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| Title | Fitting geoidal undulation using quantum-behaved particle swarm optimization: A case study in Taiwan area |
| Creator | Tsai, Ming Yao;Ning, Fang-Shii 甯方璽 |
| Contributor | 地政系 |
| Key Words | 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) |
| Date | 2013-10 |
| Date Issued | 26-May-2015 18:07:47 (UTC+8) |
| Summary | 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. |
| Relation | 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 |
| Type | 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) | conference | en |