USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Boletim de Ciências Geodésicas |
Texto Completo: | https://revistas.ufpr.br/bcg/article/view/52786 |
Resumo: | There exist a number of methods for approximating the local geoid surface and studies carried out to determine a local geoid. In this study, performance of geoid by PSO method in modeling local geoid was presented and analyzed. The ellipsoidal heights (h), derived from GPS observations, and known orthometric heights from first-order bench marks were first used to create local geometric geoid model, then the PSO method was used to convert ellipsoidal heights into orthometric heights (H). The resulting values were used to compare between the spirit leveling and GPS methods. The adopted PSO method can improve the fitting of local geometric geoid by quadratic surface fitting method, which agrees with the known orthometric heights within ±1.02cmthe Cartography produced: General Map, Partial Maps, Profile, Cross Sections and others. |
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Boletim de Ciências Geodésicas |
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USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODELGeociências; GeodésiaParticle swarm optimization (PSO); Quadratic surface fitting; Ellipsoidal height; Orthometric heightThere exist a number of methods for approximating the local geoid surface and studies carried out to determine a local geoid. In this study, performance of geoid by PSO method in modeling local geoid was presented and analyzed. The ellipsoidal heights (h), derived from GPS observations, and known orthometric heights from first-order bench marks were first used to create local geometric geoid model, then the PSO method was used to convert ellipsoidal heights into orthometric heights (H). The resulting values were used to compare between the spirit leveling and GPS methods. The adopted PSO method can improve the fitting of local geometric geoid by quadratic surface fitting method, which agrees with the known orthometric heights within ±1.02cmthe Cartography produced: General Map, Partial Maps, Profile, Cross Sections and others.Boletim de Ciências GeodésicasBulletin of Geodetic SciencesKao, Szu-PyngNing, Fang-ShiiChen, Chao-NanChen, Chia-Ling2017-07-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufpr.br/bcg/article/view/52786Boletim de Ciências Geodésicas; Vol 23, No 2 (2017)Bulletin of Geodetic Sciences; Vol 23, No 2 (2017)1982-21701413-4853reponame:Boletim de Ciências Geodésicasinstname:Universidade Federal do Paraná (UFPR)instacron:UFPRporhttps://revistas.ufpr.br/bcg/article/view/52786/32445Copyright (c) 2017 Szu-Pyng Kao, Fang-Shii Ning, Chao-Nan Chen, Chia-Ling Chenhttp://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccess2017-07-31T16:00:12Zoai:revistas.ufpr.br:article/52786Revistahttps://revistas.ufpr.br/bcgPUBhttps://revistas.ufpr.br/bcg/oaiqdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br1982-21701413-4853opendoar:2017-07-31T16:00:12Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)false |
dc.title.none.fl_str_mv |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL |
title |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL |
spellingShingle |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL Kao, Szu-Pyng Geociências; Geodésia Particle swarm optimization (PSO); Quadratic surface fitting; Ellipsoidal height; Orthometric height |
title_short |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL |
title_full |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL |
title_fullStr |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL |
title_full_unstemmed |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL |
title_sort |
USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODEL |
author |
Kao, Szu-Pyng |
author_facet |
Kao, Szu-Pyng Ning, Fang-Shii Chen, Chao-Nan Chen, Chia-Ling |
author_role |
author |
author2 |
Ning, Fang-Shii Chen, Chao-Nan Chen, Chia-Ling |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Kao, Szu-Pyng Ning, Fang-Shii Chen, Chao-Nan Chen, Chia-Ling |
dc.subject.por.fl_str_mv |
Geociências; Geodésia Particle swarm optimization (PSO); Quadratic surface fitting; Ellipsoidal height; Orthometric height |
topic |
Geociências; Geodésia Particle swarm optimization (PSO); Quadratic surface fitting; Ellipsoidal height; Orthometric height |
description |
There exist a number of methods for approximating the local geoid surface and studies carried out to determine a local geoid. In this study, performance of geoid by PSO method in modeling local geoid was presented and analyzed. The ellipsoidal heights (h), derived from GPS observations, and known orthometric heights from first-order bench marks were first used to create local geometric geoid model, then the PSO method was used to convert ellipsoidal heights into orthometric heights (H). The resulting values were used to compare between the spirit leveling and GPS methods. The adopted PSO method can improve the fitting of local geometric geoid by quadratic surface fitting method, which agrees with the known orthometric heights within ±1.02cmthe Cartography produced: General Map, Partial Maps, Profile, Cross Sections and others. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-07-31 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufpr.br/bcg/article/view/52786 |
url |
https://revistas.ufpr.br/bcg/article/view/52786 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://revistas.ufpr.br/bcg/article/view/52786/32445 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2017 Szu-Pyng Kao, Fang-Shii Ning, Chao-Nan Chen, Chia-Ling Chen http://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2017 Szu-Pyng Kao, Fang-Shii Ning, Chao-Nan Chen, Chia-Ling Chen http://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
dc.source.none.fl_str_mv |
Boletim de Ciências Geodésicas; Vol 23, No 2 (2017) Bulletin of Geodetic Sciences; Vol 23, No 2 (2017) 1982-2170 1413-4853 reponame:Boletim de Ciências Geodésicas instname:Universidade Federal do Paraná (UFPR) instacron:UFPR |
instname_str |
Universidade Federal do Paraná (UFPR) |
instacron_str |
UFPR |
institution |
UFPR |
reponame_str |
Boletim de Ciências Geodésicas |
collection |
Boletim de Ciências Geodésicas |
repository.name.fl_str_mv |
Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR) |
repository.mail.fl_str_mv |
qdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br |
_version_ |
1799771719415627776 |