Identification of desalination and wind power plants sites using m-polar fuzzy Aczel–Alsina aggregation information

Abstract

Real-world decision-making problems often include multi-polar uncertainties dependent on multi-dimensional attributes. The m-polar fuzzy (mF) sets can efficiently handle such multi-faceted complications with T-norm based weighted aggregation techniques. The Aczel–Alsina T-norms offer comparatively flexible and accurate aggregation than the other well-known T-norm families. Consequently, this work introduced novel mF Aczel–Alsina aggregation operators (AOs), including weighted averaging (mFAAWA, mFAAOWA, mFAAHWA) and weighted geometric (mFAAWG, mFAAOWG, mFAAHWG) AOs. The fundamental properties, including boundedness, idempotency, monotonicity, and commutativity are investigated. Based on the proposed AOs, a decision-making algorithm is developed and implemented to solve two detailed multi-polar site selection problems (for desalination plant and for wind-power plant). Finally, a comparison with mF Dombi and mF Yager AOs reveals that different T-norm based AOs may yeild different solutions for the same problem.

Improving Risk Assessment Model for Cyber Security Using Robust Aggregation Operators for Bipolar Complex Fuzzy Soft Inference Systems

“…These FSs, BFSs, SSs, CFSs, BCFSs, FSSs, CFSSs, and BFSSs are the special parts of BCFSSs. After BCFSSs were considered by Mahmood et al [9], there were still few works on aggregation operators (AOs) for BCFSSs in the literature. In this paper, we continue working on BCFSSs by giving operational laws for BCFSSs and then propose some AOs for BCFSSs.…”

“…Thus, FSs are the dominant case of BFSs because of some limitations in FSs, and so BFSs are used to improve FSs. Because of their advantages, researchers have applied BFSs in different fields, such as in [7][8][9].…”