Tahir Mahmood
57206168189
Publications - 6
A novel Complex q-rung orthopair fuzzy Yager aggregation operators and their applications in environmental engineering
Publication Name: Heliyon
Publication Date: 2025-01-15
Volume: 11
Issue: 1
Page Range: Unknown
Description:
Improving human health and comfort in buildings requires efficient temperature regulation. Temperature control system has a significant contribution in minimizing the impact of climate change. Temperature control system is used in industry to control temperature. The polar form of complex Pythagorean fuzzy set is a limited notion because when decision makers take the value for membership degree as 0.71+ι0.81 then we can observe that the basic condition for complex Pythagorean fuzzy set fails to hold that is r=0.712+0.812=1.3661∉[0,1]. Moreover, we can observe that the Cartesian form of a complex Pythagorean fuzzy set is also a limited notion because it can never discus advance data. Hence keeping in mind these limitations of the existing notions, in this article, we have explored the Cartesian form of a complex q-rung orthopair fuzzy set. Moreover, we have developed the Yager operational laws based on a Cartesian form of complex q-rung orthopair fuzzy set. We have introduced aggregation theory named complex q-rung orthopair fuzzy Yager weighted average and complex q-rung orthopair fuzzy Yager weighted geometric aggregation operators in Cartesian form. Based on these aggregation operators, we have initiated a multi-attribute group decision-making (MAGDM) approach to define the reliability and authenticity of the developed theory. Furthermore, we have utilized this device algorithm in the selection of a temperature control system. The comparative study of the delivered approach shows the advancement and superiority of the delivered approach.
Open Access: Yes
Prioritization of Geothermal Energy Systems for Industrial Applications by Using Hesitant Bipolar Fuzzy Multi-Criteria Decision-Making Technique Based on Dombi Operators
Publication Name: Contemporary Mathematics Singapore
Publication Date: 2025-01-01
Volume: 6
Issue: 4
Page Range: 4033-4059
Description:
The proposed research fills a significant gap in the decision-making technique for evaluating geothermal energy systems in industrial processes by introducing a new approach involving Hesitant Bipolar Fuzzy (HBF) Sets (HBFSs) with Dombi operators. The existing literature has mostly focused on uncertainty only, overlooking the aspect that decisions tend to be imprecise, bipolar, and hesitant in reality. To overcome this gap, we first introduce Dombi operators in the context of HBFSs, thereby improving the parametric flexibility in handling more complex uncertain information. Based on these operators, we establish an HBF Multi-Criteria Decision-Making (MCDM) method for the ranking of geothermal energy systems. The applicability of our proposed methodology for prioritizing different types of geothermal energy systems for industrial applications is illustrated in a detailed case study that supports the theoretical framework. The benefit of the suggested method is also supplemented by the comparison of the proposed method with the previous methods and evidence of the capability to handle uncertainty and make more precise and confident decisions. This study offers an important theoretical as well as practical contribution to decision-making practices and the choice of sustainable energy systems for geothermal energy options under uncertainty, offering decision-makers a robust framework of analysis. Moreover, we have the following key findings or outcomes of proposed research. • Development of HBF Dombi Weighted Averaging (HBFDWA) operators. • Development of HBF Dombi Ordered Weighted Averaging (HBFDOWA) operators. • Development of HBF Dombi Weighted Geometric (HBFDWG) operators. • Development of HBF Dombi Ordered Weighted Geometric (HBFDOWG) operators. • A case study is performed based on the developed operators to rank geothermal energy systems. • A comparative analysis is performed to show the superiority of the proposed approach. • A sensitivity analysis is discussed to show the influences of the parameter.
Open Access: Yes
Identification of Delay-Tolerant Networking by Employing MABAC Technique Based on Bipolar Complex Fuzzy Dombi Heronian Mean Operators
Publication Name: Contemporary Mathematics Singapore
Publication Date: 2025-01-01
Volume: 6
Issue: 3
Page Range: 3562-3612
Description:
This work proposes a hybrid decision making model for dynamic and irregularly connected communication systems called Delay-Tolerant Networks (DTNs). A resilient and adaptable network allows for communication in an environment where traditional networks may fail to operate effectively. The main significance of this system is that it is commonly utilized in such scenarios where traditional networks are impractical, such as remote areas, disaster-stricken regions, space missions, and military operations. The proposed model includes the “Multi-Attributive Border Approximation Area Comparison” (MABAC) method, together with Bipolar Complex Fuzzy Dombi Heronian Mean (BCFDHM) operators. To take the positive as well as negative attributes’ evaluations into consideration in complicated fuzzy environments, we use an enriched aggregation structure for the criteria, which incorporates the relationship between criteria through the Heronian mean function. Due to this, the MABAC technique within BCF information is more advanced and better than classical MABAC techniques in various models. After that, with the help of these enriched aggregation structures, we successfully identify and rank alternatives for DTN in an uncertain, imprecise, and bipolar condition. By employing the MABAC technique for the DTN system, we find the best and better alternative to the DTN system, which is Ã4 as mentioned below in section 4. At last, we compare our initiated work with many existing theories to prove the authenticity of the suggested work.
Open Access: Yes
Energy Storage System Selection for AI-Controlled Microgrids Using Complex Hesitant Fuzzy MCDM Approach Based on Dombi Operators
Publication Name: Contemporary Mathematics Singapore
Publication Date: 2025-01-01
Volume: 6
Issue: 3
Page Range: 3269-3300
Description:
The current definition of the Complex Hesitant Fuzzy Set (CHFS), derived from the Ramot form of complex numbers, cannot process information as in Tamir’s complex fuzzy form. We have data with uncertainty and extra information that cannot be described by any other structure than Tamir’s complex fuzzy form. Hence, in this article, we initiated the idea of CHFS based on Tamir’s complex fuzzy form and established its operational laws. Since Decision-Making (DM) theory is central to nearly all disciplines, we have proposed a novel complex hesitant fuzzy Multi-Criterion Decision-Making (MCDM) model. This method can handle all sorts of real-life MCDM problems, where the data contains uncertainty, hesitancy, and extra fuzzy information. While developing this method, we also develop and apply Dombi aggregation operators in this manuscript. After that, we discussed a case study that concerns energy storage system selection for AI-controlled microgrids and discussed how the theory we have developed can be applied to real-world challenges. Last, we conferred on how this proposed theory is superior to other theories and why it should be adopted.
Open Access: Yes
Optimizing Computer Engineering Problems Using CODAS Method with Bipolar Complex Fuzzy Soft Frank Aggregation Operators
Publication Name: Contemporary Mathematics Singapore
Publication Date: 2025-01-01
Volume: 6
Issue: 4
Page Range: 5145-5171
Description:
In this article, we start by explaining why Bipolar Complex Fuzzy Soft Set (BCFSS) is better than existing approaches by highlighting its abilities to enhance Computer Engineering (CpE) by removing ambiguity more effectively than Fuzzy Set (FS), Fuzzy Soft Set (FSS), Complex Fuzzy Soft Set (CFSS), Bipolar Fuzzy Set (BFS), Bipolar Fuzzy Soft Set (BFSS), and Bipolar Complex Fuzzy Set (BCFS). This will improve effectiveness as well as clarity. Make sure that those new to fuzzy sets properly understand the key issue in CpE. Reveal first the BCFSS’s new strategy and then detail how it differs from existing approaches, pointing out the overlooked features of previous approaches that justified your research. Enhance the preparation concept link by explaining how BCFSS enhances CpE Decision-Making (DM) in situations when conventional models are inadequate when paired with Frank Aggregation Operator (AO) (Frank Arithmetic Aggregation Operator (FAAO) and Frank Geometric Aggregation Operator (FGAO)). Moreover, keeping in mind the effectiveness of the “Combinative Distance-based Assessment (CODAS) method” we developed this method in the framework of BCFSSs and used this method and develop AOs to solve some decision-making problems related to CpE. Our sentence structure should also be refined to provide smooth transitions between ideas and to enhance readability and navigation. Lastly, provide comparison studies that highlight the improvement’s superiority over current methods to show that it is feasible.
Open Access: Yes
Energy Storage System Selection by Using Complex Intuitionistic Fuzzy Rough MCDM Technique Based on Schweizer-Sklar Operators
Publication Name: Contemporary Mathematics Singapore
Publication Date: 2025-01-01
Volume: 6
Issue: 5
Page Range: 7011-7040
Description:
Energy Storage System (ESS) is a talented solution to overcome the intermittency (that they do not produce energy all the time) and demand-supply misalliance problems in different renewable energy systems. Selecting the most optimal ESS requires the consideration of different conflicting criteria under uncertainty. This study presents a novel Multi-Criteria Decision-Making (MCDM) framework based on Complex Intuitionistic Fuzzy Rough Sets (CIFRSs) and Schweizer-Sklar aggregation operators to facilitate a more comprehensive and flexible ESS selection process. Specifically, we develop new aggregation operators namely, the Complex Intuitionistic Fuzzy Rough (CIFR) Schweizer-Sklar weighted average and the CIFR Schweizer-Sklar weighted geometric operators to model imprecise, vague, and inconsistent information. CIFR-MCDM methodology captures the intuitionistic, roughness and extra related fuzzy information in one structure. A case study is performed to illustrate the applicability of the suggested method in ranking different ESS alternatives. Comparative analysis with existing approaches confirms the robustness and effectiveness of the proposed framework in handling complex decision environments. The results highlight the potential of the CIFR-MCDM methodology to support informed and reliable ESS selection in renewable energy applications.
Open Access: Yes
