Fuzzy systems are considered a revolutionary approach in our perspective on problem-solving. Prior to the introduction of fuzzy systems, it was practically impossible to incorporate human knowledge into computations and modeling of nonlinear problems based on the human brain’s inferential approach. The distinct features of a fuzzy system include the lack of a need for a database and the ability to define a set of rules to solve a problem. This approach has been widely applicable across all sciences and has demonstrated performance that has been recognized with over fifty honorary doctorates (during their lifetime) for its Iranian-Azerbaijani creator, Professor Lotfi Aliaskerzadeh. This educational collection focuses on fuzzy systems. Accordingly, the structural details, modeling approach, and specific elements of fuzzy systems are explained. Alongside problem-solving, the definition of a fuzzy system using optimization algorithms is also presented. After completing this course, you will be capable of implementing your problem based on the presented technique and writing your articles accordingly.

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  • 3 hours and 45 minutes of instructional videos
  • Programming and implementation tutorials
  • Integration with optimization algorithms tutorial
  • Practical training on fuzzy systems
  • Detailed inference training
  • Tips for writing articles
  • Access to executable codes


  • Part 1: What is a Fuzzy System?
  • Part 2: Implementation in MATLAB 2020
  • Part 3: Information to Provide for Readers of Fuzzy Articles
  • Part 4: Modeling Fuzzy Systems Based on the Transit Search Optimization Algorithm (2022)


Dr. Masoomeh Mirrashid
Research Fellow (Postdoctoral)

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