Soft Computing for Adaptive Traffic Control

Veljanovska, Kostandina (2022) Soft Computing for Adaptive Traffic Control. In: 12th International conference on Applied Internet and Information Technologies (AIIT2022), October 14th, Zrenjanin, Serbia.

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Abstract

The aim of this paper is to emphasize the significance of soft computing techniques, to introduce soft computing technique as good functional approximator and to analyze performance of two learning algorithms:one hard computing and one machine learning algorithm. The problem of controlling freeway ramp entrance by reinforcement learning was selected. The aim of this research is to help the local government in reducing air pollution by making influence in the number of vehicles entering the freeway. This way there are possibilities for environmental pollution reduction, fuel consumption reduction and for improving air quality. The results are promising for various dimensions of the cities and intercity freeways since the machine learning algorithms are used and the proposed model is capable of learning from presented data even if they are not precise.

Item Type: Conference or Workshop Item (Speech)
Subjects: Scientific Fields (Frascati) > Natural sciences > Computer and information sciences
Divisions: Faculty of Information and Communication Technologies
Depositing User: Prof. d-r. Andrijana Bocevska
Date Deposited: 02 Dec 2022 11:02
Last Modified: 02 Dec 2022 11:02
URI: http://eprints.uklo.edu.mk/id/eprint/7469

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