An Extended MULTIMOORA Based on Trapezoidal Fuzzy Neutrosophic Sets and Objective Weighting Method in Group Decision-Making

Abstract

Multi-objective optimization based on ratio analysis plus full multiplicative form (MUL-TIMOORA) is an efficient decision-making method for solving multi-criteria group decision-making (MCGDM) processes. It uses three strategies to examine different alternatives and to determine their evaluation values. These strategies include ratio system approach (RSA), reference point approach (RPA), and full multiplicative form (FMF). However, this method presents some challenges in the examination model, such as the ability to aggregate and determine the final result according to these strategies without considering value differences, the complexity of calculating the aggregation and multi-time comparisons, and the probability of distinguishing circular reasoning rules in dominance theory. In addition, determining an appropriate instrument for handling uncertainty, inconsistency, and incompleteness of information and a suitable weight for each criterion and decision-maker for reducing human interventions are also considered and will be a complex MCGDM process. To overcome these weaknesses, we propose an extended MULTI-MOORA based on trapezoidal fuzzy neutrosophic numbers (TraFNNs) for MCGDM. We integrated it with ordinal priority approach (OPA) method to decide the initial weights for decision-makers and criteria without human subjective assessment. In addition, we used correlation coefficient and standard deviation (CCSD) technique to statistically compute the relationship between these strategies in resolving unique weights to obtain realistic results and eliminate the above issues. Finally, sensitivity and comparative analyses demonstrate the capability and effectivity of the extended method.INDEX TERMS Correlation coefficient and standard deviation method, multi-criteria group decisionmaking, MULTIMOORA method, trapezoidal fuzzy neutrosophic number.

Applying Artificial Neural Network Based on Backpropagation Method for Indonesian Sign Language Recognition

“…Therefore, ISL sign language recognition still has much room for improvement and future studies, such as recognition based on sign language words or an application for real-time recognition. In addition, improving weights in backpropagation iterations can be effectively constructed using decision-making methods such as an integrated objective weighting [38], a hybrid bipolar neutrosophic-EDAS approach [39], and improved trapezoidal fuzzy neutrosophic sets [40][41] [42].…”