The New Generation of Fuzzy Inference Systems

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#Artificial Intelligence #Fuzzy Systems #Computational Intelligence #Intelligent Systems #Machine Learning #Inference Systems #Fuzzy Sets #Fuzzy Logic #Clustering #Modeling #Control systems #Optimization #Robotic #Type-2 fuzzy sets #Fuzzy classification #Membership functions #Possibility theory #Intelligent Control #Man-Machine #Cybernetic #FFIS #Uncertain Systems #Mamdani's System #T-S systems #Information #Matlab

This is a tutorial on the new generation of fuzzy inference systems called fractional fuzzy inference systems. It opens a gate to a space of new ideas, new design methods, and a new way to increase the intelligence quotient of machines.

The fractional fuzzy inference systems (FFISs), as the new generation of fuzzy inference systems, emerged in 2020. It has been demonstrated that typical FISs (e.g., Mamdani's FIS) is a special case of FFISs.

Additionally, independent of the problem, typical FISs never lead to more satisfactory results than those which fractional FISs can obtain. In simple words (informally speaking), assume that you have got a project, device, or a system in which you have employed a typical FIS (e.g., Mamdani's FIS).

Suppose that you replace the typical FIS with its corresponding fractional FIS. In that case, you certainly get more satisfactory results (e.g., the error is reduced, the efficiency increases, the accuracy increases, the cost in optimization problem decreases, the quality of image increases, the control performance is improved, etc.).

You don't need to change the inputs, outputs, defuzzification method, fuzzification method, if-then rule base, or the general structure of membership functions—only the inference engine changes.

Who should watch this tutorial?

  • Those who would like to get more satisfactory results from FISs
  • Those who have got a project and would like to improve the results Those who are looking for new ideas
  • Those who would like to increase the intelligence of their systems
  • Those who have worked with FISs and would like to revisit them with more satisfactory results
  • Those who would like to register some patents
  • Those who teach FISs and would like to be familiar with a new generation of FISs
  • Those who are looking for new ways for designing engineering systems
  • Those who are looking for ideas for their thesis
  • Those who are passionate about learning new ideas in the field of fuzzy systems

This is a tutorial on the new generation of fuzzy inference systems called fractional fuzzy inference systems. It opens a gate to a space of new ideas, new design methods, and a new way to increase the intelligence quotient of machines.

The fractional fuzzy inference systems (FFISs), as the new...

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