中文摘要：

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.

英文摘要：

To solve the limitations of data extraction algorithm ODLRST of unitary linear regression analysis for the wireless sensor network,improve efficiency of data compression and expand the scope of application of linear data compression,a improved temporal and spatial data compression algorithm TSDCACI based on confidence interval was proposed,introducing prediction and statistical evaluation of the probability of confidence interval and considering the expected changes and abnormal changes respectively to correct abnormal data status compression model in the linear regression analysis method.Simulation results show that the proposed algorithm is better than ODLRST,and not only able to guarantee higher compression ratio,but also to transport volatile test data,reduce energy consumption and prolong the network＇s life cycle.It is more in line with the actual situation local of data compression of small-scale sensor nodes and expand the scope of application.