The project can work fine but still under devlopping to improve functionalty and add more features

i have devoloped a tunable fuzzy logic inference system (FIS). This system can be fine-tuned through optimization algorithms to meet specific cost function requirements. With this FIS system, users can create up to two inputs and one output, with the ability to customize each fuzzy variable using triangular or trapezoidal membership functions.

One of the most exciting features of our FIS system is that it allows users to define the objective function that needs to be minimized and run the optimization process to achieve their desired outcomes. This means that this system offers optimization capabilities for a wide variety of applications. This project offers:

• Flexible was to create two-input one-output FIS Chosing from defferent optimization algorithms
• Optimizing fuzzy variable ranges
• Optimizing membership function types altering betting triangular and trapezoidal MFs
• Tuning the membership function parameter and shapes
• Tuning the rule-base
• Optimizing the rule-weights

this aim of this project is to represents a significant step forward in the field of fuzzy logic, as it provides a powerful and flexible tool for optimizing complex systems. this FIS system will prove to be a valuable asset for researchers, engineers, who are looking for ways to optimize their processes and achieve better outcomes.