摘要
投影寻踪是一种降维处理技术,它可以将高维分析问题通过投影方向转化为低维问题分析。应用该法的关键在于寻求最佳投影方向,这可以转化为一个复杂的非线性优化问题,结合Matlab的遗传算法工具箱进行优化求解。本文以淮南新庄孜煤矿为例,建立突水水源判别投影寻踪模型,并与模糊综合评判模型、神经网络模型、灰色聚类模型进行分析比较。结果表明:投影寻踪判别模型能够有效地判别突水水源,比模糊综合评判、神经网络模型、灰色聚类模型具有更高的准确性,为矿井突水水源判别提供了一个新途径。
Projection pursuit is a dimension-reduced data treatment method. Multi-dimensional question can be converted into low-dimension question according to projection direction. The key of using this method is to search the best projection direction, which can be solved by transforming a nonlinear optimization question, combined with Matlab genetic algorithm toolbox for the optimal solution. In this paper, Xinzhuangzi Mine was taken as an example, establishing projection pursuit model to discriminate water-inrush source, compared with fuzzy comprehensive evaluation, artificial neural network and gray clustering model. The result indicated that projection pursuit discrimination model has higher discrimination accuracy than fuzzy comprehensive evaluation, artificial neural network and gray clustering model, which provides a new way to discriminate water-inrush source.
出处
《地质论评》
CAS
CSCD
北大核心
2012年第6期1175-1179,共5页
Geological Review
基金
国家自然科学基金资助项目(批准号40872166
51179042)
合肥工业大学创新群体计划项目(2009HGCX0233)的成果
关键词
遗传算法
投影寻踪模型
新庄孜煤矿
突水水源
genetic algorithm
projection pursuit model
Xinzhuangzi coal mine
water-inrush source
