Application of genetic programming clustering in defining LOS criteria of urban street in Indian context
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Patnaik:2016:TBS,
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author = "Ashish Kumar Patnaik and Prasanta Kumar Bhuyan",
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title = "Application of genetic programming clustering in
defining {LOS} criteria of urban street in Indian
context",
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journal = "Travel Behaviour and Society",
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volume = "3",
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pages = "38--50",
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year = "2016",
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ISSN = "2214-367X",
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DOI = "doi:10.1016/j.tbs.2015.08.003",
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URL = "http://www.sciencedirect.com/science/article/pii/S2214367X15000277",
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abstract = "India is a highly populated country having second
largest road network in the world. Owing to boastfully
population, the congestion is growing rapidly on the
urban road networks. The level of service (LOS) is not
substantially defined for heterogeneous traffic flow
with different operational characteristics. Defining
LOS is essentially a classification problem. The
application of cluster analysis is the worthiest
proficiency to solve such problem for which genetic
programming (GP) clustering, an evolutionary algorithm
is used in this study. Five cluster validation
parameters are used to examine the optimal number of
clusters. The cluster validation parameters are used to
obtain the number of categories of urban street
classes. After acquiring optimal number of clusters, GP
clustering is implemented to the free flow speed (FFS)
data to get ranges of different urban street classes.
Again, GP clustering is enforced on average travel
speeds of street segments to specify the ranges of
different LOS categories. Speed data used in this study
are collected using Trimble GeoXT GPS receivers fitted
on mid-sized vehicles for five major urban corridors
comprising of 100 street segments of Greater Mumbai
region. Result shows that FFS of urban street classes
and average travel speed of LOS categories are lower
than that mentioned in Highway Capacity Manual (HCM
2000) on account of physical and surrounding
environmental characteristics. Also, average travel
speed of LOS categories expressed in terms percentage
of FFS of urban street classes found to be different
from that mentioned in HCM 2010.",
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keywords = "genetic algorithms, genetic programming, Urban
streets, Level of service (LOS), Clustering analysis,
Free flow speed (FFS), Highway Capacity Manual (HCM)",
- }
Genetic Programming entries for
Ashish Kumar Patnaik
Prasanta Kumar Bhuyan
Citations