7 resultados para Computational experiment
em Aberystwyth University Repository - Reino Unido
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Pritchard, L., Corne, D., Kell, D.B., Rowland, J. & Winson, M. (2005) A general model of error-prone PCR. Journal of Theoretical Biology 234, 497-509.
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Whelan, K. E. and King, R. D. (2004) Intelligent software for laboratory automation. Trends in Biotechnology 22 (9): 440-445
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King R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S., Kell, D. B. and Oliver, S. G. (2004) Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427 (6971) p247-252
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Sponsorship: EPSRC
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R. Zwiggelaar, '100 Jaar rontgen straling: wisselwerking tussen theorie, experiment en simulatie', Nederlands Tijdschrift voor Natuurkunde 61 (12), 207-209 (1995)
Resumo:
Computational Intelligence and Feature Selection provides a high level audience with both the background and fundamental ideas behind feature selection with an emphasis on those techniques based on rough and fuzzy sets, including their hybridizations. It introduces set theory, fuzzy set theory, rough set theory, and fuzzy-rough set theory, and illustrates the power and efficacy of the feature selections described through the use of real-world applications and worked examples. Program files implementing major algorithms covered, together with the necessary instructions and datasets, are available on the Web.
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Soldatova, L. N., Aubrey, W., King, R. D., Clare, A. J. (2008). The EXACT description of biomedical protocols. Bioinformatics, 24 (13), i295-i303 Sponsorship: BBSRC / RAEng / EPSRC specialissue: ISMB