Research on an Improved Adaptive Fitting Algorithm of Trajectory Information

In order to facilitate the storage, visualization and data mining of large-scale trajectory information, an improved adaptive fitting algorithm of trajectory information is proposed, which can automatically select the optimal fitting interval and generate the key points and coefficients of the fitte...

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Veröffentlicht in:Journal of physics. Conference series Jg. 1169; H. 1; S. 12020 - 12025
Hauptverfasser: Futai, LIANG, Hongquan, LI, Mao, ZHENG, Lingzhi, LI
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bristol IOP Publishing 01.02.2019
Schlagworte:
Adaptive algorithms
Algorithms
Curve fitting
Data compression
Data mining
Feature extraction
Least squares method
Optimization
Quadratic programming
ISSN:1742-6588, 1742-6596
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Abstract In order to facilitate the storage, visualization and data mining of large-scale trajectory information, an improved adaptive fitting algorithm of trajectory information is proposed, which can automatically select the optimal fitting interval and generate the key points and coefficients of the fitted interval. The algorithm consists of two steps: Firstly, the adaptive fitting method is used to fit the trajectory points to obtain the most suitable fitted trajectory interval, and the fitting method adopts the least squares method. Secondly, the constrained quadratic programming method is used to optimize the obtained trajectory interval coefficients to make the fitting curve smooth and continuous. The experimental simulation proves that the algorithm has obvious effects on data compression and feature extraction of trajectory information.
AbstractList In order to facilitate the storage, visualization and data mining of large-scale trajectory information, an improved adaptive fitting algorithm of trajectory information is proposed, which can automatically select the optimal fitting interval and generate the key points and coefficients of the fitted interval. The algorithm consists of two steps: Firstly, the adaptive fitting method is used to fit the trajectory points to obtain the most suitable fitted trajectory interval, and the fitting method adopts the least squares method. Secondly, the constrained quadratic programming method is used to optimize the obtained trajectory interval coefficients to make the fitting curve smooth and continuous. The experimental simulation proves that the algorithm has obvious effects on data compression and feature extraction of trajectory information.
Author Mao, ZHENG
Futai, LIANG
Lingzhi, LI
Hongquan, LI
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  fullname: Lingzhi, LI
  organization: Air Force Early Warning Academy , China
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Cites_doi 10.1186/2193-1801-4-S2-P3
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Copyright Published under licence by IOP Publishing Ltd
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SubjectTerms Adaptive algorithms
Algorithms
Curve fitting
Data compression
Data mining
Feature extraction
Least squares method
Optimization
Quadratic programming
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