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The study of gas sensor array signal processing with new genetic algorithms

机译:遗传算法在气体传感器阵列信号处理中的研究

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In the field of gas sensor array signal processing, one of the most important and the most difficult procedures is the identification of the feature parameters (FP). Then we can use the optimum FP to distinguish different odours sensitively. Currently, however, there is no acceptable method for extracting the optimum FP. Therefore, a new method called organization feature parameter based on formulae expression tree by using genetic algorithms has been proposed in this paper. It could solve the problem how to getting optimum FP, and make the genetic algorithm more convenient and straight. The formulae expression tree for the fusion of feature parameters has been discussed and then the selection, crossover and mutation for the genetic algorithm were studied in depth. In order to prove the advantage of the method, some experiments adopting the new method have been carried out to recognize vinegar odours by using gas sensor array. The result demonstrated that the new method is a very useful and effective method for pattern recognition.
机译:在气体传感器阵列信号处理领域,最重要也是最困难的过程之一就是特征参数(FP)的识别。然后,我们可以使用最佳FP敏感地区分不同的气味。但是,目前,尚无用于提取最佳FP的可接受方法。因此,本文提出了一种新的基于遗传算法的基于公式表达式树的组织特征参数的方法。它可以解决如何获得最优FP的问题,并使遗传算法更加方便直接。讨论了特征参数融合的公式表达式树,然后深入研究了遗传算法的选择,交叉和变异。为了证明该方法的优点,已经进行了一些采用新方法的实验,通过使用气体传感器阵列来识别醋味。结果表明,该新方法是一种非常有用和有效的模式识别方法。

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