Abstract
As we all know, the Bonferroni mean (BM) operator has the advantage of considering interrelationships between parameters. In this paper, we combine the generalized weighted BM (GWBM) operator and generalized weighted Bonferroni geometric mean (GWGBM) operator with interval neutrosophic numbers (INNs) to develop the generalized interval neutrosophic number weight BM (GINNWBM) operator and generalized interval neutrosophic numbers weighted GBM (GINNWGBM) operator which consider the relationship among three aggregated arguments, then the MADM methods are developed with these operators. Finally, we use an example for evaluating the technological innovation capability for the high-tech enterprises to illustrate the proposed methods.
Highlights
Neutrosophic sets (NSs), which were proposed originally by Smarandache [1], [2], have been attracted the attention of many scholars, and NSs have been acted as a workspace in depicting indeterminate and inconsistent information
Thereafter, we extend generalized geometric Bonferroni mean (GGBM) to INNS and introduce the generalized interval neutrosophic numbers geometric Bonferroni mean (GINNGBM) operator
The generalized interval neutrosophic number weight BM (GINNWBM) and GINNWGBM operators consider the relationship among three aggregated arguments
Summary
Neutrosophic sets (NSs), which were proposed originally by Smarandache [1], [2], have been attracted the attention of many scholars, and NSs have been acted as a workspace in depicting indeterminate and inconsistent information. Zhang et al [14] defined some interval neutrosophic information aggregating operators. Peng et al [16] developed simplified neutrosophic information aggregation operators. Zhang et al [22] gave the improved weighted correlation coefficient for interval neutrosophic sets. Wei and Wei [27] proposed some single-valued neutrosophic dombi prioritized weighted aggregation operators in MADM. Zhang et al [22] defined the improved weighted correlation coefficient of INNs for MADM. How to effectively expand the traditional generalized weighted BM (GWBM) operator and generalized weighted Bonferroni geometric mean (GWGBM) operator to INN environment is a significant research task which the focus of this paper The organization of this manuscript is given as follows.
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