Kifayat Ullah
6603208187
Publications - 8
Computational Assessment of Energy Supply Sustainability Using Picture Fuzzy Choquet Integral Decision Support System
Publication Name: Computers Materials and Continua
Publication Date: 2025-01-01
Volume: 85
Issue: 1
Page Range: 1311-1337
Description:
For any country, the availability of electricity is crucial to the development of the national economy and society. As a result, decision-makers and policy-makers can improve the sustainability and security of the energy supply by implementing a variety of actions by using the evaluation of these factors as an early warning system. This research aims to provide a multi-criterion decision-making (MCDM) method for assessing the sustainability and security of the electrical supply. The weights of criteria, which indicate their relative relevance in the assessment of the sustainability and security of the energy supply, the MCDM method allow users to express their opinions. To overcome the impact of uncertainty and vagueness of expert opinion, we explore the notion of picture fuzzy theory, which is a more efficient and dominant mathematical model. Recently, the theory of Aczel-Alsina operations has attained a lot of attraction and has an extensive capability to acquire smooth approximated results during the aggregation process. However, Choquet integral operators are more flexible and are used to express correlation among different attributes. This article diagnoses an innovative theory of picture fuzzy set to derive robust mathematical methodologies of picture fuzzy Choquet Integral Aczel-Alsina aggregation operators. To prove the intensity and validity of invented approaches, some dominant properties and special cases are also discussed. An intelligent decision algorithm for the MCDM problem is designed to resolve complicated real-life applications under multiple conflicting criteria. Additionally, we discussed a numerical example to investigate a suitable electric transformer under consideration of different beneficial key criteria. A comparative study is established to capture the superiority and effectiveness of pioneered mathematical approaches with existing methodologies.
Open Access: Yes
A Human-Aided Evaluation Based on Distance from Average Solution Method for the Diagnosis of Skin Disease Using T-Spherical Fuzzy Information
Publication Name: Contemporary Mathematics Singapore
Publication Date: 2025-01-01
Volume: 6
Issue: 5
Page Range: 6689-6713
Description:
Disorders of the skin have been identified as skin diseases. These medical disorders may involve severe skin manifestations, including allergic reactions, frustration, and itching. Numerous skin disorders may be inherited, while other aspects may be caused by lifestyle. To diagnose the various skin disorders based on the symptoms of skin diseases, we introduce the novel idea of Interval-Valued T-Spherical Fuzzy Set (IV-TSFS) that significantly enhances the ability to handle vagueness and unpredictability in the data being gathered. The IV-TSFS takes the concept of T-SFS by incorporating Interval Values (IVs). This innovation greatly improves the capacity to represent and manage uncertainty because they offer a structured and flexible framework that captures real-world ambiguity, vagueness, and unpredictability as compared to other classical fuzzy models. In this article, we construct the extended conventional IV-TSF Evaluation based on Distance from Average Solution (EDAS) approach by using the conventional Evaluation based on Distance from Average Solution (EDAS) method and also identifying a wide range of possibilities and understanding the potential variability in outcomes, which is especially useful in Decision-Making (DM) scenarios. This method provides a balanced view of each alternative’s performance, helping decision-makers to rank and select the most suitable option effectively. It is the most powerful way to visualize and compare the performance of various alternatives in a structured and quantitative manner. Firstly, we briefly review the description of T-SFSs and IV-TSFSs and discuss the score function Ṩcr(₮), accuracy function Ἇcr(₮), and the basic Operational Laws (OLs) of IV-TSFVs. Next, we explain the extensive interventions of the extended conventional Interval-Valued T-Spherical Fuzzy (IV-TSF) EDAS method to cope with uncertain and unreliable information, which is especially useful in DM scenarios. Finally, a numerical example is provided to effectively diagnose the favorable skin disease based on the symptoms of skin diseases by using the IV-TSF EDAS approach, and several comparative results of our proposed model with other existing Aggregation Operators (AOs) are carried out to demonstrate the invaluable benefits associated with this strategy.
Open Access: Yes
Integration of MULTIMOORA algorithm combined with circular q-rung orthopair fuzzy information for optimizing player positioning
Publication Name: Scientific Reports
Publication Date: 2025-12-01
Volume: 15
Issue: 1
Page Range: Unknown
Description:
The following paper presents a new analytical framework for the optimization of player positioning, a methodology with significant practical implications. The method implements the multi-objective optimization by ratio analysis with full multiplicative form (MULTIMOORA) in a decision-making context in which several non-commensurable performance variables have to be combined. The application of Dombi operationalizes the framework by prioritizing weighted aggregation operators coupled with circular q-rung orthopair fuzzy sets (Cq-ROFSs). The Cq-ROFSs allow multidimensional representation of uncertainty, and allow dynamic actions upon the fuzzy parameter q, such that both intuitionistic fuzzy sets and Pythagorean fuzzy sets are subsets. Two Dombi prioritized operators on Cq-ROFSs are thereby devised a Cq-ROFSs Dombi prioritized weighted averaging operator (Cq-ROFSDPWA) and a Cq-ROFSs Dombi prioritized weighted geometric operator (Cq-ROFSDPWG). Results from empirical experiments are reported that demonstrate the performance of the resulting methodology, highlighting its practical relevance. The fundamental properties of these operators are also examined. The proposed aggregation operators are applied within the MULTIMOORA technique to assess their effectiveness. Numerical examples demonstrate that the methods yield logical and consistent results across different decision-making scenarios. Comparative analyses further highlight the advantages of the Cq-ROFSDPWA and Cq-ROFSDPWG operators over existing approaches.
Open Access: Yes
Innovating the Pilot Project Based on Multi-Attribute Group Decision-Making and Some Prioritized Aggregation Operators for Complex Pythagorean Fuzzy Information
Publication Name: Fuzzy Information and Engineering
Publication Date: 2025-01-01
Volume: 17
Issue: 3
Page Range: 261-283
Description:
Gathering information from a real-life scenario is a very difficult process due to involvement of the multiple criteria and human opinion. A complex Pythagorean fuzzy set (CPyFS) is an interesting tool to deal with uncertainty while gathering information from human opinion involved in real-life scenarios. But, the aggregation of the information gathered by CPyFS becomes very hectic. Several aggregation operators (AOs) aggregate the information in the form of complex Pythagorean fuzzy values (CPyFVs). However, they lack the prioritization of attributes according to their weights. In this article, an interesting new class of AOs including complex Pythagorean fuzzy (CPyF) prioritized averaging operator (CPyFPAO) and CPyF prioritized geometric operator (CPyFPGO) is introduced. Basic and necessary properties of the introduced AOs are observed. Furthermore, the case study is discussed where the introduced AOs are applied to seek the most suitable optimized site for starting a pilot health project with the help of the multi-attribute group decision-making (MAGDM) process. The results obtained from all proposed AOs are analyzed and compared with some existing AOs. All the analyses are explained with the help of the tabulated data and graphs.
Open Access: Yes
A data-driven approach to tackling academic stress-coping and mental health issues in college students using spherical fuzzy MARCOS methodology
Publication Name: Applied Soft Computing
Publication Date: 2025-12-01
Volume: 185
Issue: Unknown
Page Range: Unknown
Description:
The drastically developing nature of the knowledge economy and the rising need for top-notch expertise have placed tremendous pressure on college students. As higher education becomes more accessible, masses of students are enrolling in colleges, which puts additional pressure on colleges and institutions; as a result, they cannot provide adequate resources to the students. As the class size increases, many students require mental health assistance, academic guidance, and financial aid, which then puts pressure on the teachers and the facilities. This flood of students overloads the facilities, resulting in it becoming more challenging to provide attention and concern, leading many students to feel overlooked and affecting their mental health. Due to not getting timely support, students may find it challenging to handle their academic responsibilities. Moreover, the students face a heavy workload, unclear guidance, and limited resource access. The objective of this study is to develop a structured, data-driven decision-making framework for systematically evaluating and improving student mental health and academic stress-coping strategies in a college setting. To address this, a comprehensive decision-making structure, measurement of alternatives, and ranking according to the compromised solution (MARCOS) within the spherical fuzzy (SF) environment, has been applied, which evaluates the key factors causing mental health issues by comparing the ideal and anti-ideal alternatives. The novelty of the proposed approach lies in leveraging the SF framework's explicit ability to model hesitation (abstinence) alongside truth and falsity degrees, enabling more accurate representation of subjective psychological assessments compared to traditional fuzzy models. Furthermore, the method calculates utility functions corresponding to each alternative (coping technique), prioritizes the strategies, and selects the most effective intervention. The results reveal that personalized mental health plans emerged as the top-ranked coping strategy, highlighting the importance of tailored support in culturally and contextually diverse academic environments.
Open Access: Yes
Critical impact of automobile industry with advanced decision support system and Aczél-Alsina Hammy mean operators
Publication Name: Scientific Reports
Publication Date: 2026-12-01
Volume: 16
Issue: 1
Page Range: Unknown
Description:
The automobile industry plays a pivotal role in global economic development, technological innovation, and sustainable mobility solutions. It drives advancements in engineering, manufacturing, and smart technologies and influences transportation systems. A decision analysis system in the automobile industry serves as a structured framework to evaluate complex choices involving design, production, supply chain, marketing, and sustainability strategies based on vague human information. To achieve the main goal of this article, we explore the concepts of spherical fuzzy sets (SFSs) for handling uncertainty and vagueness in human judgments. The SFS is a more efficient and broader fuzzy framework that has extensive information about an object. Besides the concepts discussed in the fuzzy framework, we also modify the theory of Hamy mean (HM) models under Aczel Alsina operations. By combining two different theories of Aczel Alsina operations and Hamy mean models, we derive a family of mathematical models, namely spherical fuzzy Aczel Alsina Hamy mean (SFAHM) and spherical fuzzy Aczel Alsina weighted Hamy mean (SFAWHM) operators. Moreover, another generalization of the Dual HM (DHM) models is modified in the form of spherical fuzzy Aczel Alsina DHM (SFADHM) and spherical fuzzy Aczel Alsina weighted DHM (SFAWDHM) operators. Some reliable and appropriate characteristics are also studied to demonstrate the flexibility of the proposed operators. An intelligent decision algorithm of the multi-attribute group decision-making (MAGDM) problem is discussed to resolve real-life applications and a group of expert’s opinions. To see the effectiveness and reliability of newly developed terminologies, we discussed a numerical example to choose desirable alternatives under an automobile industry system. The influence study is also presented here by setting numerous parametric values in the currently discussed methodologies. To showcase the validation and superiority of diagnosed mathematical models, we establish a comparative study to compare the results of invented approaches with the results of existing terminologies.
Open Access: Yes
Positive Impact of Waste Management Strategies and Decision Analysis with Intuitionistic Fuzzy Sugeno-Weber Aggregation Operators
Publication Name: Boletim Da Sociedade Paranaense De Matematica
Publication Date: 2025-08-13
Volume: 43
Issue: 3
Page Range: Unknown
Description:
Waste management is a crucial and significant subject that has gained much attention globally because it has several environmental, social, financial and economic implications. Solid waste management is a very challenging task for clean urban and rural societies. We studied some reliable strategies for handling the waste materials and garbage produced by people. To serve this purpose, an intuitionistic fuzzy set (IFS) is a well-known model used for modeling and processing unpredictable information and providing accurate approximated results in the decision-making process. Power average operators allow the interrelationship of the input arguments and deal with uncertain information in complicated situations. This article expresses Sugeno-weber triangular norms under intuitionistic fuzzy (IF) information. We developed a class of new aggregation operators, including intuitionistic fuzzy Sugeno-Weber power-weighted average (IFSWPWA) and intuitionistic fuzzy Sugeno-Weber power-weighted geometric (IFSWPWG) operators. It is observed that both the newly proposed operators satisfy the properties of aggregation. The multi-criteria decision-making (MCDM) problem is proposed to evaluate real-life applications and numerical examples. An experimental case study under the system of waste materials is considered in the article to reveal the intensity and applicability of derived approaches. The comparison analysis and sensitivity analysis show the significance of our proposed work.
Open Access: Yes
DOI: 10.5269/bspm.79085
Multi robot task assignment with decision analysis and circular q-Rung orthopair fuzzy Schweizer-Sklar T-norms
Publication Name: Journal of Umm Al Qura University for Applied Sciences
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
A multi-robotic task assignment and decision analysis system refers to an advanced framework in robotics and artificial intelligence where multiple robots are coordinated to perform a set of tasks efficiently and intelligently. This article designs innovative approaches to fix uncertainty during task allocation in a multi-robotic system under a hybrid fuzzy framework and decision-making models. To achieve this goal, we expose a modified theory of circular q-rung orthopair fuzzy set (Crq-ROFS), which is a broader framework of intuitionistic fuzzy sets and q-rung orthopair fuzzy sets. We formulated feasible operations of Schweizer-Sklar t-norm and t-conorm in light of circular information about q-rug orthopair fuzzy (Crq-ROF). We also delved into a family of mathematical approaches of Schweizer-Sklar t-norm and t-conorm, namely, Crq-ROF Schweizer-Sklar weighted average (Crq-ROFSSWA) and Crq-ROF Schweizer-Sklar weighted geometric (Crq-ROFSSWG) operators with dominant propositions. The theory of the multi-attribute decision-making (MADM) problem offers authentic and reliable solutions by aggregating human judgment. An experimental case study discussed evaluating an ideal solution under consideration of multi-criteria or attribute information. A comparison method is conducted to showcase the reliability and effectiveness of the pioneering approaches with existing approaches.
Open Access: Yes
