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Issue 18, 2011
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Swarm intelligence metaheuristics for enhanced data analysis and optimization

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Abstract

The swarm intelligence (SI) computing paradigm has proven itself as a comprehensive means of solving complicated analytical chemistry problems by emulating biologically-inspired processes. As global optimum search metaheuristics, associated algorithms have been widely used in training neural networks, function optimization, prediction and classification, and in a variety of process-based analytical applications. The goal of this review is to provide readers with critical insight into the utility of swarm intelligence tools as methods for solving complex chemical problems. Consideration will be given to algorithm development, ease of implementation and model performance, detailing subsequent influences on a number of application areas in the analytical, bioanalytical and detection sciences.

Graphical abstract: Swarm intelligence metaheuristics for enhanced data analysis and optimization

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Publication details

The article was received on 01 May 2011, accepted on 19 Jul 2011 and first published on 05 Aug 2011


Article type: Critical Review
DOI: 10.1039/C1AN15369B
Citation: Analyst, 2011,136, 3587-3594
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    Swarm intelligence metaheuristics for enhanced data analysis and optimization

    G. Hanrahan, Analyst, 2011, 136, 3587
    DOI: 10.1039/C1AN15369B

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