2016
DOI: 10.12988/jite.2016.6723
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Prediction of public transportation occupation based on several crowd spots using ordinary kriging method

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Cited by 13 publications
(11 citation statements)
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“…6; which uses the shortest distance criterion achieving better predictions for short distances between nodes, was chosen (Giraldo, 2002;Wackernagel, 2003). This method has previously been used by researchers for issues such as demand prediction of public transport systems (Prasetiyowati, Imrona, Ummah, & Sibaroni, 2016 …”
Section: Global Average Accessibility Calculation For the Current Andmentioning
confidence: 99%
“…6; which uses the shortest distance criterion achieving better predictions for short distances between nodes, was chosen (Giraldo, 2002;Wackernagel, 2003). This method has previously been used by researchers for issues such as demand prediction of public transport systems (Prasetiyowati, Imrona, Ummah, & Sibaroni, 2016 …”
Section: Global Average Accessibility Calculation For the Current Andmentioning
confidence: 99%
“…The ordinary Kriging method proposes that variable value can be predicted as a linear combination of the n random variables, as presented in Expression (3) [13], where λ1 = the weights of the original values. This method has been used for different studies related to the prediction of supply models in transport networks [25]. In order to establish the relationship between the isochronous accessibility curves and the population of the city, the neighborhood division map of the city of Manizales, which has information on areas, densities and socioeconomic strata, will be used.…”
Section: Calculation Of Global Average Accessibilitymentioning
confidence: 99%
“…Z(x+d) is another sample value separated by a distance h, n is the number of couples that are separated by that distance h. It is emphasized that the model uses the shortest distance criterion to obtain better predictions for short distances between the nodes, meaning that the similarity or spatial correlation between the observations is greater (Giraldo, 2002;Wackernagel, 2003). This method has been used previously by researchers for issues such as demand prediction for public transport systems (Prasetiyowati, Imrona, Ummah, & Sibaroni, 2016). The accessibility analysis leads to the final step, which is to identify the location of AD to fulfill the requirements of time in an identified great zone.…”
Section: Calculation Of Global Average Accessibility Stagementioning
confidence: 99%