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Prediction of Tehran-Saveh freeway Accidents with using Fuzzy Neural Network and Fuzzy regression of natural logarithm

عنوان مقاله: Prediction of Tehran-Saveh freeway Accidents with using Fuzzy Neural Network and Fuzzy regression of natural logarithm
شناسه ملی مقاله: ICESCON02_249
منتشر شده در دومین کنفرانس بین المللی علوم و مهندسی در سال 1394
مشخصات نویسندگان مقاله:

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

خلاصه مقاله:
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.

کلمات کلیدی:
Freeway, Fuzzy neural networks, Fuzzy regression of the natural logarithm

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/490656/