Assessment of Near-Earth Asteroid Deflection Techniques via Spherical Fuzzy Sets

Abstract

Extensions of fuzzy sets to broader contexts constitute one of the leading areas of research in the context of problems in artificial intelligence. Their aim is to address decision-making problems in the real world whenever obtaining accurate and sufficient data is not a straightforward task. In this way, spherical fuzzy sets were recently introduced as a step beyond to modelize such problems more precisely on the basis of the human nature, thus expanding the space of membership levels, which are defined under imprecise circumstances. The main goal in this study is to apply the spherical fuzzy set version of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a well-established multicriteria decision-making approach, in the context of planetary defense. As of the extraction of knowledge from a group of experts in the field of near-Earth asteroids, they rated four deflection technologies of asteroids (kinetic impactor, ion beam deflection, enhanced gravity tractor, and laser ablation) that had been previously assessed by means of the classical theory of fuzzy series. This way, a comparative study was carried out whose most significant results are the kinetic impactor being the most suitable alternative and the spherical fuzzy set version of the TOPSIS approach behaves more sensitively than the TOPSIS procedure for triangular fuzzy sets with regard to the information provided by our group of experts.

Assessing farmers' perception to Agriculture 4.0 technologies: A new interval‐valued spherical fuzzy sets based approach

“…Ordinary fuzzy sets have been used many times to compare the results of the extensions of fuzzy sets. [118][119][120][121] At this point, one of the most frequently used fuzzy sets is triangular fuzzy sets. [118][119][120][121] TFNs are considered as the pillar of the fuzzy set.…”

“…[118][119][120][121] At this point, one of the most frequently used fuzzy sets is triangular fuzzy sets. [118][119][120][121] TFNs are considered as the pillar of the fuzzy set. 122 TFNs are intuitive and easy to use; it is also computationally simple and very useful in promoting representation and information processing in a fuzzy environment.…”

“…Apart from this, it has been seen that the MAIRCA method is usually used with triangular fuzzy sets, which are type 1 fuzzy sets, in problems involving uncertainty. Therefore, in our comparative analysis, triangular fuzzy sets are used because they are more accepted in the literature for comparison [118][119][120][121] and their reliability has been proven with many papers, 102,106,112,122 and also to demonstrate the advantages of using spherical fuzzy sets which is the extension of ordinary fuzzy sets. As a result of the calculations obtained by adopting the steps of the triangular fuzzy MAIRCA method, the total gap matrix is calculated as in Table 12.…”

A New Spherical Fuzzy LBWA-MULTIMOOSRAL Framework: Application in Evaluation of Leanness of MSMEs in India

“…SFS has garnered attention from the researchers for extensive use in solving various real-life issues like medical diagnosis problem using trigonometric similarity measures and Choquet integral-based SF operation [54]; 3D printer selection using interval valued SF-additive ratio assessment (ARAS) method [55]; waste disposal location selection using SF-REGIME approach [56]; insurance policy selection using SF bi-objective linear decision-making model [57]; SF-analytic hierarchy process for supplier selection [58]; process mining application with SF-AHP [59]; energy management using SF linear Diophantine fuzzy soft rough sets [60]; cosine similarity-based medical diagnosis [61]; advertisement strategy formulation with SF-TOPSIS method [62]; Earth science application with SF [63]; SF-based failure mode and effect analysis in marble manufacturing [64]; assessment of efficacies of Facebook ads using SF-VIKOR in a group decision-making setup [65]; present value analysis in wealth management [66]; agricultural management in Industry 4.0 using interval-valued SF [67]; hospital performance evaluation using interval-valued SF-AHP [68]; and fraud detection with interval-valued AHP-MULTIMOORA method [69], among others. We have found that though there is an increasing number of applications of SFS in variety of areas, there is scope for further extensions of existing MCDM algorithms.…”

Multiple criteria choice modeling using the grounds of T‐spherical fuzzy REGIME analysis

“…Specifically, Gündoğdu and Kahraman 26 raised a solving approach for ameliorating the limited configuration in picture fuzzy sets and then put forward a spherical fuzzy (SF) framework using the agency of much broader ranges of picture fuzzy sets 27 . That is, the sum of squares of four membership degrees behooves to be equal to 1 in the SF framework, which permits the decision maker to assign these grades within more considerable extents 24,28 . By introducing a positive integer exponent t , the notion of SF sets can be further extended to T‐spherical fuzzy (T‐SF) sets which allows the decision maker to assign more flexible grades of membership located at any position in the unit interval [0, 1].…”