Current developments and future directions of bio-inspired computation and implications for ecoinformatics

Xin YAO, Yong LIU, Jin LI, Jun HE, Colin FRAYN

Research output: Journal PublicationsJournal Article (refereed)peer-review

15 Citations (Scopus)


Evolutionary and neural computation has been used widely in solving various problems in biological ecosystems. This paper reviews some of the recent work in evolutionary computation and neural network ensembles that could be explored further in the context of ecoinformatics. Although these bio-inspired techniques were not developed specifically for ecoinformatics, their successes in solving complex problems in other fields demonstrate how these techniques could be adapted and used for tackling difficult problems in ecoinformatics. Firstly, we will review our work in modelling and model calibration, which is an important topic in ecoinformatics. Secondly one example will be given to illustrate how coevolutionary algorithms could be used in problem-solving. Thirdly, we will describe our work on neural network ensembles, which can be used for various classification and prediction problems in ecoinformatics. Finally, we will discuss ecosystem-inspired computational models and algorithms that could be explored as directions of future research. © 2005 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)9-22
Number of pages14
JournalEcological Informatics
Issue number1
Early online date24 Nov 2005
Publication statusPublished - Jan 2006
Externally publishedYes


  • Evolutionary algorithms
  • Evolutionary computation
  • Evolutionary neural networks
  • Genetic algorithms
  • Global optimisation
  • Neural network ensembles


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