Zhe Liu^1,2,3,*, Sijia Zhu⁴, Yulong Huang^1,*, Tapan Senapati^5,6,7, Xiangyu Li⁸, Wulfran Fendzi Mbasso⁹, Himanshu Dhumras¹⁰, Mehdi Hosseinzadeh^11,12,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2157-2188, 2025, DOI:10.32604/cmes.2025.072352 - 26 November 2025

Abstract Uncertainty and ambiguity are pervasive in real-world intelligent systems, necessitating advanced mathematical frameworks for effective modeling and analysis. Fermatean fuzzy sets (FFSs), as a recent extension of classical fuzzy theory, provide enhanced flexibility for representing complex uncertainty. In this paper, we propose a unified parametric divergence operator for FFSs, which comprehensively captures the interplay among membership, non-membership, and hesitation degrees. The proposed operator is rigorously analyzed with respect to key mathematical properties, including non-negativity, non-degeneracy, and symmetry. Notably, several well-known divergence operators, such as Jensen-Shannon divergence, Hellinger distance, and χ²-divergence, are shown to be special cases More >

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 >

Sijia Zhu¹, Yuhan Li², Prasanalakshmi Balaji^3,*, Akila Thiyagarajan³, Rajanikanth Aluvalu⁴, Zhe Liu^5,6,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2099-2121, 2025, DOI:10.32604/cmes.2025.068734 - 31 August 2025

Abstract While interval-valued picture fuzzy sets (IvPFSs) provide a powerful tool for modeling uncertainty and ambiguity in various fields, existing divergence measures for IvPFSs remain limited and often produce counterintuitive results. To address these shortcomings, this paper introduces two novel divergence measures for IvPFSs, inspired by the Jensen-Shannon divergence. The fundamental properties of the proposed measures—non-degeneracy, symmetry, triangular inequality, and boundedness—are rigorously proven. Comparative analyses with existing measures are conducted through specific cases and numerical examples, clearly demonstrating the advantages of our approach. Furthermore, we apply the new divergence measures to develop an enhanced interval-valued picture More >

Ikhtesham Ullah¹, Muhammad Sajjad Ali Khan², Fawad Hussain¹, Madad Khan³, Kamran^4,*, Ioan-Lucian Popa^5,6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2123-2164, 2025, DOI:10.32604/cmes.2025.064832 - 31 August 2025

Abstract Multi-criteria decision-making (MCDM) is essential for handling complex decision problems under uncertainty, especially in fields such as criminal justice, healthcare, and environmental management. Traditional fuzzy MCDM techniques have failed to deal with problems where uncertainty or vagueness is involved. To address this issue, we propose a novel framework that integrates group and overlap functions with Aczel-Alsina (AA) operational laws in the intuitionistic fuzzy set (IFS) environment. Overlap functions capture the degree to which two inputs share common features and are used to find how closely two values or criteria match in uncertain environments, while the… More >

Hafiz Muhammad Waqas¹, Tahir Mahmood^1,2, Walid Emam³, Ubaid ur Rehman⁴, Dragan Pamucar^5,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4699-4727, 2025, DOI:10.32604/cmc.2025.065011 - 30 July 2025

Abstract Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks. It is the identification of malicious activity, unauthorized access, and possible intrusions in networks and systems. Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data, learn patterns, and anticipate potential threats. Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly. Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks. This research advocates for proactive measures and… More >

Sana Shahab¹, Ibtehal Alazman², Ashit Kumar Dutta³, Mohd Anjum⁴, Vladimir Simic^5,6,7,*, Željko Stević⁸, Nouf Abdulrahman Alqahtani²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2155-2183, 2025, DOI:10.32604/cmes.2025.064553 - 30 May 2025

Abstract With the increasing complexity of hotel selection, traditional decision-making models often struggle to account for uncertainty and interrelated criteria. Multi-criteria decision-making (MCDM) techniques, particularly those based on fuzzy logic, provide a robust framework for handling such challenges. This paper presents a novel approach to MCDM within the framework of Circular Intuitionistic Fuzzy Sets (C-IFS) by combining three distinct methodologies: Weighted Aggregated Sum Product Assessment (WASPAS), an Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN), and the CRITIC method (Criteria Importance Through Intercriteria Correlation). To address the dynamic nature of traveler preferences in hotel selection,… More >

Shah Zeb Khan¹, Muhammad Rahim², Adel M. Widyan^3,*, A. Almutairi³, Njood Shaher Ethaar Almutire³, Hamiden Abd El-Wahed Khalifa³

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 2185-2211, 2025, DOI:10.32604/cmes.2025.063929 - 30 May 2025

Abstract This study introduces a novel distance measure (DM) for spherical fuzzy sets (SFSs) to improve decision-making in complex and uncertain environments. Many existing distance measures either fail to satisfy essential axiomatic properties or produce unintuitive outcomes. To address these limitations, we propose a new three-dimensional divergence-based DM that ensures mathematical consistency, enhances the discrimination of information, and adheres to the axiomatic framework of distance theory. Building on this foundation, we construct a multi-criteria decision-making (MCDM) model that utilizes the proposed DM to evaluate and rank alternatives effectively. The applicability and robustness of the model are More >

Pham Huy Thong¹, Hoang Thi Canh^2,3,*, Luong Thi Hong Lan⁴, Nguyen Tuan Huy⁴, Nguyen Long Giang^1,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5461-5485, 2025, DOI:10.32604/cmc.2025.065127 - 19 May 2025

Abstract Multi-view clustering is a critical research area in computer science aimed at effectively extracting meaningful patterns from complex, high-dimensional data that single-view methods cannot capture. Traditional fuzzy clustering techniques, such as Fuzzy C-Means (FCM), face significant challenges in handling uncertainty and the dependencies between different views. To overcome these limitations, we introduce a new multi-view fuzzy clustering approach that integrates picture fuzzy sets with a dual-anchor graph method for multi-view data, aiming to enhance clustering accuracy and robustness, termed Multi-view Picture Fuzzy Clustering (MPFC). In particular, the picture fuzzy set theory extends the capability to… More >

Anastasios Dounis^*, Ioannis Palaiothodoros, Anna Panagiotou

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 759-811, 2025, DOI:10.32604/cmes.2024.057888 - 17 December 2024

Abstract Accurate medical diagnosis, which involves identifying diseases based on patient symptoms, is often hindered by uncertainties in data interpretation and retrieval. Advanced fuzzy set theories have emerged as effective tools to address these challenges. In this paper, new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets (q-ROFS) and interval-valued q-rung orthopair fuzzy sets (IVq-ROFS). Three aggregation operators are proposed in our methodologies: the q-ROF weighted averaging (q-ROFWA), the q-ROF weighted geometric (q-ROFWG), and the q-ROF weighted neutrality averaging (q-ROFWNA), which enhance decision-making under uncertainty. These operators are paired More > Graphic Abstract

Daekook Kang¹, Ramya Lakshmanaraj², Samayan Narayanamoorthy², Navaneethakrishnan Suganthi Keerthana Devi², Samayan Kalaiselvan³, Ranganathan Saraswathy⁴, Dragan Pamucar^5,6,7,*, Vladimir Simic^8,9

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4947-4972, 2024, DOI:10.32604/cmc.2024.055260 - 12 September 2024

Abstract This socialized environment among educated and developed people causes them to focus more on their appearance and health, which turns them towards medical-related treatments, leading us to discuss anti-aging treatment methods for each age group, particularly for urban people who are interested in this. Some anti-aging therapies are used to address the alterations brought on by aging in human life without the need for surgery or negative effects. Five anti-aging therapies such as microdermabrasion or dermabrasion, laser resurfacing anti-aging skin treatments, chemical peels, dermal fillers for aged skin, and botox injections are considered in this… More >