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In this research investigation, the authors present a Model of Optimization of the Fuzzy Logic Analysis based on the Linguistic Variables Number and their Bounds Optimization, supplemented with an OCTAVE Computer Program Code illustrating the Model genericness at Levels 2 and 3. It can be generally noted that in Fuzzy Logic Analysis, the Fuzzy Logic Output is good enough only up to the sanctity of the Fuzzy Logic Linguistic Variables Bounds and also the Number of Fuzzy Linguistic Variables considered. This problem can be averted when we consider holistic analysis of the all possible Fuzzy Logic Linguistic Variables Bounds cases constrained by heuristic colloquial sense without affecting the optimization scheme, for each number of Linguistic Variables considered among all the number of possible Linguistic Variables. Such optimization analysis is mathematically validated with regards the Fuzzy Logic Linguistic Variables by noting that the Fuzzy Logic Final Output Answer is best for the case of Linguistic Variable Bounds which has the Minimum Sum of Squares of Deviations w.r.t all other answers derived considering all other possible cases of Fuzzy Logic Output Answer’s Sum of Squares of Deviations w.r.t to all other answers derived considering all other possible cases of the Fuzzy Linguistic Variable Bounds in holisticness. And such Optimization is validated w. r. t the Number of Fuzzy Linguistic Variables by noting that for the Optimal Number of Fuzzy Linguistic Variable Bounds, the Sum of Squares of Deviations of the Fuzzy Output answers gotten from each of the best Bounds for each Number of Fuzzy Linguistic Variables considered lies at the knee point of Elbow Type Plot drawn by plotting those thusly gotten Sum of Squares of Deviations of the Fuzzy Output answers of the best Fuzzy Linguistic Variable Bounds against the Number of Fuzzy Linguistic Variables considered for the analysis. This model is of profound significance as this helps one in constructing of Optimal Telescopes and as well as Optimal Fuzzy Logic based Fuzzy Governors and Controllers.

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Fuzzy Logic Linguistic Variables Number and Bounds Optimization—(Levels 2 and 3)

  • 会议论文

  • 发表日期：

    2025年

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  • Ramesh Chandra Bagadi,
  • K. V. G. D. Balaji,
  • Rudra Pratap Das

摘要

In this research investigation, the authors present a Model of Optimization of the Fuzzy Logic Analysis based on the Linguistic Variables Number and their Bounds Optimization, supplemented with an OCTAVE Computer Program Code illustrating the Model genericness at Levels 2 and 3. It can be generally noted that in Fuzzy Logic Analysis, the Fuzzy Logic Output is good enough only up to the sanctity of the Fuzzy Logic Linguistic Variables Bounds and also the Number of Fuzzy Linguistic Variables considered. This problem can be averted when we consider holistic analysis of the all possible Fuzzy Logic Linguistic Variables Bounds cases constrained by heuristic colloquial sense without affecting the optimization scheme, for each number of Linguistic Variables considered among all the number of possible Linguistic Variables. Such optimization analysis is mathematically validated with regards the Fuzzy Logic Linguistic Variables by noting that the Fuzzy Logic Final Output Answer is best for the case of Linguistic Variable Bounds which has the Minimum Sum of Squares of Deviations w.r.t all other answers derived considering all other possible cases of Fuzzy Logic Output Answer’s Sum of Squares of Deviations w.r.t to all other answers derived considering all other possible cases of the Fuzzy Linguistic Variable Bounds in holisticness. And such Optimization is validated w. r. t the Number of Fuzzy Linguistic Variables by noting that for the Optimal Number of Fuzzy Linguistic Variable Bounds, the Sum of Squares of Deviations of the Fuzzy Output answers gotten from each of the best Bounds for each Number of Fuzzy Linguistic Variables considered lies at the knee point of Elbow Type Plot drawn by plotting those thusly gotten Sum of Squares of Deviations of the Fuzzy Output answers of the best Fuzzy Linguistic Variable Bounds against the Number of Fuzzy Linguistic Variables considered for the analysis. This model is of profound significance as this helps one in constructing of Optimal Telescopes and as well as Optimal Fuzzy Logic based Fuzzy Governors and Controllers.