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題名 Fitting geoidal undulation using quantum-behaved particle swarm optimization: A case study in Taiwan area
作者 Tsai, Ming Yao;Ning, Fang-Shii
甯方璽
貢獻者 地政系
關鍵詞 Remote sensing; Geoidal undulation; Global conver-gence; Optimization problems; Original particle swarm optimization; Orthometric heights; QPSO; Quantum-behaved particle swarm optimization; Surface equation; Particle swarm optimization (PSO)
日期 2013-10
上傳時間 26-May-2015 18:07:47 (UTC+8)
摘要 This research proposes a version of the local geoidal undulation model that is generated from GNSS geodetic height, orthometric height and proper curve fitting surface model. We adopted here the algorithm of the quantum-behaved particle swarm optimization (QPSO) which has been improved from the original PSO. The original particle swarm optimization (PSO) is used to solve the optimization problem, and can solve the surface equation efficiently. The QPSO is a global convergence guaranteed and requires less parameters compared with the original PSO. The QPSO can search the best 2nd curve surface model more efficiently to fit the geoidal undulation of Taiwan area as well as to find the most appropriate partition fitting range.
關聯 34th Asian Conference on Remote Sensing 2013, ACRS 2013, 5, 2013, 4505-4512, 34th Asian Conference on Remote Sensing 2013, ACRS 2013; Bali; Indonesia; 20 October 2013 到 24 October 2013; 代碼 105869
資料類型 conference
dc.contributor 地政系
dc.creator (作者) Tsai, Ming Yao;Ning, Fang-Shii
dc.creator (作者) 甯方璽zh_TW
dc.date (日期) 2013-10
dc.date.accessioned 26-May-2015 18:07:47 (UTC+8)-
dc.date.available 26-May-2015 18:07:47 (UTC+8)-
dc.date.issued (上傳時間) 26-May-2015 18:07:47 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/75313-
dc.description.abstract (摘要) This research proposes a version of the local geoidal undulation model that is generated from GNSS geodetic height, orthometric height and proper curve fitting surface model. We adopted here the algorithm of the quantum-behaved particle swarm optimization (QPSO) which has been improved from the original PSO. The original particle swarm optimization (PSO) is used to solve the optimization problem, and can solve the surface equation efficiently. The QPSO is a global convergence guaranteed and requires less parameters compared with the original PSO. The QPSO can search the best 2nd curve surface model more efficiently to fit the geoidal undulation of Taiwan area as well as to find the most appropriate partition fitting range.
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) 34th Asian Conference on Remote Sensing 2013, ACRS 2013, 5, 2013, 4505-4512, 34th Asian Conference on Remote Sensing 2013, ACRS 2013; Bali; Indonesia; 20 October 2013 到 24 October 2013; 代碼 105869
dc.subject (關鍵詞) Remote sensing; Geoidal undulation; Global conver-gence; Optimization problems; Original particle swarm optimization; Orthometric heights; QPSO; Quantum-behaved particle swarm optimization; Surface equation; Particle swarm optimization (PSO)
dc.title (題名) Fitting geoidal undulation using quantum-behaved particle swarm optimization: A case study in Taiwan area
dc.type (資料類型) conferenceen