Information error-based Pythagorean fuzzy cloud technique for managing road traffic risk
Mahmoud A. Zaher1,*, Marwan Al-Akaidi 2
1 Faculty of Artificial Intelligence, Egyptian Russian University (ERU), Cairo, Egypt
2 Al-Farahidi University - Baghdad, Iraq
Emails: mahmoud.zaher@eru.edu.eg ; marwan1@ieee.org
Abstract
This research proposes a novel procurement process for road traffic analysis by using the information error-based Pythagorean fuzzy cloud (PFC) method. First, a 20-factor assessment index method for road traffic was developed. The notion of PFCs was devised to represent the assessment information of an indication. Concurrently, the PFC-weighted Bonferroni mean (PFCWBM) operator was created to aggregate the evaluation data of multiple indications. Then, a method for evaluating and selecting road traffic based on the PFCWBM operator was developed. Furthermore, an application for demonstrating the efficacy of the suggested method was provided. Finally, the effectiveness of the proposed method was evaluated. Results demonstrate that our algorithm can define and assess complicated data with relatively high susceptibility and environmental adaptation.
Keywords: Pythagorean fuzzy cloud; road traffic; information error; risk analysis