CAJ | 학술논문

现有感知数据传输模型存在能量消耗大、网络生存周期短、适用范围窄、收敛性弱以及实际应用性差的问题，为了实现大面积感知数据高效传输，提出了基于数据关联度的模糊自适应融合算法，建立了自适应网络模型。感知节点发送的数据经汇聚节点、中继节点转发时，通过自适应网络模型，根据感知数据关联度，动态修正输入参数加权系数从而改变控制规则，再用优化的控制规则进行参数调整，融合后的数据再传送到上一级平台，实验表明了该算法能明显改善海量感知数据传输性能。
현유감지수거전수모형존재능량소모대、망락생존주기단、괄용범위착、수렴성약이급실제응용성차적문제，위료실현대면적감지수거고효전수，제출료기우수거관련도적모호자괄응융합산법，건립료자괄응망락모형。감지절점발송적수거경회취절점、중계절점전발시，통과자괄응망락모형，근거감지수거관련도，동태수정수입삼수가권계수종이개변공제규칙，재용우화적공제규칙진행삼수조정，융합후적수거재전송도상일급평태，실험표명료해산법능명현개선해량감지수거전수성능。
According to the data transfer requirements,which focus on large energy consumption, short network life cycle,narrow scope range of application,weak convergence,as well as the poor practical applications .In order to achieve the widespread sensor data efficient transmission,the fuzzy adaptive fusion algorithm based on the data relevance is proposed,adaptive network model is established. Sensor node data is forward by gathering and relay node,by adaptive network model, according to sensor data relevance,input parameters weighting coefficient is changed dynamically and in doing so change control rules,finally achieved parameter adjustment by optimizing control rules, fused data is transferred to the higher platform. The experiment shows that the algorithm can greatly improve the performance of mass sensor data transmission.