Cluster validity and uncertainty assessment for self‐organizing map pest profile analysis-Reference-Cited by-同舟云学术

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Cluster validity and uncertainty assessment for self‐organizing map pest profile analysis

Published:2016-11-14 Issue:3 Volume:8 Page:349-357
ISSN:2041-210X
Container-title:Methods in Ecology and Evolution
language:en
Short-container-title:Methods Ecol Evol

Author:

Roigé Mariona¹,McGeoch Melodie A.²,Hui Cang³⁴,Worner Susan P.¹

Affiliation:

1. National Centre for Advanced Bio‐Protection Technologies Lincoln University PO Box 84 Canterbury 7647 New Zealand

2. School of Biological Sciences Monash University Clayton Vic. 3800 Australia

3. Centre for Invasion Biology Department of Mathematical Sciences Stellenbosch University Matieland 7602 South Africa

4. African Institute for Mathematical Sciences Muizenberg 7945 South Africa

Funder

European Commission

Australian Research Council

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.12669

Reference61 articles.

1. Managing and Mining Uncertain Data

2. Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist

3. Future research challenges for incorporation of uncertainty in environmental and ecological decision-making

4. The global spread of crop pests and pathogens

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1. Potential Global Invasion Risk of Scale Insect Pests Based on a Self-Organizing Map;Insects;2023-06-21

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3. Multi‐species hotspots detection using self‐organizing maps: Simulation and application to purse seine tuna fisheries management;Methods in Ecology and Evolution;2022-10-17

4. Country Compendium of the Global Register of Introduced and Invasive Species;Scientific Data;2022-07-09

5. Extracting Cluster-Level Uncertainty from K-Means Clustering—An Example of Analysis of Uncertainty Inherent to Valuation Methodologies for Multiple Construction Projects;Advances in Information Communication Technology and Computing;2022

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