Open Access
Issue
BIO Web Conf.
Volume 8, 2017
2016 International Conference on Medicine Sciences and Bioengineering (ICMSB2016)
Article Number 01037
Number of page(s) 8
Section Session I: Medicine
DOI https://doi.org/10.1051/bioconf/20170801037
Published online 11 January 2017
  • Guilbert J J. The world health report 2002 - reducing risks, promoting healthy life.[J]. Education for Health, 2003, 16(16):230–230. [CrossRef] [Google Scholar]
  • Segal Daniel L. Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR)[M]// Diagnostic and statistical manual of mental disorders:. American Psychiatric Association, 2013:4189–4189. [Google Scholar]
  • Christmann C, Koeppe C, Braus D F, et al. A simultaneous EEG–fMRI study of painful electric stimulation[J]. Neuroimage, 2007, 34(4):1428–37. [CrossRef] [PubMed] [Google Scholar]
  • Hess E H. Attitude And Pupil Size.[J]. Scientific American, 1965, 212(4):46–54. [CrossRef] [PubMed] [Google Scholar]
  • Duque A, Vázquez C. Double attention bias for positive and negative emotional faces in clinical depression: Evidence from an eye-tracking study[J]. Journal of Behavior Therapy & Experimental Psychiatry, 2015, 46:107–14. [CrossRef] [Google Scholar]
  • Y.H. Shi, Eberhart R.C., Parameter selection in particle swarm optimization, in: Annual Conference on Evolutionary Programming, San Diego, 1998 [Google Scholar]
  • Higashi N, Iba H. Particle swarm optimization with mutation[C]//Swarm Intelligence Symposium, 2003. SIS’03. Proceedings of the 2003 IEEE. IEEE, 2003: 72–79. [Google Scholar]
  • Zhan D, Lu H, Hao W, et al. Improving particle swarm optimization: Using neighbor heuristic and Gaussian cloud learning[J]. Intelligent Data Analysis, 2016, 20(1): 167–182. [CrossRef] [Google Scholar]
  • Wang H., Li C., Liu Y., & Zeng S. (2007). A Hybrid Particle Swarm Algorithm with Cauchy Mutation. Swarm Intelligence Symposium, 2007. Sis (pp.356–360). [Google Scholar]
  • Zhang L, Tang Y, Hua C, et al. A new particle swarm optimization algorithm with adaptive inertia weight based on Bayesian techniques[J]. Applied Soft Computing, 2015, 28: 138–149. [CrossRef] [Google Scholar]
  • Brockmann D., & Sokolov I. M. (2002). Lévy flights in external force fields: from models to equations. Chemical Physics, 284(1), 409–421. [CrossRef] [Google Scholar]
  • Hakl H, Uğuz H. A novel particle swarm optimization algorithm with Levy flight[J]. Applied Soft Computing, 2014, 23(5):333–345. [CrossRef] [Google Scholar]
  • Wang H, Wang W, Wu Z. Particle swarm optimization with adaptive mutation for multimodal optimization[J]. Applied Mathematics & Computation, 2013, 221(9):296–305. [CrossRef] [Google Scholar]
  • Nishio T, Kushida J, Hara A, et al. Adaptive particle swarm optimization with multi-dimensional mutation[C] // 2015 IEEE 8th International Workshop on Computational Intelligence and Applications (IWCIA). IEEE, 2015: 131–136. [Google Scholar]
  • Andrews P. S. (2006, July). An investigation into mutation operators for particle swarm optimization. In 2006 IEEE International Conference on Evolutionary Computation (pp. 1044–1051). IEEE. [CrossRef] [Google Scholar]
  • Dong W, Kang L, Zhang W. Opposition-based particle swarm optimization with adaptive mutation strategy[J]. Soft Computing, 2016:1–10. [Google Scholar]
  • Ngo T T, Sadollah A, Kim J H. A cooperative particle swarm optimizer with stochastic movements for computationally expensive numerical optimization problems[J]. Journal of Computational Science, 2016, 13:68–82. [CrossRef] [Google Scholar]
  • Nim Tottenham, et al., The NimStim set of facial expressions: Judgments from untrained research participants. Psychiatry Research 168 (2009) 242–249. [CrossRef] [PubMed] [Google Scholar]
  • Lim W H, Isa N A M. Two-layer particle swarm optimization with intelligent division of labor[J]. Engineering Applications of Artificial Intelligence, 2013, 26(10): 2327–2348. [CrossRef] [Google Scholar]
  • Mandal S, Ghoshal S P, Kar R, et al. Design of optimal linear phase FIR high pass filter using craziness based particle swarm optimization technique[J]. Journal of King Saud University-Computer and Information Sciences, 2012, 24(1): 83–92. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.