Improved Biogeography-Based Optimization approach to secondary protein prediction

  • Junsong Fan*
  • , Haibin Duan
  • , Guangming Xie
  • , Hong Shi
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, many bio-inspired computation algorithms have been proposed to solve constraint problems. Biogeography-Based Optimization (BBO) is one of these newly proposed optimization algorithms. As a new way to solve complicated optimization problems, BBO has a quick convergence. In this paper, we proposed an improved BBO for solving protein structure prediction problems. Comparative experiments with standard BBO and differential evolution algorithm (DE) are also conducted, and the results demonstrate this improved BBO approach performs better in solving these complicated protein prediction problems.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4223-4228
Number of pages6
ISBN (Electronic)9781479914845
DOIs
StatePublished - 3 Sep 2014
Event2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing, China
Duration: 6 Jul 201411 Jul 2014

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2014 International Joint Conference on Neural Networks, IJCNN 2014
Country/TerritoryChina
CityBeijing
Period6/07/1411/07/14

Keywords

  • Biogeography-Based Optimization
  • Protein Prediction
  • migration method

Fingerprint

Dive into the research topics of 'Improved Biogeography-Based Optimization approach to secondary protein prediction'. Together they form a unique fingerprint.

Cite this