Categorizing bicycling environments using GPS-based public bicycle speed data
• A methodology for categorizing bicycling environments is proposed. • GPS based public bicycle speed data is used. • A support vector machine is adopted for the proposed categorization algorithm. • Technical feasibility of the proposed algorithm is demonstrated.
Autor*in: |
Joo, Shinhye [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Schlagwörter: |
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Umfang: |
12 |
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Übergeordnetes Werk: |
Enthalten in: Dithiocarbamate-calix[4]arene functionalized gold nanoparticles as a selective and sensitive colorimetric probe for assay of metsulfuron-methyl herbicide - Rohit, Jigneshkumar V. ELSEVIER, 2016, an international journal : a journal affiliated with IFAC, the International Federation of Automatic Control, Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:56 ; year:2015 ; pages:239-250 ; extent:12 |
Links: |
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DOI / URN: |
10.1016/j.trc.2015.04.012 |
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Katalog-ID: |
ELV023839252 |
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10.1016/j.trc.2015.04.012 doi GBVA2015016000016.pica (DE-627)ELV023839252 (ELSEVIER)S0968-090X(15)00153-9 DE-627 ger DE-627 rakwb eng 380 380 DE-600 530 620 VZ 50.22 bkl 35.07 bkl Joo, Shinhye verfasserin aut Categorizing bicycling environments using GPS-based public bicycle speed data 2015 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • A methodology for categorizing bicycling environments is proposed. • GPS based public bicycle speed data is used. • A support vector machine is adopted for the proposed categorization algorithm. • Technical feasibility of the proposed algorithm is demonstrated. Bicycling environments Elsevier Support vector machine Elsevier Bicycle speed data Elsevier Public bicycle Elsevier Bicycle traffic monitoring Elsevier Oh, Cheol oth Jeong, Eunbi oth Lee, Gunwoo oth Enthalten in Elsevier Science Rohit, Jigneshkumar V. ELSEVIER Dithiocarbamate-calix[4]arene functionalized gold nanoparticles as a selective and sensitive colorimetric probe for assay of metsulfuron-methyl herbicide 2016 an international journal : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV001932888 volume:56 year:2015 pages:239-250 extent:12 https://doi.org/10.1016/j.trc.2015.04.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 50.22 Sensorik VZ 35.07 Chemisches Labor chemische Methoden VZ AR 56 2015 239-250 12 045F 380 |
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10.1016/j.trc.2015.04.012 doi GBVA2015016000016.pica (DE-627)ELV023839252 (ELSEVIER)S0968-090X(15)00153-9 DE-627 ger DE-627 rakwb eng 380 380 DE-600 530 620 VZ 50.22 bkl 35.07 bkl Joo, Shinhye verfasserin aut Categorizing bicycling environments using GPS-based public bicycle speed data 2015 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • A methodology for categorizing bicycling environments is proposed. • GPS based public bicycle speed data is used. • A support vector machine is adopted for the proposed categorization algorithm. • Technical feasibility of the proposed algorithm is demonstrated. Bicycling environments Elsevier Support vector machine Elsevier Bicycle speed data Elsevier Public bicycle Elsevier Bicycle traffic monitoring Elsevier Oh, Cheol oth Jeong, Eunbi oth Lee, Gunwoo oth Enthalten in Elsevier Science Rohit, Jigneshkumar V. ELSEVIER Dithiocarbamate-calix[4]arene functionalized gold nanoparticles as a selective and sensitive colorimetric probe for assay of metsulfuron-methyl herbicide 2016 an international journal : a journal affiliated with IFAC, the International Federation of Automatic Control Amsterdam [u.a.] (DE-627)ELV001932888 volume:56 year:2015 pages:239-250 extent:12 https://doi.org/10.1016/j.trc.2015.04.012 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 50.22 Sensorik VZ 35.07 Chemisches Labor chemische Methoden VZ AR 56 2015 239-250 12 045F 380 |
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• A methodology for categorizing bicycling environments is proposed. • GPS based public bicycle speed data is used. • A support vector machine is adopted for the proposed categorization algorithm. • Technical feasibility of the proposed algorithm is demonstrated. |
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• A methodology for categorizing bicycling environments is proposed. • GPS based public bicycle speed data is used. • A support vector machine is adopted for the proposed categorization algorithm. • Technical feasibility of the proposed algorithm is demonstrated. |
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• A methodology for categorizing bicycling environments is proposed. • GPS based public bicycle speed data is used. • A support vector machine is adopted for the proposed categorization algorithm. • Technical feasibility of the proposed algorithm is demonstrated. |
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