中国高等学校学术文摘·林学2009,Vol.4Issue(3) :291-296.DOI:10.1007/s11461-009-0041-3

Ordination of self-organizing feature map neural networks and its application to the study of plant communities

Jintun ZHANG Dongping MENG Yuexiang XI
中国高等学校学术文摘·林学2009,Vol.4Issue(3) :291-296.DOI:10.1007/s11461-009-0041-3

Ordination of self-organizing feature map neural networks and its application to the study of plant communities

Jintun ZHANG 1Dongping MENG 2Yuexiang XI2
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作者信息

  • 1. College of Life Sciences, Beijing Normal University, Beijing 100875, China
  • 2. Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China
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Abstract

A self-organizing feature map (SOFM) neural network is a powerful tool in analyzing and solving complex, non-linear problems. According to its features, a SOFM is entirely compatible with ordination studies of plant communities. In our present work, mathematical principles, and ordination techniques and procedures are introduced. A SOFM ordination was applied to the study of plant communities in the middle of the Taihang mountains. The ordination was carried out by using the NNTool box in MATLAB. The results of 68 quadrats of plant communities were distributed in SOFM space. The ordination axes showed the ecological gradients clearly and provided the relationships between communities with ecological meaning. The results are consistent with the reality of vegetation in the study area. This suggests that SOFM ordination is an effective technique in plant ecology. During ordination procedures, it is easy to carry out clustering of communities and so it is beneficial for combining classification and ordination in vegetation studies.

Key words

self-organizing feature map/vegetation/quantitative methodology/gradient analysis/ordination/Taihang mountains

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基金项目

国家自然科学基金(30870399)

Teachers' Foundation of Ministry of Education in China()

出版年

2009
中国高等学校学术文摘·林学
高等教育出版社

中国高等学校学术文摘·林学

ISSN:1673-3517
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