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Fuzzy logic is an extension of traditional logic that allows for partial truth values between 0 and 1. One key component of fuzzy logic is fuzzy implication, which is used in systems like decision-making, control systems, and AI to model uncertain conditions and outcomes. Unlike classical logic, fuzzy implication can handle situations where truth is not binary. Additionally, fuzzy implication operators do not account for reliability of information. This article is specifically devoted to extension of ALI-I fuzzy implication to Z-implication. The goal of such an extension would be to improve flexibility and applicability to more complex or uncertain situations that cannot be easily captured by classical fuzzy logic.

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Extension of ALI-I Logic to Z-Fuzzy Environment

  • 会议论文

  • 发表日期：

    2026年

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  • Rafik A. Aliev,
  • Shamil A. Ahmadov,
  • Latafat A. Gardashova,
  • Oleg Huseynov

摘要

Fuzzy logic is an extension of traditional logic that allows for partial truth values between 0 and 1. One key component of fuzzy logic is fuzzy implication, which is used in systems like decision-making, control systems, and AI to model uncertain conditions and outcomes. Unlike classical logic, fuzzy implication can handle situations where truth is not binary. Additionally, fuzzy implication operators do not account for reliability of information. This article is specifically devoted to extension of ALI-I fuzzy implication to Z-implication. The goal of such an extension would be to improve flexibility and applicability to more complex or uncertain situations that cannot be easily captured by classical fuzzy logic.