Analysis of TOPSIS techniques based on bipolar complex fuzzy N‐soft setting and their applications in decision‐making problems

Mahmood, Tahir; Rehman, Ubaid ur; Ali, Zeeshan; Haleemzai, Izatmand

doi:10.1049/cit2.12209

Cited by 8 publications

(1 citation statement)

References 60 publications

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“…Fatimah et al [ 17 ] introduced N -soft sets as a broader concept than soft sets. Several novel hybrid models such as N -bipolar soft sets [ 18 ], N -polar soft sets [ 19 ], complex fermatean fuzzy N -soft sets [ 20 ], bipolar fuzzy N -soft sets [ 21 ], bipolar complex fuzzy N-soft set [ 22 ], bipolar complex intuitionistic fuzzy N-soft [ 23 ], probabilistic hesitant N -soft sets [ 24 ], fuzzy N -soft expert sets [ 25 ], spherical fuzzy N-soft expert sets [ 26 ], Pythagorean fuzzy N-soft expert sets [ 27 ], have been developed by researchers. These models demonstrate the effective handling of hybrid situations by N -soft sets.…”

Section: Introductionmentioning

confidence: 99%

N-bipolar hypersoft sets: Enhancing decision-making algorithms

Musa

2024

PLoS ONE

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This paper introduces N-bipolar hypersoft (N-BHS) sets, a versatile extension of bipolar hypersoft (BHS) sets designed to effectively manage evaluations encompassing both binary and non-binary data, thereby exhibiting heightened versatility. The major contributions of this framework are twofold: Firstly, the N-BHS set introduces a parameterized representation of the universe, providing a nuanced and finite granularity in perceiving attributes, thereby distinguishing itself from conventional binary BHS sets and continuous fuzzy BHS sets. Secondly, this model signifies a new area of research aimed at overcoming limitations inherent in the N-bipolar soft set when handling multi-argument approximate functions. Through the strategic partitioning of attributes into distinct subattribute values using disjoint sets, the N-BHS set emerges as a powerful tool for effectively addressing uncertainty-related problems. In pursuit of these objectives, the paper outlines various algebraic definitions, including incomplete N-BHS sets, efficient N-BHS sets, normalized N-BHS sets, equivalence under normalization, N-BHS complements, and BHS sets derived from a threshold, exemplified through illustrative examples. Additionally, the article explores set-theoretic operations within the N-BHS sets framework, such as relative null/whole N-BHS sets, N-BHS subsets, and two distinct approaches to N-BHS extended/restricted union and intersection. Finally, it proposes and compares decision-making methodologies regarding N-BHS sets, including a comprehensive comparison with relevant existing models.

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Section: Introductionmentioning

confidence: 99%

N-bipolar hypersoft sets: Enhancing decision-making algorithms

Musa

2024

PLoS ONE

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Pattern recognition and medical diagnosis based on trigonometric similarity measures for bipolar complex fuzzy soft sets

2023

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Evaluating the feasibility of direct contact membrane distillation and nanofiltration in ground water treatment through a techno-economic analysis

Elboughdiri,

Cosma,

Amari

et al. 2024

Appl Water Sci

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This study delves into the realm of water treatment by conducting a comprehensive techno-economic evaluation of direct contact membrane distillation (DCMD) and nanofiltration (NF) processes. While previous research has explored the technical aspects of membrane distillation (MD) and nanofiltration, there remains a notable gap in economic analyses. Our research aims to bridge this gap by assessing the financial feasibility of employing MD and NF technologies for water desalination. Specifically, we scrutinize the performance of hydrophobic microporous flat sheet membranes crafted from polytetrafluoroethylene (PTFE) supported by non-woven polypropylene (PP) in desalinating brackish water through DCMD and NF processes. By varying operating conditions such as flow rate and feed temperature, we evaluate the membrane's efficacy. Employing an analytical model based on heat and mass transfer equations, we predict process performance across diverse scenarios. Our model demonstrates a high level of accuracy, with flux predictions deviating by less than 10% when utilizing the Knudsen-molecular mechanism model. Furthermore, through a detailed design and economic analysis of industrial-scale units for both processes, we reveal that the cost of permeated water is lower with NF compared to DCMD. Specifically, our calculations indicate a water cost of 1.34 USD/m3 for DCMD at a feed temperature of 65 °C with an 80% recovery rate, positioning it as a competitive option among conventional desalination methods. Notably, our financial assessment highlights that steam cost constitutes the primary expense in DCMD operations, contingent upon heating value and fuel prices. Noteworthy findings suggest that natural gas emerges as the most cost-effective fuel for steam production in a DCMD plant. This study underscores the economic viability and potential cost efficiencies associated with NF over DCMD in water treatment applications.

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Analysis of TOPSIS techniques based on bipolar complex fuzzy N‐soft setting and their applications in decision‐making problems

Cited by 8 publications

References 60 publications

N-bipolar hypersoft sets: Enhancing decision-making algorithms

N-bipolar hypersoft sets: Enhancing decision-making algorithms

Pattern recognition and medical diagnosis based on trigonometric similarity measures for bipolar complex fuzzy soft sets

Evaluating the feasibility of direct contact membrane distillation and nanofiltration in ground water treatment through a techno-economic analysis

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