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This study investigates Asymmetric Interval Numbers (AINs) and their potential to improve the accuracy of linear equation solutions under uncertainty compared to Moore interval arithmetic. AINs introduce a novel approach to representing uncertainty by incorporating an expected value. The primary objective is to compare the solution accuracy between AINs and Moore’s approach through a series of simulation tests. We design experiments that start with crisp values and gradually introduce uncertainty, assessing how AINs affect result quality across various scenarios. These simulations provide significant notes on the performance of AINs relative to Moore’s interval arithmetic, highlighting their potential advantages in handling uncertainty.

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Comparison of Solution Accuracy for Linear Equations Using Moore’s Interval Numbers and Asymmetric Interval Numbers

  • 会议论文

  • 发表日期：

    2026年

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  • Wojciech Sałabun,
  • Andrii Shekhovtsov

摘要

This study investigates Asymmetric Interval Numbers (AINs) and their potential to improve the accuracy of linear equation solutions under uncertainty compared to Moore interval arithmetic. AINs introduce a novel approach to representing uncertainty by incorporating an expected value. The primary objective is to compare the solution accuracy between AINs and Moore’s approach through a series of simulation tests. We design experiments that start with crisp values and gradually introduce uncertainty, assessing how AINs affect result quality across various scenarios. These simulations provide significant notes on the performance of AINs relative to Moore’s interval arithmetic, highlighting their potential advantages in handling uncertainty.