources of rank deficiency in weight matrices are discussed: naturally occurring due to the inherent characteristics of LSA mathematical models and artificially induced to eliminate nuisance parameters from LSA estimation. The physical interpretation of the sources of rank deficiency is demonstrated using a case study to solve the problem of 3D line fitting, which is often encountered in geomatics but has not been addressed

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Xiao, Feng, Fei Li, Shengkai Zhang, Jiaxing Li, Tong Geng, and Yue Xuan. "Estimating Arctic Sea Ice Thickness with CryoSat-2 Altimetry Data Using the Least Squares Adjustment Method." Sensors 20, no. 24 (2020): 7011. http://dx.doi.org/10.3390/s20247011.

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Satellite altimeters can be used to derive long-term and large-scale sea ice thickness changes. Sea ice thickness retrieval is based on measurements of freeboard, and the conversion of freeboard to thickness requires knowledge of the snow depth and snow, sea ice, and sea water densities. However, these parameters are difficult to be observed concurrently with altimeter measurements. The uncertainties in these parameters inevitably cause uncertainties in sea ice thickness estimations. This paper introduces a new method based on least squares adjustment (LSA) to estimate Arctic sea ice thickness

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Zulkifli, Akram, Mohd Azwan Abbas, Norshahrizan Mohd Hashim, Mohamad Asrul Mustafar, and Ashraf Abdullah. "Reliability of using LS-VCE computation in Deriving Variances for Multi-Classes Dataset." IOP Conference Series: Earth and Environmental Science 1051, no. 1 (2022): 012002. http://dx.doi.org/10.1088/1755-1315/1051/1/012002.

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Abstract Stochastic modelling (SM) plays an essential role in least-squares adjustment (LSA), especially for geodetic network data processing. Estimated variances derived from SM are vital factors in determining the reliability of the computed parameter vectors and ensuring the sensitivity of adjustment outcomes toward outliers. As there are multi-source of datasets consisting various of data quality, there is still room for improvement when positional accuracy becomes the main priority. Concerning the accuracy argument, legacy datasets that were exploited in establishing the National Digital

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Chen, Qusen, Hua Chen, Weiping Jiang, Xiaohui Zhou, and Peng Yuan. "A New Cycle Slip Detection and Repair Method for Single-Frequency GNSS Data." Journal of Navigation 71, no. 6 (2018): 1492–510. http://dx.doi.org/10.1017/s0373463318000243.

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Cycle slip detection for single frequency Global Navigation Satellite System (GNSS) data is currently mainly based on measurement modelling or prediction, which cannot be effectively performed for kinematic applications and it is difficult to detect or repair small cycle slips such as half-cycle slips. In this paper, a new method that is based on the total differential of ambiguity and Least-Squares Adjustment (LSA) for cycle slip detection and repair is introduced and validated. This method utilises only carrier-phase observations to build an ambiguity function. LSA is then conducted for dete

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Schulze, M. J., F. Thiemann, and M. Sester. "Using Semantic Distance to Support Geometric Harmonisation of Cadastral and Topographical Data." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-2 (November 11, 2014): 15–22. http://dx.doi.org/10.5194/isprsannals-ii-2-15-2014.

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In the context of geo-data infrastructures users may want to combine data from different sources and expect consistent data. If both datasets are maintained separately, different capturing methods and intervals leads to inconsistencies in geometry and semantic, even if the same reality has been modelled. Our project aims to automatically harmonize such datasets and to allow an efficient actualisation of the semantics. The application domain in our project is cadastral and topographic datasets. To resolve geometric conflicts between topographic and cadastral data a local nearest neighbour metho

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Santiago-Angarita, José Libardo, and Olga Lucy Rincón-Leal. "Regresión lineal de mínimos cuadrados para la carga y descarga de un condensador." Eco matemático 6, no. 1 (2015): 34. http://dx.doi.org/10.22463/17948231.454.

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ResumenEl objetivo es determinar experimentalmente el proceso de carga y descarga de un condensador estando conectado en serie con una resistencia y una fuente de corriente continua, utilizando para ello los métodos numéricos en el proceso de ajuste de curvas a través de la regresión lineal de mínimos cuadrados, y con ayuda del software matemático Matlab se realizó la construcción de las respectivas curvas. Se estableció una relación entre el voltaje y el tiempo, formándose así una gráfica exponencial; se dedujeron las relaciones existentes y el comportamiento del fenómeno, dadas las ecuacione

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Yang, Zhouming, Xin Liu, Jinyun Guo, Yaowei Xia, and Xiaotao Chang. "An Enhanced Method for Detecting and Repairing the Cycle Slips of Dual-Frequency Onboard GPS Receivers of LEO Satellites." Journal of Sensors 2020 (November 26, 2020): 1–17. http://dx.doi.org/10.1155/2020/8817626.

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Cycle slip detection and repair play important roles in the processing of data from dual-frequency GPS receivers onboard low-Earth orbit (LEO) satellites. To detect and repair cycle slips more comprehensively, an enhanced error method (EEM) is proposed. EEM combines single-frequency and narrow-lane carrier phase observations to construct special observations and observation equation groups. These special observations differ across time and satellite (ATS). ATS observations are constructed by three steps. The first step is differencing single-frequency and narrow-lane observations through a tim

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Liu, Jidong, Seyyed Meghdad Hasheminasab, Tian Zhou, Raja Manish, and Ayman Habib. "An Image-Aided Sparse Point Cloud Registration Strategy for Managing Stockpiles in Dome Storage Facilities." Remote Sensing 15, no. 2 (2023): 504. http://dx.doi.org/10.3390/rs15020504.

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Stockpile volume estimation plays a critical role in several industrial/commercial bulk material management applications. LiDAR systems are commonly used for this task. Thanks to Global Navigation Satellite System (GNSS) signal availability in outdoor environments, Uncrewed Aerial Vehicles (UAV) equipped with LiDAR are frequently adopted for the derivation of dense point clouds, which can be used for stockpile volume estimation. For indoor facilities, static LiDAR scanners are usually used for the acquisition of point clouds from multiple locations. Acquired point clouds are then registered to

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Hashim, N. M., A. H. Omar, S. N. M. Ramli, K. M. Omar, and N. Din. "CADASTRAL DATABASE POSITIONAL ACCURACY IMPROVEMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W5 (October 5, 2017): 91–96. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w5-91-2017.

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Positional Accuracy Improvement (PAI) is the refining process of the geometry feature in a geospatial dataset to improve its actual position. This actual position relates to the absolute position in specific coordinate system and the relation to the neighborhood features. With the growth of spatial based technology especially Geographical Information System (GIS) and Global Navigation Satellite System (GNSS), the PAI campaign is inevitable especially to the legacy cadastral database. Integration of legacy dataset and higher accuracy dataset like GNSS observation is a potential solution for imp

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Hai, G., H. Xie, J. Chen, L. Chen, R. Li, and X. Tong. "EXPERIMENTAL DEM EXTRACTION FROM ASTER STEREO PAIRS AND 3D REGISTRATION BASED ON ICESAT LASER ALTIMETRY DATA IN UPSTREAM AREA OF LAMBERT GLACIER, ANTARCTICA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W7 (September 14, 2017): 1517–20. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w7-1517-2017.

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DEM Extraction from ASTER stereo pairs and three-dimensional registration by reference to ICESat laser altimetry data are carried out in upstream area of Lambert Glacier, East Antarctica. Since the study area is located in inland of East Antarctica where few textures exist, registration between DEM and ICESat data is performed. Firstly, the ASTER DEM generation is based on rational function model (RFM) and the procedure includes: a) rational polynomial coefficient (RPC) computation from ASTER metadata, b) L1A image product de-noise and destriping, c) local histogram equalization and matching,

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Dissertations / Theses on the topic "Least Squares Adjustment (LSA)"

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Woodard, Joseph Walker. "The Linear Least Squares Problem of Bundle Adjustment." UNF Digital Commons, 1990. http://digitalcommons.unf.edu/etd/227.

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A method is described for finding the least squares solution of the overdetermined linear system that arises in the photogrammetric problem of bundle adjustment of aerial photographs. Because of the sparse, blocked structure of the coefficient matrix of the linear system, the proposed method is based on sparse QR factorization using Givens rotations. A reordering of the rows and columns of the matrix greatly reduces the fill-in during the factorization. Rules which predict the fill-in for this ordering are proven based upon the block structure of the matrix. These rules eliminate the need for

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Merritt, Roger Surveying &amp Spatial Information Systems Faculty of Engineering UNSW. "An assessment of using least squares adjustment to upgrade spatial data in GIS." Awarded by:University of New South Wales. Surveying and Spatial Information Systems, 2005. http://handle.unsw.edu.au/1959.4/23003.

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The GIS Industry has digitised cadastre from the best available paper maps over the last few decades, incorporating the inherent errors in those paper maps and in the digitising process. The advent of Global Positioning Systems, modern surveying instruments and advances in the computing industry has made it desirable and affordable to upgrade the placement, in terms of absolute and relative position) of these digital cadastres. The Utility Industry has used GIS software to place their assets relative to these digital cadastres, and are now finding their assets placed incorrectly when viewed ag

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Snow, Kyle Brian. "Topics in Total Least-Squares Adjustment within the Errors-In-Variables Model: Singular Cofactor Matrices and Prior Information." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354677123.

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Lehmann, Rüdiger. "The 3σ-rule for outlier detection from the viewpoint of geodetic adjustment". Hochschule für Technik und Wirtschaft Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:520-qucosa-158886.

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The so-called 3σ-rule is a simple and widely used heuristic for outlier detection. This term is a generic term of some statistical hypothesis tests whose test statistics are known as normalized or studentized residuals. The conditions, under which this rule is statistically substantiated, were analyzed, and the extent it applies to geodetic least-squares adjustment was investigated. Then, the efficiency or non-efficiency of this method was analyzed and demonstrated on the example of repeated observations<br>Die sogenannte 3σ-Regel ist eine einfache und weit verbreitete Heuristik für die Ausrei

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Lehmann, Rüdiger. "The 3σ-rule for outlier detection from the viewpoint of geodetic adjustment". American Society of Civil Engineers, 2013. https://htw-dresden.qucosa.de/id/qucosa%3A23281.

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The so-called 3σ-rule is a simple and widely used heuristic for outlier detection. This term is a generic term of some statistical hypothesis tests whose test statistics are known as normalized or studentized residuals. The conditions, under which this rule is statistically substantiated, were analyzed, and the extent it applies to geodetic least-squares adjustment was investigated. Then, the efficiency or non-efficiency of this method was analyzed and demonstrated on the example of repeated observations.<br>Die sogenannte 3σ-Regel ist eine einfache und weit verbreitete Heuristik für die Ausre

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Hong, Je Hyeong. "Widening the basin of convergence for the bundle adjustment type of problems in computer vision." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/275067.

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Bundle adjustment is the process of simultaneously optimizing camera poses and 3D structure given image point tracks. In structure-from-motion, it is typically used as the final refinement step due to the nonlinearity of the problem, meaning that it requires sufficiently good initialization. Contrary to this belief, recent literature showed that useful solutions can be obtained even from arbitrary initialization for fixed-rank matrix factorization problems, including bundle adjustment with affine cameras. This property of wide convergence basin of high quality optima is desirable for any nonli

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Quesada, Olmo María Nieves. "Desarrollo y análisis de un sistema para la determinación de la dinámica del movimiento más general de la azotea de un edificio de gran altura y su evolución en el tiempo." Doctoral thesis, Universitat Politècnica de València, 2019. http://hdl.handle.net/10251/58993.

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[EN] The goal of this research is to analise and to develop a system that allows the determination of the most general movement dynamics of a tall building, as well as to quantify its evolution over time by means of Gaussian algorithms revision and by applying GNSS techniques and methodologies. In this thesis, the oscillation of the control quadrilateral located on the roof of the ``Torre Espacio'' bulding and determined by a high precision survey network is assessed rigorously with the method of sequential solution with addition of variables or parameters using VRS-RTK techniques. It is th

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Rybecký, Pavel. "Vybudování sítě PPBP v katastrálním území Vysoká u Valašského Meziříčí." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2013. http://www.nusl.cz/ntk/nusl-226213.

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The main fokus of this D thesis consists in the creating of horizontal points in Lešná village that is closed to Valašské Meziříčí, part Vysoká. Sixty five points of horizontal control (PPBP) were located and set in Vysoká. The network adjustment was done with the help of the method of lest squares and coordinates were counted with the G-NET/Mini programme.

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Lehmann, Rüdiger, and Michael Lösler. "Multiple Outlier Detection: Hypothesis Tests versus Model Selection by Information Criteria." Hochschule für Technik und Wirtschaft Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:520-qucosa-225770.

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The detection of multiple outliers can be interpreted as a model selection problem. Models that can be selected are the null model, which indicates an outlier free set of observations, or a class of alternative models, which contain a set of additional bias parameters. A common way to select the right model is by using a statistical hypothesis test. In geodesy data snooping is most popular. Another approach arises from information theory. Here, the Akaike information criterion (AIC) is used to select an appropriate model for a given set of observations. The AIC is based on the Kullback-Leibler

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Lehmann, Rüdiger, and Michael Lösler. "Multiple Outlier Detection: Hypothesis Tests versus Model Selection by Information Criteria." Hochschule für Technik und Wirtschaft Dresden, 2016. https://htw-dresden.qucosa.de/id/qucosa%3A23307.

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The detection of multiple outliers can be interpreted as a model selection problem. Models that can be selected are the null model, which indicates an outlier free set of observations, or a class of alternative models, which contain a set of additional bias parameters. A common way to select the right model is by using a statistical hypothesis test. In geodesy data snooping is most popular. Another approach arises from information theory. Here, the Akaike information criterion (AIC) is used to select an appropriate model for a given set of observations. The AIC is based on the Kullback-Leibler

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Books on the topic "Least Squares Adjustment (LSA)"

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Milbert, Dennis G. ADJUST: The horizontal observation adjustment program. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Charting and Geodetic Services, 1987.

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Milbert, Dennis G. ADJUST: The horizontal observation adjustment program. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Charting and Geodetic Services, 1987.

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Milbert, Dennis G. ADJUST: The horizontal observation adjustment program. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Ocean Service, Charting and Geodetic Services, 1987.

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4

Bakker, G. Radio positioning at sea: Geodetic survey computations : least squares adjustment. Delft University Press, 1989.

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5

Blais, J. A. R. Least-squares block adjustment of stereoscopic models and error analysis. University of Calgary, Division of Surveying Engineering, 1985.

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Bakker, G. Radio positioning at sea: Geodetic survey computations : least squares adjustment. Delft University Press, 1989.

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D, Ghilani Charles, ed. Adjustment computations: Statistics and least squares in surveying and GIS. 3rd ed. John Wiley & Sons, 1997.

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Wolf, Paul R. Adjustment Computation, Practical Least Squares for Surveyors. 3rd ed. Landmark Enterprises, 1987.

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9

Geological Survey (U.S.), ed. The Generic Bundle Adjustment. U.S. Geological Survey, 1989.

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Wolf. Adjustment Computations: Statistics & Least Squares in Surveying & GIS - Solutions Manual. Wiley & Sons, Incorporated, John, 1997.

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Book chapters on the topic "Least Squares Adjustment (LSA)"

1

Zsolnay, E. M., H. J. Nolthenius, E. J. Szondi, and W. L. Zijp. "New Aspects in Least Squares Adjustment Methods." In Reactor Dosimetry. Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-010-9726-0_20.

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Zsolnay, E. M., H. J. Nolthenius, E. J. Szondi, and W. L. Zijp. "New Aspects in Least Squares Adjustment Methods." In Reactor Dosimetry. Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5378-9_72.

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Schaffrin, Burkhard. "Some Generalized Equivalence Theorems for Least-Squares Adjustment." In International Association of Geodesy Symposia. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-10735-5_15.

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Somwaru, Agapi, V. Eldon Ball, and Utpal Vasavada. "Modeling Dynamic Resource Adjustment Using Iterative Least Squares." In Computational Techniques for Econometrics and Economic Analysis. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-015-8372-5_12.

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Eichhorn, Heinrich. "Generalized Least-Squares Adjustment, a Timely but Much Neglected Tool." In Qualitative and Quantitative Behaviour of Planetary Systems. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2030-2_31.

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Touati, F., S. Kahlouche, and M. Idres. "Robust and Efficient Weighted Least Squares Adjustment of Relative Gravity Data." In Gravity, Geoid and Earth Observation. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10634-7_9.

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Heiker, A., and H. Kutterer. "Integration of Observations and Models in a Consistent Least Squares Adjustment Model." In International Association of Geodesy Symposia. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10828-5_8.

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Kayıkçı, Emine Tanır, Robert Heinkelmann, Maria Karbon, et al. "Optimized Parameterization of VLBI Auxiliary Parameters in Least-Squares Adjustment: Preliminary Results." In International Association of Geodesy Symposia. Springer International Publishing, 2015. http://dx.doi.org/10.1007/1345_2015_80.

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Demetriou, Ioannis C. "Sigmoid Data Fitting by Least Squares Adjustment of Second and Third Divided Differences." In Network Models in Economics and Finance. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09683-4_6.

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De Petris, Samuele, Giovanni Cuozzo, Claudia Notarnicola, and Enrico Borgogno-Mondino. "Forest Height Estimation Using Sentinel-1 Interferometry. A Phase Unwrapping-Free Method Based on Least Squares Adjustment." In Geomatics for Green and Digital Transition. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17439-1_18.

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Conference papers on the topic "Least Squares Adjustment (LSA)"

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Luo, Minnan, Lingling Zhang, Feiping Nie, Xiaojun Chang, Buyue Qian, and Qinghua Zheng. "Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/337.

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Semi-supervised learning plays a significant role in multi-class classification, where a small number of labeled data are more deterministic while substantial unlabeled data might cause large uncertainties and potential threats. In this paper, we distinguish the label fitting of labeled and unlabeled training data through a probabilistic vector with an adaptive parameter, which always ensures the significant importance of labeled data and characterizes the contribution of unlabeled instance according to its uncertainty. Instead of using traditional least squares regression (LSR) for classifica

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Havlicek, Jakub. "GEOREFERENCING APPLYING WEIGHTING COEFFICIENTS FOR LEAST SQUARES METHOD ADJUSTMENT." In 16th International Multidisciplinary Scientific GeoConference SGEM2016. Stef92 Technology, 2016. http://dx.doi.org/10.5593/sgem2016/b23/s11.033.

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Deng, Susu, and Xiaohua Tong. "A new least squares adjustment method for map conflation." In Geoinformatics 2006: Geospatial Information Science, edited by Jianya Gong and Jingxiong Zhang. SPIE, 2006. http://dx.doi.org/10.1117/12.712989.

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COX, M. G., A. B. FORBES, J. L. FLOWERS, and P. M. HARRIS. "LEAST SQUARES ADJUSTMENT IN THE PRESENCE OF DISCREPANT DATA." In Advanced Mathematical and Computational Tools in Metrology. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812702647_0004.

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Ghosh, Suhash, Chittaranjan Sahay, Poorna Pruthvi Chandra Malempati, and Swetabh Singh. "Dependence of Measuring Instrument Eccentricity and Tilt Error on the Four Mathematical Methods of Circularity Form Errors." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11954.

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Abstract In precision machining of cylindrical parts, the measurement and evaluation of circularity is an indispensable component to quantify form tolerance. Of all the methods of measuring these form errors, the most precise is the one with accurate spindle/turntable type measuring instrument. On the instrument, the component is rotated on a highly accurate spindle which provides an imaginary circular datum. The workpiece axis is aligned with the axis of the spindle by means of a centering and tilt adjustment leveling table. Based on reference circles, this paper focuses on the four modeling

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Yuan, Ce, Jin Zhang, Zuqiang Xiong, and Yonghe Liu. "Automatic cartographic generalization for urban buildings based on least squares adjustment." In Geoinformatics 2007, edited by Manchun Li and Jiechen Wang. SPIE, 2007. http://dx.doi.org/10.1117/12.759699.

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Demetriou, I. C., and Alexander M. Korsunsky. "METHODS FOR LEAST SQUARES DATA SMOOTHING BY ADJUSTMENT OF DIVIDED DIFFERENCES." In CURRENT THEMES IN ENGINEERING SCIENCE 2007: Selected Presentations at the World Congress on Engineering—2007. AIP, 2008. http://dx.doi.org/10.1063/1.2991344.

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Todd, Charles D., and Jonathan Maxwell. "Aberrational weight adjustment by tolerance-based weighting in damped least squares optimization." In Optical Instrumentation & Systems Design, edited by Joseph J. M. Braat. SPIE, 1996. http://dx.doi.org/10.1117/12.246732.

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Masui and Morimura. "An Algorithm for the Least-Squares Adjustment Based on Classification and Generalization." In Conference on Precision Electromagnetic Measurements. IEEE, 1988. http://dx.doi.org/10.1109/cpem.1988.671256.

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Wu, Jianwei. "Airborne LiDAR Data Strip Adjustment Based on Least Squares Matching and Independent Model." In 2010 International Conference on Multimedia Technology (ICMT). IEEE, 2010. http://dx.doi.org/10.1109/icmult.2010.5631458.

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Reports on the topic "Least Squares Adjustment (LSA)"

1

Blaha, George. Nonlinear Parametric Least-Squares Adjustment. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada184039.

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Blaha, Georges. Analysis of the Nonlinear Parametric Least-Squares Adjustment via an Isomorphic Geometrical Setup with Tensor Structure. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada208219.

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Over, Thomas, Riki Saito, Andrea Veilleux, et al. Estimation of Peak Discharge Quantiles for Selected Annual Exceedance Probabilities in Northeastern Illinois. Illinois Center for Transportation, 2016. http://dx.doi.org/10.36501/0197-9191/16-014.

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This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used i

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