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http://dx.doi.org/10.5351/KJAS.2007.20.3.459

A Study on the Prediction of Traffic Counts Based on Shortest Travel Path  

Heo, Tae-Young (Division of Nano Data System, Korea Maritime University)
Park, Man-Sik (Department Preventive Medicine, Korea University)
Eom, Jin-Ki (Korea Railroad Research Institute)
Oh, Ju-Sam (Korea Institute of Construction Technology)
Publication Information
The Korean Journal of Applied Statistics / v.20, no.3, 2007 , pp. 459-473 More about this Journal
Abstract
In this paper, we suggest a spatial regression model to predict AADT. Although Euclidian distances between one monitoring site and its neighboring sites were usually used in the many analysis, we consider the shortest travel path between monitoring sites to predict AADT for unmonitoring site using spatial regression model. We used universal Kriging method for prediction and found that the overall predictive capability of the spatial regression model based on shortest travel path is better than that of the model based on multiple regression by cross validation.
Keywords
Cross-validation; semivariogram; annual average daily franc; Kriging;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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