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9篇 您的检索式：作者名="Mohaymany"

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		题名	作者	年代	出处	被引量
	1	GIS-based method for detecting high-crash-risk road segments using network kernel density estimation显示文摘Identifying high-crash-risk road segments provides safety specialists with an insight to better understanding of crash patterns and enhancing road safety management.The common hotspot identification methods are not robust enough to visualize the underlying shape of crash patterns since they neglect the spatial properties of crash data.Spatial traffic accidents have the tendency to be dependent,a phenomenon known as spatial autocorrelation.Values over distance are more or less similar than expected for randomly associated observations.Modeling the spatial variations can properly be explained in terms of first-and second-order properties.The first-order properties,describe the way of varying the expected value of point pattern in space which can be due to changes in the substantial properties of the local environment,while second-order effects describe the interactive effects of events explaining on how the events are interacted.Considering the discrete nature of crash data and the limited access to exact locations where crashes occur,it is likely that a continuous surface drawn from discrete points will better reflect crash density,present a more realistic picture of crash distribution.Network kernel density estimation(NKDE)is a nonparametric approach for events distributed over one-dimensional space which facilitates estimating the density at any location in the study region not just at the location where the event occurs.NKDE for road safety applications enables the extraction and visualization of crash density along roadways The application of suggested method was illustrated for Arak-Khomein rural road in Markazi province,Iran and the stability of hazardous segments by examining the resulted network estimated density during the three years of study(2006–2008)was investigated.The result of this paper helps the traffic engineers and safety specialists to determine the segments which demand more safety attentions from both transportation authorities and drivers and request assigning the resources such as budget and time.	Afshin Shariat MOHAYMANY Matin SHAHRI Babak MIRBAGHERI	2013	Geo-Spatial Information Science2013，16，2：	5
	2	Detecting the spatial-temporal autocorrelation among crash frequencies in urban areas显示文摘	Matkan A A Mohaymany A S Shahri M	2013	Can J Civ Eng2013，40，：	1
	3	Economic conditions for minibus usage in a multimodal feeder network 显示文摘	Gholami A Mohaymany A S	2011	Transportation Planning & Technology2011，34，8：	1
	4	Multimodal feeder network design problem: ant colony optimiza- tion approach显示文摘	MOHAYMANY A S GHOLAMI A	2010	Journal of Transportation Engi- neering2010，，4：	1
	5	Detecting the spatial-temporal autocorrelation among crash frequencies in urban areas显示文摘	Matkan A A Mohaymany A S Shahri M		0，，：	1
	6	Multi modal feeder network design problem:Ant colony optimization approach显示文摘	Mohaymany A S Gholami A	2010	Journal of Transportation Engineering2010，136，4：	1
	7	Multimodal feeder network design problem: Ant colony optimization approach显示文摘	Mohaymany A S Gholami A	2010	Journal of Transportation Engineering2010，136，4：	1
	8	Multimodal feeder network design problem: ant colony optimization approach显示文摘	Shariat Mohaymany A Gholami A	2010	Journal of Transportation Engineering2010，136，4：	1
	9	Designing a multimodal feeder network by covering stops with different modes显示文摘	Tahoorinia M M Mohaymany A S Gholami A	2014	Canadian Journal of Civil Engineering2014，41，1：	1

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