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    题名: 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
    贡献者: 地政系
    关键词: 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
    上传时间: 2015-05-26 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
    数据类型: conference
    显示于类别:[地政學系] 會議論文

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