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农业传感数据特征分析

发表时间:2016-02-15  浏览量:1766  下载量:722
全部作者: 刘峰
作者单位: 华中农业大学信息学院
摘 要: 针对农业传感数据的特征分析问题,首先,采用离散余弦变换(discrete cosine transformation,DCT)分别将不同类型的传感数据从时空域变换到DCT域,进而在DCT域中分析传感数据的特征。其次,通过计算不同类型传感数据间的相关系数,以描述不同感知对象间的相关性。结果表明,相对于时空域,同一类传感数据在DCT域中表现出了较为明显的相关性;同时,不同类型的传感数据之间也表现出了不同程度的相关性。因此,可利用同一种类传感数据内部的相关性及不同种类传感数据间的相关性设计缺失数据估计算法。
关 键 词: 农业工程;农业物联网;传感数据分析;离散余弦变换;相关系数
Title: Analysis of the characteristics of agricultural sensor data
Author: LIU Feng
Organization: College of Informatics, Huazhong Agricultural University
Abstract: To design the efficient missing sensor data estimation algorithms, in order to find out the characteristics of agricultural sensor data, firstly, different types of sensor data are respectively transformed from time-space domain to discrete cosine transformation (DCT) domian where the characteristics of these data are analyzed. Secondly, the relationships between different types of sensed object are described through calculating the correlation coefficients of different types of sensor data. The results show that the correlation of the same type of sensor data samples is more obvious in DCT domain than in time-space domain, and the strength of correlation between different types of sensor data is different. Consequently, the correlation of the same type of sensor data samples and the correlation between different types of sensor data can be used to design missing sensor data estimation algorithm.
Key words: agricultural engineering; agricultural internet of things; sensor data analysis; discrete cosine transformation; correlation coefficient
发表期数: 2016年2月第3期
引用格式: 刘峰. 农业传感数据特征分析[J]. 中国科技论文在线精品论文,2016,9(3):270-274.
 
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