生态学中MLP投入贡献分析的零模型验证

M. Watts, S. Worner
{"title":"生态学中MLP投入贡献分析的零模型验证","authors":"M. Watts, S. Worner","doi":"10.1109/HIS.2006.51","DOIUrl":null,"url":null,"abstract":"A method is presented for applying a null-model analysis to the verification of the significance of the input neurons of Multi-Layer Perceptrons (MLP). This method was applied to a problem from ecology, namely the establishment of invasive insect pest species. Previous work has described how the MLP were trained to predict species establishment from climate data, and to identify which climatic factors are significant. The null-model analysis method described here was used to validate these predictions.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Null-Model Validation of MLP Input Contribution Analysis in Ecology\",\"authors\":\"M. Watts, S. Worner\",\"doi\":\"10.1109/HIS.2006.51\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method is presented for applying a null-model analysis to the verification of the significance of the input neurons of Multi-Layer Perceptrons (MLP). This method was applied to a problem from ecology, namely the establishment of invasive insect pest species. Previous work has described how the MLP were trained to predict species establishment from climate data, and to identify which climatic factors are significant. The null-model analysis method described here was used to validate these predictions.\",\"PeriodicalId\":150732,\"journal\":{\"name\":\"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIS.2006.51\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIS.2006.51","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

提出了一种将零模型分析应用于多层感知器(MLP)输入神经元显著性验证的方法。该方法应用于生态学中的一个问题,即入侵害虫物种的确定。以前的工作描述了如何训练MLP从气候数据中预测物种的建立,并确定哪些气候因素是重要的。这里描述的零模型分析方法被用来验证这些预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Null-Model Validation of MLP Input Contribution Analysis in Ecology
A method is presented for applying a null-model analysis to the verification of the significance of the input neurons of Multi-Layer Perceptrons (MLP). This method was applied to a problem from ecology, namely the establishment of invasive insect pest species. Previous work has described how the MLP were trained to predict species establishment from climate data, and to identify which climatic factors are significant. The null-model analysis method described here was used to validate these predictions.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信