Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Stefano Sampaio Suraci"'
Publikováno v:
Revista Brasileira de Cartografia, Vol 71, Iss 2, Pp 486-500 (2019)
L1-norm adjustment corresponds to the minimization of the sum of weighted absolute residuals. Unlike Least Squares, it is a robust estimator, i.e., insensitive to outliers. In geodetic networks, the main application of L1-norm refers to the identific
Externí odkaz:
https://doaj.org/article/eaf854ac621d4403ab1f2e32400155ae
Publikováno v:
Revista Cartográfica, Iss 101 (2020)
Nesse artigo, aplicações da minimização da norma L1 (ML1) e da norma L∞ (ML∞) na estimação de redes altimétricas foram investigadas. Redes de nivelamento simuladas pela Técnica de Monte Carlo e dados reais da rede brasileira de nivelament
Externí odkaz:
https://doaj.org/article/687f2fd28de241a397d0856238bff39f
Autor:
Leonardo Castro de Oliveira, Sergio Baselga, Marcelo Tomio Matsuoka, Vinicius Francisco Rofatto, Ivandro Klein, Stefano Sampaio Suraci
Publikováno v:
Mathematical Problems in Engineering, Vol 2021 (2021)
Robust estimators are often lacking a closed-form expression for the computation of their residual covariance matrix. In fact, it is also a prerequisite to obtain critical values for normalized residuals. We present an approach based on Monte Carlo s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9d83b4474f5b92cdf2f0c81820491dd
https://doi.org/10.1155/2021/8123493
https://doi.org/10.1155/2021/8123493
Autor:
Sergio Baselga, Vinicius Francisco Rofatto, Stefano Sampaio Suraci, Leonardo Castro de Oliveira, Marcelo Tomio Matsuoka, Ivandro Klein
Publikováno v:
Survey Review. 54:70-78
The goal of this paper is to evaluate the outlier identification performance of iterative Data Snooping (IDS) and L1-norm in levelling networks by considering the redundancy of the network, number ...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0bf327019e7ba087fba1f622cfe3a5c0
https://doi.org/10.1080/00396265.2021.1878338
https://doi.org/10.1080/00396265.2021.1878338
Publikováno v:
Revista Brasileira de Cartografia, Vol 71, Iss 2, Pp 486-500 (2019)
L1-norm adjustment corresponds to the minimization of the sum of weighted absolute residuals. Unlike Least Squares, it is a robust estimator, i.e., insensitive to outliers. In geodetic networks, the main application of L1-norm refers to the identific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::edc67e9c774a246d16d5515e17f613a0
https://doi.org/10.14393/rbcv71n2-47697
https://doi.org/10.14393/rbcv71n2-47697
Autor:
Sergio Baselga, Vinicius Francisco Rofatto, Leonardo Castro de Oliveira, Marcelo Tomio Matsuoka, Ivandro Klein, Stefano Sampaio Suraci
Publikováno v:
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
Mathematical Problems in Engineering, Vol 2021 (2021)
instname
Mathematical Problems in Engineering, Vol 2021 (2021)
Robust estimation has proved to be a valuable alternative to the least squares estimator for the cases where the dataset is contaminated with outliers. Many robust estimators have been designed to be minimally affected by the outlying observations an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d8c9764e8311d589ba1229100ff1dc00
http://hdl.handle.net/10251/186638
http://hdl.handle.net/10251/186638
Publikováno v:
Boletim de Ciências Geodésicas v.25 n.spe 2019
Boletim de Ciências Geodésicas
Universidade Federal do Paraná (UFPR)
instacron:UFPR
Boletim de Ciências Geodésicas
Universidade Federal do Paraná (UFPR)
instacron:UFPR
This article has theoretically discussed some points regarding outliers caused by errors in geodetic observations (see consideration made). Comments have also been made on the usual 3σ-rule to identify outliers and its common approachs in the simula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::834be05dbe43735153b692356f0e08ed
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1982-21702019000600203
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1982-21702019000600203
Publikováno v:
Revista Brasileira de Geomática. 7:172
This work drew attention to the Chebyshev norm minimization, a method of adjustment of observations still little explored in the geodetic literature. Chebyshev norm minimization refers to the minimization of the maximum weighted absolute residual of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e72cb1ef53243e41aec95e219c865340
https://doi.org/10.3895/rbgeo.v7n4.9627
https://doi.org/10.3895/rbgeo.v7n4.9627