摘要
针对无线传感器网络容易受噪音干扰的问题,在以往的工作基础上提出了一种新的业务流预测算法CAWP(Cellular Annealing-based Wavelet Prediction).该算法首先利用小波变换对业务流进行分解,并将其小波系数作为抗体群.同时,采用定义的元胞演化规则代替免疫克隆退火中的交叉和变异操作,以获得下一时刻最优的小波系数.最后,通过仿真实验对比分析了该算法与其他算法之间的性能状况,结果表明CAWP具有较好的适应性.
In order to mitigate the interference problem by noise in wireless sensor network, a novel traffic prediction algorithm CAWP (Cellular Annealing-based Wavelet Prediction) is proposed. In this algorithm, traffic is decomposed by wavelet transform, which wavelet coefficients are seen as antibody group. Then, the crossover and mutation operation are replaced with cellular evolution rules, and the optimal wavelet transform in the next moment is got. Finally, a simulation was conducted to study the performance in those algorithms. The results show that CAWP has good suitability.
出处
《微电子学与计算机》
CSCD
北大核心
2013年第10期21-24,共4页
Microelectronics & Computer
基金
国家自然科学基金项目(61001013,61272382)
广东省科技计划项目(2012B010100037)
广东省自然科学基金项目(10252500002000001,S2012010009963)
关键词
无线传感器网络
预测
小波
元胞
退火
wireless sensor network
predictiom wavelet
cellular
annealing