Bibhas Chandra Giri

Management Information Systems · 2001–2018

A researcher in the Science corpus: 6 papers; trusts 10 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

Whom Bibhas Chandra Giri trusts overall

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

  1. Jun Ye
  2. Chen-Tung Chen
  3. Jianmai Shi
  4. Pinaki Majumdar
  5. Serafim Opricovic
  6. Geraldo Ferrer
  7. Florentin Smarandache

Who trusts Bibhas Chandra Giri overall

  1. Biswajit Sarkar
  2. Chung-Yuan Dye
  3. Hui-Ling Yang
  4. Renzo Akkerman
  5. Ata Allah Taleizadeh
  6. Jinn-Tsair Teng
  7. Chun-Tao Chang
  8. Liang-Yuh Ouyang

Papers from Bibhas Chandra Giri's perspective

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

  1. Improved cosine similarity measures of simplified neutrosophic sets for medical diagnoses (Artif. Intell. Medicine)
  2. On similarity and entropy of neutrosophic sets (Journal of Intelligent & Fuzzy Systems)
  3. Intuitionistic fuzzy information - Applications to pattern recognition (Pattern Recognition Letters)
  4. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS (European Journal of Operational Research)
  5. Extensions of the TOPSIS for group decision-making under fuzzy environment (Fuzzy Sets Syst.)
  6. A geometric interpretation of the neutrosophic set — A generalization of the intuitionistic fuzzy set (IEEE International Conference on Granular Computing)
  7. A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets (Journal of Intelligent & Fuzzy Systems)
  8. Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean (Neural computing & applications (Print))
  9. Fuzzy Multiple Attribute Decision Making - Methods and Applications
  10. A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method (Expert systems with applications)

Their papers