TRAVEL TIME PREDICTION IN SUBURBAN ROADS USING SPATIAL DATA MINING TECHNIQUES (CASE STUDY: GHAEMSHAHR-BABOL AND SARI-GHAEMSHAR ROADS)

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MOSLEMI NAJJARKOLAEI FARDIN; EFFATI MEYSAM; NASERI FARZIN; RAJABI MOHAMMAD ALI

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Journal: JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT) Year:2015 | Volume:4 | Issue:3 Page(s): 16-28

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Title

TRAVEL TIME PREDICTION IN SUBURBAN ROADS USING SPATIAL DATA MINING TECHNIQUES (CASE STUDY: GHAEMSHAHR-BABOL AND SARI-GHAEMSHAR ROADS)

Author(s)

MOSLEMI NAJJARKOLAEI FARDIN | EFFATI MEYSAM | NASERI FARZIN | RAJABI MOHAMMAD ALI | Issue Writer Certificate

Keywords

TRAVEL TIMEQ2

GEOSPATIAL INFORMATION SYSTEMQ2

SPATIAL DATA MININGQ2

FORWARD ARTIFICIAL NEURAL NETWORKQ2

Abstract

TRAVEL TIME prediction has been concerned by specialists in different fields in regard with transportation systems programming. GEOSPATIAL INFORMATION SYSTEMs and data mining analyzes by using new methods have obtained several capabilities to extract hidden patterns among the data to predict TRAVEL TIME. These methods can be considered as good alternatives for conventional methods. In this study K-means clustering method as a SPATIAL DATA MINING technique and also a forward neural network method have been used to predict TRAVEL TIME. In this regard eight variables were extracted from vehicles GPS and climatic and cars accidents data during a three years period. These variables were used to predict TRAVEL TIME in Babol -Ghaemshahr and Ghaemshahr- Sari roads in Mazandaran province. In order to evaluate the proposed method the outputs of clustering and neural network methods were compared with real data in the study corridor. The study showed the artificial neural network method can lead to more satisfactory results in comparison with the clustering method by considering a root mean square error equal to 0.0015 and a mean square errorequal to 0.65 showed.

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APA: Copy

MOSLEMI NAJJARKOLAEI, FARDIN, EFFATI, MEYSAM, NASERI, FARZIN, & RAJABI, MOHAMMAD ALI. (2015). TRAVEL TIME PREDICTION IN SUBURBAN ROADS USING SPATIAL DATA MINING TECHNIQUES (CASE STUDY: GHAEMSHAHR-BABOL AND SARI-GHAEMSHAR ROADS). JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT), 4(3), 16-28. SID. https://sid.ir/paper/245818/en

Vancouver: Copy

MOSLEMI NAJJARKOLAEI FARDIN, EFFATI MEYSAM, NASERI FARZIN, RAJABI MOHAMMAD ALI. TRAVEL TIME PREDICTION IN SUBURBAN ROADS USING SPATIAL DATA MINING TECHNIQUES (CASE STUDY: GHAEMSHAHR-BABOL AND SARI-GHAEMSHAR ROADS). JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT)[Internet]. 2015;4(3):16-28. Available from: https://sid.ir/paper/245818/en

IEEE: Copy

FARDIN MOSLEMI NAJJARKOLAEI, MEYSAM EFFATI, FARZIN NASERI, and MOHAMMAD ALI RAJABI, “TRAVEL TIME PREDICTION IN SUBURBAN ROADS USING SPATIAL DATA MINING TECHNIQUES (CASE STUDY: GHAEMSHAHR-BABOL AND SARI-GHAEMSHAR ROADS),” JOURNAL OF SOFT COMPUTING AND INFORMATION TECHNOLOGY (JSCIT), vol. 4, no. 3, pp. 16–28, 2015, [Online]. Available: https://sid.ir/paper/245818/en

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