Precision and Efficiency Meet: Computing the Similarity of Interval Type-2 Trapezoidal Fuzzy Sets DOI
Babak Rezaee

Journal of Intelligent & Fuzzy Systems, Год журнала: 2025, Номер unknown

Опубликована: Апрель 15, 2025

The proliferation of interval type-2 fuzzy sets in domains characterized by substantial uncertainty, particularly natural language processing and intelligent decision-making systems, has highlighted the critical need for efficient accurate similarity assessment methodologies. However, evaluating between presents considerable challenges, primarily due to computational inefficiencies associated with traditional measurement techniques. This paper addresses these challenges proposing a approach aimed at enhancing efficiency assessments trapezoidal sets. core proposed lies leveraging geometric properties trapezoids determine closed polygon that results from intersection two non-normal type-1 method eliminates complex sequential condition evaluations intricate flowcharts traversal common existing methods. A key contribution this work is novel handling infeasible points, ensuring without sacrificing precision. implementation incorporates Shoelace algorithm area computation, further efficiency. Numerical analysis demonstrates provides streamlined computationally solution sets, optimizing both precision algorithmic performance.

Язык: Английский

I2QD: Unsupervised feature selection via information quality, quantity, and difference degree DOI
Pengfei Zhang, Yuxin Zhao, Lvhui Hu

и другие.

Information Processing & Management, Год журнала: 2025, Номер 62(5), С. 104173 - 104173

Опубликована: Апрель 9, 2025

Язык: Английский

Процитировано

0

Precision and Efficiency Meet: Computing the Similarity of Interval Type-2 Trapezoidal Fuzzy Sets DOI
Babak Rezaee

Journal of Intelligent & Fuzzy Systems, Год журнала: 2025, Номер unknown

Опубликована: Апрель 15, 2025

The proliferation of interval type-2 fuzzy sets in domains characterized by substantial uncertainty, particularly natural language processing and intelligent decision-making systems, has highlighted the critical need for efficient accurate similarity assessment methodologies. However, evaluating between presents considerable challenges, primarily due to computational inefficiencies associated with traditional measurement techniques. This paper addresses these challenges proposing a approach aimed at enhancing efficiency assessments trapezoidal sets. core proposed lies leveraging geometric properties trapezoids determine closed polygon that results from intersection two non-normal type-1 method eliminates complex sequential condition evaluations intricate flowcharts traversal common existing methods. A key contribution this work is novel handling infeasible points, ensuring without sacrificing precision. implementation incorporates Shoelace algorithm area computation, further efficiency. Numerical analysis demonstrates provides streamlined computationally solution sets, optimizing both precision algorithmic performance.

Язык: Английский

Процитировано

0