基于介质温度数值分布规律的冰盖厚度检测分析方法  

The Detection and Analysis of Ice Thickness Based on Numerical Distribution of Medium Temperature

作　　者：杨涛[1,2] 智静[3] 秦建敏[1,2] 邓霄[2] 侯煜[4] 

机构地区：[1]太原理工大学新型传感器与智能控制教育部与山西省重点实验室,山西太原030024 [2]太原理工大学物电学院,山西太原030024 [3]国网山西省电力公司物资分公司,山西太原030001 [4]中国水利水电科学研究院,北京100038

出　　处：《数学的实践与认识》2016年第13期118-124,共7页Mathematics in Practice and Theory

基　　金：国家自然科学基金(51279122);水利部公益性行业专项经费项目(201501025);国家自然科学基金(51205273);中俄国际合作项目(51511130042);山西省青年基金项目(2015021097)

摘　　要：针对水文预报领域冰层厚度检测过程中对空气与冰层、冰层与冰下水层的分界点难以判断的难题,提出了一种基于介质温度数值分布规律的冰层厚度检测分析方法.新方法在对空气与冰层、冰层与冰下水层的分界点进行分析判断时采用了聚类分析思想,通过采用改进属性归类规则的K-means算法,对采集到的空气、冰与水不同介质的温度数值分布数据进行分类,并对各自属性的温度梯度分布数据集合进行线性拟合,从各拟合曲线交点可以获得空气与冰层、冰层与冰下水层的分界点,进而计算出冰层厚度数值.采用这一方法对2014.12-2015.3内蒙包头黄河河道冰情采集数据进行分析,证明了新方法的可行性.For the process of detecting ice thickness in hydrological forecasting file, there is a problem that is difficult to determine the demarcation among air and ice, ice and water layer. We propose a method for detection and analysis based on ice thickness distribution of the medium temperature. The new approach uses cluster thinking in the analysis and judgment of ice thickness based on numerical distribution of medium temperature. Through the use of improved property classification rules of K-means algorithm, we classified the data collections of temperate in different mediums of air, water, ice; meanwhile we fit the linear regression of respective in temperature gradient distribution of Data collection. Form the Point of intersection of each fitting curve, we obtain the demarcation points among air and ice, ice and water layer. And then calculate ice thickness values. By using this method for the Yellow River in Inner Mongolia Baotou 2014.12-2015.3 ice conditions to collect data for analysis proved feasibility of the new method.

关 键 词：冰层厚度 温度 线性拟合 K-MEANS算法 

分 类 号：P332.8[天文地球—水文科学]