APCA

Adaptive detection method of sensor failures based on APCA for the thermodynamic system in power plant

基于APCA的电站热力过程故障传感器自适应检测方法

Then the data were analyzed by the absolute principal component analysis ( APCA ) to evaluate principal components and the percent variance explained by them .

对获得的浓度数据进一步作绝对主成分分析（APCA），获取颗粒物的主要来源成分和它们所占的比值。

A new pattern recognizing method based on clustering analysis , APCA neural network and RBF neural network is put forward to diagnose and forecast the slab defect in successive casting product line . Abnormal data is effectively wiped off , parameters are selected .

提出了一种新的基于聚类分析、APCA及RBF神经网络的模式识别方法，用于连铸生产线板坯缺陷的诊断和预报，有效地剔除了样本中的异常数据，对样本参数进行了优选。