Shuihua Wang

Artificial Intelligence · 2011–2024

A researcher in the Science corpus: 8 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Shuihua Wang trusts overall

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

  1. Yudong Zhang
  2. James Kennedy
  3. Abdulhamit Subasi
  4. Hui Wang
  5. Katherine R. Gray
  6. Krishnanand N. Kaipa
  7. M. E. H. Pedersen
  8. Kemal Polat
  9. Claudia Plant
  10. Arcangelo Messina

Who trusts Shuihua Wang overall

  1. S. Suganyadevi
  2. Yudong Zhang
  3. Eid Emary
  4. Yuyang Zhou
  5. Ahmed Hussein
  6. V. Seethalakshmi
  7. Kamran Shaukat

Papers from Shuihua Wang's perspective

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

  1. Enhancing particle swarm optimization using generalized opposition-based learning (Information Sciences)
  2. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces
  3. Bare bones particle swarms (Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706))
  4. Detection of multiple source locations using a glowworm metaphor with applications to collective robotics (Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005.)
  5. Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders (Comput. Biol. Medicine)
  6. Feature Selection Based on Hybridization of Genetic Algorithm and Particle Swarm Optimization (IEEE Geoscience and Remote Sensing Letters)
  7. Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network (Biomedical Signal Processing and Control)
  8. Diversity enhanced particle swarm optimization with neighborhood search (Information Sciences)
  9. Refinements of damage detection methods based on wavelet analysis of dynamical shapes
  10. Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform (Applied Mathematics and Computation)

Their papers