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为解决无线传感器网络一元线性回归模型的空时数据压缩算法ODLRST的局限性问题,提高有效数据压缩率,扩大线性数据压缩应用范围,提出了一种基于置信区间的ODLRST改进的时空数据压缩算法TSDCACI:引入置信区间概率预测与统计评估,分别考虑预期变化和异常变化,采用断点判定与野点判定修正线性回归方法中出现异常数据状况的压缩模型,.仿真实验和分析表明了所提出的TSDCACI算法优于传统的ODLRST,不仅能够保障较高的压缩率,而且可以传输波动较大的检测数据,减少节点能量消耗,延长网络生命周期,更符合局部小规模传感器节点数据压缩的实际情况,从而进一步扩大算法应用范围.
In order to solve the limitation of space-time data compression algorithm ODLRST in wireless sensor network (WSN), improve the effective data compression rate and extend the range of linear data compression, an improved space-time data compression algorithm based on confidence interval (ODLRST) TSDCACI : The introduction of confidence interval probability prediction and statistical evaluation, respectively, the expected changes and changes in anomalies, the use of breakpoint decision and wild-point decision to amend the linear regression method of abnormal data compression conditions, the simulation results show that the proposed TSDCACI algorithm Compared with the traditional ODLRST, not only the higher compression ratio can be guaranteed, but also the more fluctuating detection data can be transmitted, the energy consumption of nodes can be reduced, the network lifetime can be prolonged, and the data compression of local small-scale sensor nodes can be more in line with the actual situation of data compression. Expand the application of the algorithm.