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人工神经网络已被广泛应用于气体传感器阵列的模式识别研究中。该文利用混沌遗传人工神经网络算法(CGANN)对压电TSM晶体传感器阵列数据进行模式识别。数据处理结果表明,该方法能准确的对压电TSM传感器阵列数据中对应不同气体物质如乙醇,氯仿及丙酮等样本进行分类识别。
Artificial neural network has been widely used in the pattern recognition of gas sensor array. In this paper, chaos genetic artificial neural network algorithm (CGANN) is applied to pattern recognition of piezoelectric TSM crystal sensor array data. The data processing results show that the proposed method can accurately classify the corresponding samples with different gas substances such as ethanol, chloroform and acetone in the piezoelectric TSM sensor array data.