Some Aggregation Operators of Credibility Interval Trapezoidal Fuzzy Neutrosophic Numbers and Their DecisionMaking Application of Landslide Control Design Schemes
Keywords:
Credibility interval trapezoidal fuzzy neutrosophic number, credibility interval trapezoidal fuzzy neutrosophic number weighted arithmetic averaging operator, credibility interval trapezoidal fuzzy neutrosophic number weighted geometric averaging operator, decision making, landslide control design schemeAbstract
As a generalization of trapezoidal fuzzy neutrosophic numbers (TFNNs), credibility
trapezoidal fuzzy neutrosophic numbers (C-TFNNs) can independently describe true, false, and
indeterminate membership degrees and their credibility levels in uncertain and inconsistent
scenarios. Since the true, false, and indeterminate membership degrees are closely related to their
credibility levels, C-TFNN can ensure the credibility of TFNN, which shows its clear merit.
However, C-TFNNs cannot expresses the interval membership degrees of the truth, falsity and
indeterminacy and the uncertain credibility levels, which are produced due to human cognitive
vagueness, incompleteness, and uncertainty. Furthermore, existing decision models of C-TFNNs
cannot perform such a DM issue with both ITFNNs and uncertain credibility levels, which reveals
a gap. To compensates for this gap. this paper extends C-TFNNs to credibility interval TFNNs (CITFNNs), which strengthens the expression capability of uncertain information. Then, the
operational laws and score function of C-ITFNNs are defined to solve the aggregation and sorting
issues of C-ITFNNs in decision-making (DM) problems. Subsequently, the C-ITFNN weighted
geometric averaging (C-ITFNNWGA) and C-ITFNN weighted arithmetic averaging (CITFNNWAA) operators are proposed in view of operational laws of C-ITFNNs. Furthermore, a
multi-attribute DM model is established in terms of the two aggregation operators and the score
function in the C-ITFNN circumstance. Finally, a DM case of landslide control design schemes is
used to reveal the applicability of the proposed DM model in the C-ITFNN scenario. By comparative
analysis, the main superiority of our new DM model is that it not only compensates for the gap of
existing DM models, but also is more reliable and versatile than existing DM models
Downloads
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.