Fuzzy Graph Cellular Automaton and Its Applications in Parking Recommendations

B. Praba and R. Saranya ()
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B. Praba: Sri Sivasubramaniya Nadar College of Engineering Chennai, Tamil Nadu, India
R. Saranya: Sri Sivasubramaniya Nadar College of Engineering Chennai, Tamil Nadu, India

New Mathematics and Natural Computation (NMNC), 2022, vol. 18, issue 01, 147-162

Abstract: The scope of this paper is to make the best use of cellular automaton. It is important that they can simulate not just a discrete model but also used to solve practical problems. To stimulate the research in this field, we define Fuzzy Graph Cellular Automaton (FGCA) and classify the fuzzy rule matrix according to the rules of the cellular automaton. We also provide the details of the generations of FGCA. To cover the defined concept, the parking recommendations have been figured out to show the effective performance of the research. In this proposed model, the fuzzy neighbourhood function represents the possible cell to which the vehicle can moved so that an efficient parking management can be maintained. By using fuzzy graph cellular automaton in parking recommendations, the results are more accurate than the other models. A comparative analysis is also done. In parking recommendations, the possibility of the available parking space can be predicted appropriately using the defined concepts. The results are simulated with C + + coding in MATlab.

Keywords: Cellular automaton; fuzzy set; graph cellular automaton; basic linear rules (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1142/S1793005722500089

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