Speed Estimation by Training Adaptive Neuro-Fuzzy Inference Systems (ANFIS) in Highway (Case Study: Tehran-Qom Highway)
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
TTC17_013
تاریخ نمایه سازی: 26 مرداد 1397
Abstract:
Estimation of the traffic flow s speed, in different week days and even different parts of a day, considered as one of the most important parameters for both traffic planners and road customers. The inaccuracy of traffic s data as well as the difference of driver s behavior, lead researchers to use the fuzzy for modeling the traffic events. In this study a mix of the fuzzy logic model and artificial neural network (adaptive neuro-fuzzy inference systems (ANFIS)) is used to model the speed of a traffic flow by using other traffic s data. At first, the fussy logic s roles are presented by an export person in traffic matter, and then these roles were rechecked and modified. The results show that the presented model can estimate the flow s speed with 10 Km/hour as statistical error
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Authors
Ehsan Ramezani Khansari
PhD student, Amirkabir University of Technology (Tehran Polytechnic),
Masoud Tabibi
Assistant Professor of Transportation Engineering, Civil Engineering Department, Engineering Faculty, Amirkabir University of Technology (Tehran Polytechnic)
Fereidoon Moghadas Nejad
Associate Professor of Transportation Engineering, Civil EngineeringDepartment, Engineering Faculty, Amirkabir University of Technology (Tehran Polytechnic)
Ehsan Amini
MSc of Transportation Engineering, Civil Engineering Department, Engineering Faculty, Amirkabir University of Technology (Tehran Polytechnic)