CAJ | 학술논문

为解决温室大棚中多无线传感器监测数据融合精度低的问题，提出了一种改进型的分批估计自适应加权融合算法。算法首先对单个无线温度传感节点一段时间内所采集的数据根据容许函数阈值剔除误差较大的数据，然后对该温度传感器的数据进行分批估计得出该节点某一段时间内的最优估计值，以此得到该区域所有无线温度传感节点最优估计值后，依据权值最优分配原则对每组传感器数据进行组内自适应加权融合，从而计算得到该段时间内温室大棚的温度精确值。通过实验验证得出：相对于平均值法与传统的分批估计算法，本算法数据融合易于实现，融合值相对误差值更低，稳健性更好。
위해결온실대붕중다무선전감기감측수거융합정도저적문제，제출료일충개진형적분비고계자괄응가권융합산법。산법수선대단개무선온도전감절점일단시간내소채집적수거근거용허함수역치척제오차교대적수거，연후대해온도전감기적수거진행분비고계득출해절점모일단시간내적최우고계치，이차득도해구역소유무선온도전감절점최우고계치후，의거권치최우분배원칙대매조전감기수거진행조내자괄응가권융합，종이계산득도해단시간내온실대붕적온도정학치。통과실험험증득출：상대우평균치법여전통적분비고계산법，본산법수거융합역우실현，융합치상대오차치경저，은건성경호。
To solve multiple wireless sensor monitoring data fusion in greenhouses the problem of low precision ,this paper proposes a modified batch estimation adaptive weighted fusion algorithm. Firstly,the algorithm based on the allowable threshold function eliminate a large error data,which collected over by the wireless temperature sensor within a period of time,then,batch estimate these processed data to derive optimal estimation of the value of the node,after this optimal estimate of all wireless temperature sensor nodes in the region,according to the principle of optimal allocation of weights to adaptive weighted fusion Within the group,finally,the algorithm calculates over the period of time the greenhouse temperature exact values. Through the experiment shows:compared with batch estima?tion algorithm and the traditional method of average value,this algorithm is easy to realize data fusion,the fusion value relative error is lower,better robustness.