Dynamic selection of environmental variables to improve the prediction of aphid phenology : a machine learning approach

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(1)This is a repository copy of Dynamic selection of environmental variables to improve the prediction of aphid phenology : a machine learning approach. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/127857/ Version: Accepted Version Article: Holloway, Paul, Kudenko, Daniel orcid.org/0000-0003-3359-3255 and James, Bell (2018) Dynamic selection of environmental variables to improve the prediction of aphid phenology : a machine learning approach. Ecological Indicators. pp. 512-521. ISSN 1470-160X https://doi.org/10.1016/j.ecolind.2017.10.032 Reuse This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can’t change the article in any way or use it commercially. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. eprints@whiterose.ac.uk https://eprints.whiterose.ac.uk/

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(17) P M P M P M P M R M R M R M S M S M T M T M T M T M T M U M W M A

(18) F F T B N ADD S A O NAO O P F C A C PCC T A S S U TSS C K AUC R S C

(19) F M F M M T T ADD T N A O NAO P

(20) F I R T P A D D C ADD C C N A PCC O NAO

(21) F A M FF NF T NF T FF T C F C C W B D C N W M T

(22) F I A A A AUC AUC A U C AUC T

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