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Semi-Ensemble Learning using Neural Network for Classifying Traffic Condition

Authors :
Surya Michrandi Nasution
Emir Husni
Kuspriyanto
Rahadian Yusuf
Source :
2020 International Conference on Information Technology Systems and Innovation (ICITSI).
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

The growth of technology aims to help human’s activity. One of human’s activity which could use technology is in the transportation area by implementing machine learning. This paper discusses the semi-ensemble method for classifying traffic condition, which could be used to classify the traffic condition for shorten travel time in the road. Semi-ensemble that applied is using voting system which consists of several neural networks. The proposed method in this paper gives better performance result than single neural network Even though the performance result is not increased significantly, enhancement in semi-ensemble with voting system which comes from best-5 performance neural networks also give better result than voting system using 10 neural networks. The performance increased from 82.58% to 82.81% for its accuracy and the rests of performance value increased from 65.09% to 65.62%.

Details

Database :
OpenAIRE
Journal :
2020 International Conference on Information Technology Systems and Innovation (ICITSI)
Accession number :
edsair.doi...........90301de2f1c516a87c4ec1069db97db1
Full Text :
https://doi.org/10.1109/icitsi50517.2020.9264956