Parking Free Space Prediction Using a Fuzzy Controller

Designing a fuzzy logic controller (FLC) has proven to be an effective approach for controlling complex and nonlinear systems where traditional or conventional control methods fail. This paper presents the procedure and implementation of designing a FLC for Parking Free Space Prediction. The proposed controller utilizes fuzzy inference to model system dynamics and make real-time decisions based on linguistic rules and membership functions. The design process includes the fuzzification of input variables, Design inference engine and Knowledge base section, then defuzzification to generate crisp outputs. To enhance the controller's performance, advanced techniques such as adaptive fuzzy systems and hybrid approaches integrating fuzzy logic with machine learning algorithms are explored, the integration of adaptive algorithms allows the system to adjust in response to changing environments, further improving its prediction capabilities. The proposed approach demonstrates the potential of fuzzy logic to revolutionize intelligent parking systems and provides a framework for future enhancements in smart city infrastructure.

کلیدواژه ها:

Fuzzy ، Rule ، Inference ، Fuzzification ، De-Fuzzification ، Adaptive