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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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

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