چکیده مقاله
Accurate prediction of short term traffic flow plays a fundamental role in theIntelligent Transportation Systems ITS and Advanced Traffic ManagementSystems ATMS In this paper, a combination of multi layer Back PropagationNeural Networks BPNN and Genetic Algorithm GA is used to forecast thevolume of the traffic during peak hours The real data used for modeling isobtained from Karaj Qazvin freeway in the spring of 2013 Given the proposedmethod BPNN GA , Neural Network designed and be taught using trainingdata In part train of neural network, which is typically are used internal functionsof the Neural Network's toolbox, Genetic Algorithms have been used in thisresearch The purpose of train the network is determine the weight of its internalstructure The Genetic Algorithm optimize network weights and improve thenetwork in learning the patterns which exist in traffic data Thus the NeuralNetwork get the better answers in forecasting Then the trained network isvalidated and is used to forecast the volume of traffic during peak hours in thefollowing week To assess these forecasts, the conventional Back PropagationNeural Network BPNN has also been developed and its results are comparedwith the proposed method The results show that the proposed method BPNNGA forecasts the volume of peak hour traffic with greater stability and moreaccurately than conventional Neural Networks
کلیدواژهها
نویسندگان
Shahin Shahani
Assistant Professor, Department of Civil Engineering, Payam Noor University, Tehran Shomal Center, Tehran, Iran
Mahdi Motamedi sedeh
Master Student, Department of Civil Engineering, Payam Noor University, Tehran Shomal Center, Tehran, Iran
Alireza Daneshmandi
Master of Science, Department of Civil Engineering, Payam Noor University, Tehran Shomal Center, Tehran, Iran
شیوه ارجاع
Shahani, Shahin and Motamedi sedeh, Mahdi and Daneshmandi, Alireza,1394,Peak Hour Traffic Volume Prediction using a Hybrid Genetic Neural Method,The 14th International Conference on Traffic and Transportation Engineering,Tehran
ارائهشده در
مجموعه مقالات چهاردهمین کنفرانس بین المللی مهندسی حمل و نقل و ترافیک5 اسفند 1393 · تهران