Sagvan Y. Musa^1,2, Zanyar A. Ameen^3,*, Wafa Alagal⁴, Baravan A. Asaad^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3493-3529, 2025, DOI:10.32604/cmes.2025.070019 - 30 September 2025

Abstract Urban transportation planning involves evaluating multiple conflicting criteria such as accessibility, cost-effectiveness, and environmental impact, often under uncertainty and incomplete information. These complex decisions require input from various stakeholders, including planners, policymakers, engineers, and community representatives, whose opinions may differ or contradict. Traditional decision-making approaches struggle to effectively handle such bipolar and multivalued expert evaluations. To address these challenges, we propose a novel decision-making framework based on Pythagorean fuzzy N-bipolar soft expert sets. This model allows experts to express both positive and negative opinions on a multinary scale, capturing nuanced judgments with higher accuracy. It… More >

Kenian Wang^1,2,*, Yuan Hong^1,2, Chunxiao Li²

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1123-1142, 2024, DOI:10.32604/cmc.2024.052088 - 18 July 2024

Abstract With the exponential increase in information security risks, ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment. However, experts possess a limited understanding of fundamental security elements, such as assets, threats, and vulnerabilities, due to the confidentiality of airborne networks, resulting in cognitive uncertainty. Therefore, the Pythagorean fuzzy Analytic Hierarchy Process (AHP) Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks. First, Pythagorean fuzzy AHP is employed to construct an index system… More >

Shaista Habib¹, Muhammad Akram^2,*, M. M. Ali Al-Shamiri³

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2585-2615, 2023, DOI:10.32604/cmes.2023.024551 - 23 November 2022

Abstract According to the World Health Organization (WHO), cancer is the leading cause of death for children in low and middle-income countries. Around 400,000 kids get diagnosed with this illness each year, and their survival rate depends on the country in which they live. In this article, we present a Pythagorean fuzzy model that may help doctors identify the most likely type of cancer in children at an early stage by taking into account the symptoms of different types of cancer. The Pythagorean fuzzy decision-making techniques that we utilize are Pythagorean Fuzzy TOPSIS, Pythagorean Fuzzy Entropy More > Graphic Abstract