CAJ | 학술논문

针对压力传感器在应用中存在温度漂移这一缺点，提出了一种基于蚁群聚类算法的RBF( Radial Basis Function)神经网络温度补偿方法。利用蚁群算法的并行寻优特征和一种自适应调整挥发系数的方法作为聚类算法来确定RBF神经网络的基函数的位置，并通过裁减的方法约简隐层的神经元达到简化网络结构的目的。通过仿真可以看出，该算法具有误差小，精度高等优点，对压力传感器的温度漂移有较好的补偿效果。
침대압력전감기재응용중존재온도표이저일결점，제출료일충기우의군취류산법적RBF( Radial Basis Function)신경망락온도보상방법。이용의군산법적병행심우특정화일충자괄응조정휘발계수적방법작위취류산법래학정RBF신경망락적기함수적위치，병통과재감적방법약간은층적신경원체도간화망락결구적목적。통과방진가이간출，해산법구유오차소，정도고등우점，대압력전감기적온도표이유교호적보상효과。
Aiming at the drawback of temperature drift of the pressure sensor,a temperature compensation method of RBF Neural Networks based on ant colony clustering is proposed. Based on the feature of parallel search optimum of the ant colony algorithm and a dynamic method to adjust the parameter of evaporation coefficient,the center of each basis function of RBF can be defined by using a new proposed clustering algorithm;in order to simplify the structure of RBF network, we use a pruning method to remove those hidden units. The simulation results showed that the method has the features of small error,high precision and a good compensation effect for the pressure sensor’s tem-perature drift.