Chonghui Guo

Management Science and Operations Research · 2007–2017

A researcher in the Science corpus: 4 papers; trusts 18 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Chonghui Guo trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Francisco Herrera
  2. Luis Martínez-López
  3. Zeshui Xu
  4. Yucheng Dong
  5. Jin-Hsien Wang
  6. Chris Brooks
  7. Ivan Palomares
  8. Guiqing Zhang
  9. Xuan-hua Xu
  10. T. Warren Liao

Who trusts Chonghui Guo overall

  1. Wei Zhang

Papers from Chonghui Guo's perspective

Ordered by how strongly the researchers Chonghui Guo trusts endorse each paper. Same corpus, a different order for every researcher.

  1. A 2-tuple fuzzy linguistic representation model for computing with words (IEEE transactions on fuzzy systems)
  2. Computing the Numerical Scale of the Linguistic Term Set for the 2-Tuple Fuzzy Linguistic Representation Model (IEEE transactions on fuzzy systems)
  3. A model based on linguistic 2-tuples for dealing with multigranular hierarchical linguistic contexts in multi-expert decision-making (IEEE Trans. Syst. Man Cybern. Part B)
  4. A new version of 2-tuple fuzzy linguistic representation model for computing with words (IEEE transactions on fuzzy systems)
  5. Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment (Information Sciences)
  6. Consensus model for multi-criteria large-group emergency decision making considering non-cooperative behaviors and minority opinions (Decision Support Systems)
  7. Data Mining - Concepts and Techniques (Künstliche Intell.)
  8. A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets (Information Sciences)
  9. A fusion approach for managing multi-granularity linguistic term sets in decision making
  10. Consistency and consensus measures for linguistic preference relations based on distribution assessments (Information Fusion)

Their papers