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29 November 2016

Attention to Authors

The Volume 1, Number 2, November 2016 issue of IJARCE has been published and hardcopies have been sent to authors. Notice that, arrival process of the hardcopies, to your addresses, will takes between 12 to 30 days depending on your country of origin.

 

10 October 2016

Attention to Authors

The Volume 1, Number 1, September 2016 issue of IJARCE has been published and hardcopies have been sent to authors. Notice that, arrival process of the hardcopies, to your addresses, will takes between 5 to 30 days depending on your country of origin.

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A New Approach to Predict the Severity of Road Accidents with Hybrid MLP ANN and Differential Evolution Algorithm

Artical 6 ; volume1 ; number1 ; Page: 47-52 ; PDF Download

Authors

Zahra Asheghi Dizaji, Farhad Soleimanian Gharehchopogh

Department of Computer Engineering, Urmia Branch, Islamic Azad University, Urmia, IRAN.

Abstract

In most cases, classification has been proposed as an effective method in decision-making. Although countless methods of classification have been stated by the researchers, none of these methods has the same performance and sufficient accuracy for various issues. Accordingly, a hybrid approach has been proposed for classification in this paper. Also, considering the fact that one of the most common accidents all around the world is road accidents and traffic accidents, which endangers the lives of many people annually, therefore, determining the characteristics affecting the type of the accident is very important. Therefore, the information collected by the transportation and terminal organization in Western Azerbaijan province (Iran) were used as data collection in this paper and the aim of it is the accident classification based on the type of accident (damage, injury, death). For this purpose, a new method has been proposed for classification based on the use of two algorithms of Differential Evolution (DE) algorithm and MLP ANN. In the proposed method, DE algorithm is used for extraction of affecting features of classification, and MLP ANN algorithm is used to classify information based on characteristics determined by DE algorithm. The results of the proposed method have been evaluated with evaluation criteria Recall, Precision, F-Measure, and Kappa which the results show that the proposed method is optimal.

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