Prediction of Tehran-Saveh freeway Accidents with using Fuzzy Neural Network and Fuzzy regression of natural logarithm
Publish place: دومین کنفرانس بین المللی علوم و مهندسی
Publish Year: 1394
Type: Conference paper
Language: English
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ICESCON02_249
Index date: 6 September 2016
Prediction of Tehran-Saveh freeway Accidents with using Fuzzy Neural Network and Fuzzy regression of natural logarithm abstract
Since Iran is among the countries where the rate of accidents caused by inattention to safety rules and factors affecting it always has been rising and according to the capabilities of fuzzy neural network model in predicting accidents, the main purpose of this paper can considered using of this method in order to predict the accidents of Tehran-Saveh freeway, which is one of the most dangerous freeway in the country. In order to understand better the results obtained for determine the independent variables in the gathering information part, the data of average daily traffic, speed average of heavy truck in monthly time units, through traffic calculators were used. In this study with evaluation of Fuzzy neural network model to Fuzzy regression of natural logarithm of the freeway traffic modeling, the accuracy of the models that built in accidents studied and the results indicate that the neural network model has a better efficiency than the natural logarithm regression.
Prediction of Tehran-Saveh freeway Accidents with using Fuzzy Neural Network and Fuzzy regression of natural logarithm Keywords:
Prediction of Tehran-Saveh freeway Accidents with using Fuzzy Neural Network and Fuzzy regression of natural logarithm authors
Zahra Souran Khanali
M.A Student of Manegment, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
Maryam Mosleh
Department of Mathematics, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
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