Paper Title :An Application of Adaptive Neuro-Fuzzy Inference System in Vehicle Delay Modeling
Author :Ersin Korkmaz, Ali Payidar Akgungor
Article Citation :Ersin Korkmaz ,Ali Payidar Akgungor ,
(2016 ) " An Application of Adaptive Neuro-Fuzzy Inference System in Vehicle Delay Modeling " ,
International Journal of Advances in Mechanical and Civil Engineering (IJAMCE) ,
pp. 59-62,
Volume-3,Issue-4
Abstract : An Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is widely used to solve engineering problems.
In this study, a model for estimating the average delay was developed by using ANFIS according to effective parameters,
and the performance of the model was statistically evaluated. In this model, a hybrid method which is ANFIS was performed
for training and test. The artificial network part of method used three input parameters representing cycle time of
signalization (C), the green time (g) and the degree of saturation (x). The results of neuro-fuzzy network part of method were
compared with the analytical models named HCM and Australian delay models. The performance of ANFIS was the better
than other models and showed close agreement with simulated values.
Keywords— VehicleDelay, Neuro-Fuzzy, Signalized Intersection.
Type : Research paper
Published : Volume-3,Issue-4
DOIONLINE NO - IJAMCE-IRAJ-DOIONLINE-5393
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Copyright: © Institute of Research and Journals
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Published on 2016-09-16 |
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