矿化带圈定的自组织特征映射网算法研究及应用

矿化带圈定的自组织特征映射网算法研究及应用

陈铎¹, 李颖¹, 李艳文²

1. 吉林大学计算机科学与技术学院, 长春 130021; 2. 东北师范大学计算机学院, 长春 130117

收稿日期:2006-06-05 修回日期:1900-01-01 出版日期:2006-08-26 发布日期:2006-11-26
通讯作者: 陈铎

Arithmetic of Self\|organizing Feature Map for Partition of Mineralized Belt and Its Application

CHEN Duo¹, LI Ying¹, LI Yan wen²

1. College of Computer Science and Technology, Jilin University, Changchun 130021, China; 2. School of Computer Science, Northeast Normal University, Changchun 130117, China

Received:2006-06-05 Revised:1900-01-01 Online:2006-08-26 Published:2006-11-26
Contact: CHEN Duo

摘要/Abstract

摘要： 为实现复杂地质信息的非线性整合处理, 对地质勘探资料进行综合分析与分类, 采用自组织特征映射网, 解决了地学数据的多来源、表达方式复杂、间接性、多解性、非线性和传统矿化带圈定的人工分类的不确定性等问题, 效果明显, 分类结果与地质事实基本吻合, 该方法能够弥补人工分类的不足, 为矿化带的圈定提供准确可靠的依据. 

关键词: 矿化带, 伴生元素, SOM网络

Abstract: Geography data are multi-sources, complex expression, indirect character, multi-solution, non-linear and got-up sort of original mineralized belt is uncertainty. To solve the problems above mentioned, the Self-Organizing Feature Map was used to execute the non-linear conformity of the complex geography information, then analyze and sort the geography exploration materials were analyzed and classified. This method is effective; the result of classification conforms to the geography fact. Then it fetches up the deficiency of the got-up sort and also provides trustiness bases for the partition of the mineralized belt. 

Key words: mineralized belt, associated element, SOM network

中图分类号:

TP391.77

陈铎, 李颖, 李艳文. 矿化带圈定的自组织特征映射网算法研究及应用[J]. J4, 2006, 44(06): 217-220.

CHEN Duo, LI Ying, LI Yan wen. Arithmetic of Self\|organizing Feature Map for Partition of Mineralized Belt and Its Application[J]. J4, 2006, 44(06): 217-220.