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基于SOFM神经网络的核心种质取样算法
引用本文:林喆,郑丽敏,李自超,张洪亮. 基于SOFM神经网络的核心种质取样算法[J]. 种子, 2006, 25(5): 4-8,16
作者姓名:林喆  郑丽敏  李自超  张洪亮
作者单位:1. 中国农业大学农学与生物技术学院,北京,100094
2. 中国农业大学信息与电气工程学院,北京,100094
摘    要:介绍了核心种质和自组织特征映射网络的基本概念,使用自组织特征映射网络的自组织特性对种质性状数据进行了聚类,利用聚类的分组结果,提取核心种质,通过对核心种质的各种参数的检验并与完全随机取样和一般的系统聚类的对比。结果表明,SOFM的取样算法,是一种比较有效快捷的算法,可以在实际中加以应用。

关 键 词:SOFM网络  聚类  核心种质
收稿时间:2006-02-16
修稿时间:2006-02-16

Sampling Method of the Core Germplasm Collection Based on SOFM Neural Network
Lin Zhe,Zheng Limin,Li Zichao,Zhang Hongliang. Sampling Method of the Core Germplasm Collection Based on SOFM Neural Network[J]. Seed, 2006, 25(5): 4-8,16
Authors:Lin Zhe  Zheng Limin  Li Zichao  Zhang Hongliang
Affiliation:1. College of Agronomy and Biotechnology, CAU Beijing, 100094 ; 2. College of Information and Electrical Engineering, CAU, Beijing, 100094
Abstract:In order to find a quick and easy Sampling Method of Core Germplasm Collection, we try a new Neural Network algorithm of Self-Organizing Feature Map. Using this method we cluster characteristic dates of germplasm resources to sample Core germplasm. The comparison average,variation,variation range and coefficient in three different core set of random sampling, system cluster method and SOFM showed that SOFM sampiing method is a effective and convenient method and can be used in germplasm work. Key words SOFM network Clustering Core Collection.
Keywords:SOFM network Clustering Core Collection.
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