Wenbo Xu

Artificial Intelligence · Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) · 2004–2012

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

Subfields

Whom Wenbo Xu trusts overall

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

  1. James Kennedy
  2. Frans van den Bergh
  3. R. Eberhart
  4. Jun Sun
  5. Andries Petrus Engelbrecht
  6. Visakan Kadirkamanathan
  7. Xin Yao
  8. Asanga Ratnaweera
  9. Shang He
  10. Yuhui Shi

Who trusts Wenbo Xu overall

  1. Leandro dos S. Coelho
  2. Konstantinos E. Parsopoulos
  3. Jun Sun
  4. Hao Gao
  5. Ajit Kumar Rout
  6. Viviana Cocco Mariani
  7. Ahmed Ali Abdalla Esmin
  8. Yue-jiao Gong

Papers from Wenbo Xu's perspective

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

  1. Comparing inertia weights and constriction factors in particle swarm optimization (Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512))
  2. A new optimizer using particle swarm theory
  3. The particle swarm optimization algorithm: convergence analysis and parameter selection (Information Processing Letters)
  4. An analysis of particle swarm optimizers
  5. Stereotyping: improving particle swarm performance with cluster analysis (Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512))
  6. Optimization by Simulated Annealing
  7. Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization
  8. The fully informed particle swarm: simpler, maybe better (IEEE Transactions on Evolutionary Computation)
  9. A Cooperative approach to particle swarm optimization (IEEE Transactions on Evolutionary Computation)
  10. Stability analysis of social foraging swarms (IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics))

Their papers