A study on GPS GDOP approximation using support-vector machines

IEEE Transactions on Instrumentation and Measurement

Volumn 60, Issue 1, 2011, Pages 137-145

  Wu, Chih Hung ^a   Su, Wei Han ^b   Ho, Ya Wei ^a  

^a NATIONAL UNIVERSITY OF KAOHSIUNG   (Taiwan)

^b POLSTAR Technologies Inc   (Taiwan)

Author keywords

Computational intelligence; genetic programming (GP); geometric dilution of precision (GDOP); Global Positioning System (GPS); Kernel based method; machine learning; neural networks; regression; support vector machine (SVM)

Indexed keywords

COMPUTATIONAL INTELLIGENCE; GEOMETRIC DILUTION OF PRECISION; GLOBAL POSITIONING; KERNEL BASED METHODS; MACHINE-LEARNING; REGRESSION; SUPPORT VECTOR MACHINE (SVM);

GEARS; GENETIC PROGRAMMING; GEOMETRY; LINEAR TRANSFORMATIONS; NAVIGATION SYSTEMS; NEURAL NETWORKS; POSITION CONTROL; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; VECTORS; VIRTUAL REALITY;

GLOBAL POSITIONING SYSTEM;

EID: 78650068598     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2010.2049228     Document Type: Conference Paper

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