Multi Criteria Decision Making Method Based on Simplified Neutrosophic Linguistic Information with Cloud Model is popular PDF and ePub book, written by Jian-Qiang Wang in 2024-09-20, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Multi Criteria Decision Making Method Based on Simplified Neutrosophic Linguistic Information with Cloud Model can be Read Online from any device for your convenience.

Multi Criteria Decision Making Method Based on Simplified Neutrosophic Linguistic Information with Cloud Model Book PDF Summary

This study introduces simplified neutrosophic linguistic numbers (SNLNs) to describe online consumer reviews in an appropriate manner. Considering the defects of studies on SNLNs in handling linguistic information, the cloud model is used to convert linguistic terms in SNLNs to three numerical characteristics. Then, a novel simplified neutrosophic cloud (SNC) concept is presented, and its operations and distance are defined. Next, a series of simplified neutrosophic cloud aggregation operators are investigated, including the simplified neutrosophic clouds Maclaurin symmetric mean (SNCMSM) operator, weighted SNCMSM operator, and generalized weighted SNCMSM operator. Subsequently, a multi-criteria decision-making (MCDM) model is constructed based on the proposed aggregation operators. Finally, a hotel selection problem is presented to verify the effectiveness and validity of our developed approach.

Detail Book of Multi Criteria Decision Making Method Based on Simplified Neutrosophic Linguistic Information with Cloud Model PDF

Multi Criteria Decision Making Method Based on Simplified Neutrosophic Linguistic Information with Cloud Model
  • Author : Jian-Qiang Wang
  • Release : 20 September 2024
  • Publisher : Infinite Study
  • ISBN : 978186723xxxx
  • Genre : Mathematics
  • Total Page : 27 pages
  • Language : English
  • PDF File Size : 19,5 Mb

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