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Fuzzy Graph Cellular Automaton and Its Applications in Parking Recommendations

Author

Listed:
  • B. Praba

    (Sri Sivasubramaniya Nadar College of Engineering Chennai, Tamil Nadu, India)

  • R. Saranya

    (Sri Sivasubramaniya Nadar College of Engineering Chennai, Tamil Nadu, India)

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.

Suggested Citation

  • B. Praba & R. Saranya, 2022. "Fuzzy Graph Cellular Automaton and Its Applications in Parking Recommendations," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 147-162, March.
    • Handle: RePEc:wsi:nmncxx:v:18:y:2022:i:01:n:s1793005722500089
    DOI: 10.1142/S1793005722500089
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