چکیده مقاله
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
کلیدواژهها
نویسندگان
احسان رمضانی خوانساری
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
شیوه ارجاع
Ramezani Khansari, Ehsan and Tabibi, Masoud and Moghadas Nejad, Fereidoon and Amini, Ehsan,1396,Speed Estimation by Training Adaptive Neuro-Fuzzy Inference Systems (ANFIS) in Highway (Case Study: Tehran-Qom Highway),The 17th International Conference on Traffic and Transportation Engineering,Tehran
ارائهشده در
مجموعه مقالات هفدهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک29 بهمن 1396 · تهران