Extended PROMETHEE method with (p,q)-rung linear Diophantine fuzzy sets for robot selection problem.

The introduction of (p, q)-rung linear Diophantine fuzzy set into the field of fuzzy set theory is a significant advancement, providing a broader perspective to address complicated decision-making scenarios. Alongside, the preference ranking organization method for enrichment of evaluation (PROMETHEE) emerges as a widely recognized tool for tackling multi-criteria decision-making challenges. This study contributes theoretically to the decision-making field by integrating (p, q)-rung linear Diophantine fuzzy sets into the PROMETHEE framework, improving (p, q)-rung linear Diophantine fuzzy sets adaptability and efficiency in practical aspects, the proposed framework can effectively address various intricate decision-making challenges encountered in real-world scenarios.

Introducing a Novel multi-criteria Ranking of Alternatives with Weights of Criterion (RAWEC) model.

Optimal selection of agricultural distribution center location significantly impact the agricultural industry's growth and regional development, as they enhance product accessibility for customers and streamline delivery for suppliers. Research presented in this paper focuses on the selection of locations for the needs of an agricultural distribution center using a new method of multi-criteria decision making (MCDM), referred as the Ranking Alternatives with Weights of Criterion (RAWEC) method. On a real-world example, the Brčko District of Bosnia and Herzegovina was evaluated for potential sites for the formation of an agricultural distribution center.

An MCDM approach on Einstein aggregation operators under Bipolar Linear Diophantine Fuzzy Hypersoft Set.

The most extended form of a fuzzy set called the Bipolar Linear Diophantine Fuzzy Hypersoft Set is implemented with some basic operations. This is an extraordinary technique for handling uncertainty because it has a choice of reference parameters with auxiliary attributes. A widely used operator named Einstein aggregation operators was developed in our proposed context.

Treatment of cancer patients by generalizing a Fermatean normal vague set with aggregation operators.

Multi-attribute decision-making problems can be solved using a Fermatean vague set. Fermatean vague sets are extension of vague sets. We initiated generalized Fermatean vague weighted averaging, generalized Fermatean vague weighted geometric, power generalized Fermatean vague weighted averaging and power generalized Fermatean vague weighted geometric.

Enhancing decision-making with linear diophantine multi-fuzzy set: application of novel information measures in medical and engineering fields.

This study offers a comprehensive analysis of novel information for linear diophantine multi-fuzzy sets and illustrates its applications in practical scenarios. We introduce innovative similarity metrics tailored for linear diophantine multi-fuzzy sets, including Cosine similarity, Jaccard similarity, and Exponential similarity. Additionally, we propose Entropy, Inclusion, and Distance measures, providing a robust theoretical foundation supported by developed theorems that explain the interactions between these metrics.

Optimized deep learning networks for accurate identification of cancer cells in bone marrow.

Radiologists utilize pictures from X-rays, magnetic resonance imaging, or computed tomography scans to diagnose bone cancer. Manual methods are labor-intensive and may need specialized knowledge. As a result, creating an automated process for distinguishing between malignant and healthy bone is essential.

Technology adaptation in sugarcane supply chain based on a novel p, q Quasirung Orthopair Fuzzy decision making framework.

The present paper contributes to the literature in two ways. First, it develops a novel p, q Quasirung Orthopair Fuzzy (p, q QOF) based group decision making framework to modify a recently developed multi-criteria decision making (MCDM) model such as Comparisons between Ranked Criteria (COBRAC). Second, the paper ruminates on the Strength-Weakness-Opportunity-Threat (SWOT) of the sugarcane supply chain (SSC) in India vis-à-vis adaptation of the advanced technologies featuring Industry 4.

Application of the new simple weight calculation (SIWEC) method in the case study in the sales channels of agricultural products.

In this research is presented a new method for determining the weights of criteria called simple weight calculation (SIWEC) method. The steps of this method are presented in the practical example of determining the importance of criteria for the needs of sales of agricultural products in the Semberija region. During the presentation of this method two methods are elaborated the simple SIWEC method which includes numerical ratings and the fuzzy SIWEC method which includes ratings in the form of linguistic value.

Analysis of Hamacher power aggregation operators for circular complex p, q-quasirung orthopair fuzzy 2-tuple linguistic sets and their application in green industry development.

Green industry development focuses on balancing economic and financial growth with environmental stewardship and ensuring that companies and industries are contributing positively to both environmental sustainability and prosperity. This manuscript aims to develop the novel technique of circular complex p, q-quasirung orthopair fuzzy 2-tuple linguistic (CCp, q-QOF2-TL) set and their operational laws based on algebraic t-norms and Hamacher t-norms, where the algebraic t-norms and Einstein t-norms are the special cases of the Hamacher t-norms for parameter and . Further, we derive the Hamacher power aggregation operators based on any finite collection of CCp, q-QOF2-TL numbers (CCp, q-QOF2-TLNs), called CCp, q-QOF2-TL Hamacher power average (CCp, q-QOF2-TLHPA) operator, CCp, q-QOF2-TL Hamacher power weighted average (CCp, q-QOF2-TLHPWA) operator, CCp, q-QOF2-TL Hamacher power geometric (CCp, q-QOF2-TLHPG) operator, CCp, q-QOF2-TL Hamacher power weighted geometric (CCp, q-QOF2-TLHPWG) operator, and described their basic properties, called idempotency, monotonicity, and boundedness.

Analysis of coupling in geographic information systems based on WASPAS method for bipolar complex fuzzy linguistic Aczel-Alsina power aggregation operators.

The model of bipolar complex fuzzy linguistic set is a very famous and dominant principle to cope with vague and uncertain information. The bipolar complex fuzzy linguistic set contained the positive membership function, negative membership function, and linguistic variable, where the technique of fuzzy sets to bipolar fuzzy sets are the special cases of the bipolar complex fuzzy linguistic set. In this manuscript, we describe the model of Aczel-Alsina operational laws for bipolar complex fuzzy linguistic values based on Aczel-Alsina t-norm and Aczel-Alsina t-conorm.

A Novel Evaluation Framework for Medical LLMs: Combining Fuzzy Logic and MCDM for Medical Relation and Clinical Concept Extraction.

Artificial intelligence (AI) has become a crucial element of modern technology, especially in the healthcare sector, which is apparent given the continuous development of large language models (LLMs), which are utilized in various domains, including medical beings. However, when it comes to using these LLMs for the medical domain, there's a need for an evaluation platform to determine their suitability and drive future development efforts. Towards that end, this study aims to address this concern by developing a comprehensive Multi-Criteria Decision Making (MCDM) approach that is specifically designed to evaluate medical LLMs.

Various distance between generalized Diophantine fuzzy sets using multiple criteria decision making and their real life applications.

This paper describes a generalized Diophantine fuzzy sets, which can be seen as a generalization of both Diophantine fuzzy sets and Pythagorean fuzzy sets. We define the basic properties of generalized Diophantine fuzzy set, as well as their relationships and distances. We compare Diophantine fuzzy sets with other Diophantine Pythagorean fuzzy sets to demonstrate their importance in the literature.

Effective multi-attribute group decision-making approach to study astronomy in the probabilistic linguistic -rung orthopair fuzzy VIKOR framework.

This study employs a novel fuzzy logic-based framework to address multi-attribute group decision-making problems commonly encountered in modern astronomy. Our approach utilizes the probabilistic linguistic -rung orthopair fuzzy set (PL-ROFS) to handle the inherent uncertainties associated with astronomical data. The PL-ROFS offers significant advantages over existing fuzzy sets like probabilistic hesitant, linguistic intuitionistic, and linguistic Pythagorean fuzzy sets, which comprise both stochastic and non-stochastic uncertainties simultaneously.

A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.

The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biological factors. Similarly, the effects of vaccination on people's immunity vary across several factors. After the pandemic, real-life post-vaccination anomalies significantly impact women's health, access to medical treatments and medications, mental well-being, and daily physical activities.

Application of the full consistency method (FUCOM) - Cosine similarity framework in 5G infrastructure investment planning: An approach for telecommunication quality improvements.

In the rapidly evolving telecommunications landscape, the shift towards advanced communication technologies marks a critical milestone. This transition promises to revolutionize connectivity by enabling seamless data downloads, high-quality video streaming, and instant access to applications. However, adapting to these advanced technologies poses significant challenges for infrastructure expansion, requiring innovative investment and deployment strategies.

Applying hesitant q-rung orthopair fuzzy sets to evaluate uncertainty in subsidence causes factors.

Land subsidence is a widespread problem impacting communities worldwide. Understanding the causes and factors of land subsidence is crucial for identifying and prioritizing effective mitigation measures. One of the main reasons for prioritizing land subsidence causes is the potential impact on infrastructure and the environment.

Optimal selection of healthcare waste treatment devices using fuzzy-rough approach.

The escalating volume of healthcare waste (HCW) generated by healthcare facilities poses a pressing challenge for all nations. Adequate management and disposal of this waste are imperative to mitigate its adverse impact on human lives, wildlife, and the environment. Addressing this issue in Bosnia and Herzegovina involves the establishment of a regional center dedicated to HCW management.

Multi-attribute group decision-making based on Pythagorean fuzzy rough Aczel-Alsina aggregation operators and its applications to Medical diagnosis.

The fusion of information is a very hectic process whenever we analyze the information. Several frameworks have been introduced to reduce the uncertainty while fusing the information. Among those techniques, the Pythagorean fuzzy rough set (PyFRS), which is based on approximations is a key idea for dealing with uncertainty when data is taken from real-world circumstances.

Economic Order Quantity Model-Based Optimized Fuzzy Nonlinear Dynamic Mathematical Schemes.

Fuzzy mathematics-informed methods are beneficial in cases when observations display uncertainty and volatility since it is of vital importance to make predictions about the future considering the stages of interpreting, planning, and strategy building. It is possible to realize this aim through accurate, reliable, and realistic data and information analysis, emerging from past to present time. The principal expenditures are treated as fuzzy numbers in this article, which includes a blurry categorial prototype with pattern-diverse stipulation and collapse with salvation worth.

Solar PV power plant site selection using a GIS-based non-linear multi-criteria optimization technique.

The ongoing rise in energy consumption imposed serious environmental challenges by using fossil fuels. The use of renewable energy sources is being increasingly explored as a potential answer for achieving sustainable energy production and minimizing adverse environmental effects. In the modern day, photovoltaic (PV) systems are viewed as a possible replacement for fossil fuels as a clean energy source.

Selection of healthcare waste management treatment using fuzzy rough numbers and Aczel-Alsina Function.

The COVID-19 pandemic led to an increase in healthcare waste (HCW). HCW management treatment needs to be re-taken into focus to deal with this challenge. In practice, there are several treatments of HCW with their advantages and disadvantages.

A modified EDAS model for comparison of mobile wallet service providers in India.

The present paper has two-fold purposes. First, the current work provides an integrated theoretical framework to compare popular mobile wallet service providers based on users' views in the Indian context. To this end, we propose a new grey correlation-based Picture Fuzzy-Evaluation based on Distance from Average Solution (GCPF-EDAS) framework for the comparative analysis.

Can financial stress be anticipated and explained? Uncovering the hidden pattern using EEMD-LSTM, EEMD-prophet, and XAI methodologies.

Global financial stress is a critical variable that reflects the ongoing state of several key macroeconomic indicators and financial markets. Predictive analytics of financial stress, nevertheless, has seen very little focus in literature as of now. Futuristic movements of stress in markets can be anticipated if the same can be predicted with a satisfactory level of precision.

Evaluation of the route selection in international freight transportation by using the CODAS technique based on interval-valued Atanassov intuitionistic sets.

The selection of a proper international freight transport route is one of the crucial tasks for decision-makers since it can affect costs, efficiency, and transportation performance. Besides, the selection of suitable and appropriate freight routes can also reduce external costs of transportation such as emissions, noise, traffic congestions, accidents, and so on. Route selection in international transportation is a complicated decision-making problem as many conflicting factors and criteria affect the assessment process.