Search Results (3)

Multidimensional clustering of large-scale multi-view data is an important topic because it makes possible to combine a variety of manifestations of a complex information set. Nevertheless, comparing and selecting the most suitable deep clustering method is not an easy task, especially when several opposing criteria are applied. Multi-criteria decision-making (MCDM) techniques provide systematic approaches to making such judgments, although they are often limited in their ability to handle uncertainty, imprecise judgments, and interdependencies in practice. To solve these problems, this paper suggests a circular Fermatean fuzzy technique order preference by similarity to ideal solution (CFF-TOPSIS) method, which combines improved fuzzy modeling with MCDM to make the decision-making process accurate and sound. By exploiting the intrinsic symmetry of TOPSIS, where distances to positive and negative ideal solutions are treated symmetrically, the proposed model integrates five evaluation criteria for assessing clustering adequacy, including clustering accuracy, scalability, computational complexity, robustness, and interpretability, to critically evaluate five alternative clustering methods based on the input of three decision-makers. This measurement is performed efficiently by the CFF-TOPSIS method based on the uncertainty and subjective judgment contained within circular Fermatean fuzzy sets (CFFSs). The model is reliable and superior to existing models, as confirmed by sensitivity and comparative analyses. The suggested approach provides a systematic and flexible method for making decisions in complex big-data settings, while maintaining symmetry in the evaluation of alternatives and criteria. Full article

An Ethernet cable enables users to connect their electronic devices, such as smartphones, computers, routers, laptops, etc., to a network that permits them to utilize the internet. Additionally, it transfers broadband signals among connected devices. Wi-Fi is tremendously helpful with small, handheld gadgets, but if capacity is required, cable Ethernet connectivity cannot be surpassed. Ethernet connections typically work faster than Wi-Fi connections; they also tend to be more flexible, have fewer interruptions, can handle problems rapidly, and have a cleaner appearance. However, it becomes complicated to decide upon an appropriate Ethernet cable. The circular Fermatean fuzzy set (∘FF), an extension of the interval-valued Fermatean fuzzy set(IVFFS) for two dimensions, provides a comprehensive framework for decision-making under uncertainty, where the concept of symmetry plays a crucial role in ensuring the balanced and unbiased aggregation of criteria. The main objective of this investigation was to select one of the best Ethernet cables using multi-criteria decision-making (MCDM). We employed aggregation operators (AOs), such as Einstein averaging and geometric AO, to amalgamate cable choices based on predefined criteria within the ∘FF set environment. Our approach ranks Ethernet cable options by evaluating their proximity to the ideal choice using ∘FF cosine and ∘FF dice similarity measures to ∘FF Einstein-weighted averaging aggregation and geometric operators. The effectiveness and stability of our suggested method are guaranteed by performing visualization, comparison, and statistical analysis. Full article

With the growth of the worldwide population and depletion of natural resources, the sustainable development of food systems cannot be ignored. The demand for agri-food waste valorization practices like high-value compounds production has received widespread attention; however, numerous challenges still exist. The present study aims to identify those challenges of agri-food waste valorization and propose effective solutions based on smart technologies. Based on a systematic review of the literature, the study combs existing challenges of agri-food waste valorization and constructs a six-dimension conceptual model of agri-food waste valorization challenges. Moreover, the study integrates a Fermatean fuzzy set (FFS) with multi-criteria decision-making (MCDM) methods including stepwise weight assessment ratio analysis (SWARA), decision-making trial and evaluation laboratory-interpretative structural modeling method (DEMATEL-ISM), and quality function deployment (QFD) to evaluate the weights of each dimension, find causal interrelationships among the challenges and fundamental ones, and rank the potential smart solutions. Finally, the results indicate that the “Government” dimension is the severest challenge and point out five primary challenges in agri-food waste valorization. The most potential smart solution is the “Facilitating connectivity and information sharing between supply chain members (S8)”, which may help government and related practitioners manage agri-food waste efficiently and also facilitate circular economy. Full article