摘要
针对采集设备在获取空间多维数据时往往是离散的,受设备故障、环境等因素的影响,空间多维数据会出现遗漏或异常问题,提出了基于Lagrange插值算法的空间多维数据校准模型。首先,建立星型和雪花型的空间多维数据库结构,明确数据分布特征。然后,预处理初始数据,经过参数初始化操作,实现数据维数一致性划分,提高数据质量。再通过信息熵蚁群聚类、优化合并等过程完成数据分类,将具有相同特征的数据聚集到同一簇中,减少离群点。最后,利用基函数确立Lagrange插值多项式,引入归一化思想,确保数值在一定区间内浮动,避免龙格现象,生成新的插值多项式,多项式计算结果即为校准的数据值。实验结果表明,该方法具有较好的数据预处理能力,能有效减少校准误差。
When collecting spatial multidimensional data,collection devices are often discrete,and due to equipment failures,environmental factors,and other factors,there may be omissions or anomalies in spatial multidimensional data,a spatial multidimensional data calibration model based on the Lagrange interpolation algorithm is proposed.Firstly,Star shaped and snowflake shaped spatial multidimensional database structure is established to clarify the data distribution characteristics.Then,the initial data is preprocessed,and the consistent division of data dimension is realized through parameter initialization operation,so as to improve the data quality.Then the data classification is completed through the processes of information entropy ant colony clustering,optimization and merging.And the data with the same characteristics are gathered into the same cluster to reduce outliers.Finally,the Lagrange interpolation polynomial is established by using the basis function.And the normalization idea is introduced to ensure that the value floats in a certain range,avoid Runge phenomenon,and generate a new interpolation polynomial.The polynomial calculation result is the calibrated data value.The experimental results show that this method has good data preprocessing ability and can effectively reduce the calibration error.
作者
高晓娟
GAO Xiaojuan(Faculty of Electronic Information and Computer Engineering,Sichuan Institute of Industrial Technology,Deyang 618500,China)
出处
《吉林大学学报（信息科学版）》
CAS
2023年第4期746-751,共6页
Journal of Jilin University（Information Science Edition）
基金
四川省院校合作基金资助项目(2021JZ0081)。
关键词
Lagrange插值算法
空间多维数据
校准模型
信息熵蚁群算法
归一化思想
lagrange interpolation algorithm
spatial multidimensional data
calibration model
information entropy ant colony algorithm
normalization thought
