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气相色谱发展中主要趋势之一是研制具有人工智能的色谱仪。这类的气相色谱仪显然不仅能自动选择分析操作条件,并且还有可进行色谱峰的定性。这就需要大量的可供定性用和操作条件选择用的色谱保留值数据。应当指出,在微处理机中直接大量地储存这些保留值数据是不方便的,甚至可以说是不可能的。因此,聪明的办法是在色谱保留值理论的引导下,寻求适宜的方法,以便可以精确地预测各组分在不同固定相上的保留指数。我们以此为鹄的,进
One of the major trends in the development of gas chromatography is to develop a chromatograph with artificial intelligence. This type of gas chromatograph apparently can not only automatically select the analysis of operating conditions, but also qualitative peaks can be carried out. This requires a large amount of chromatographic retention data that can be used to select qualitative and operating conditions. It should be pointed out that it is inconvenient or even impossible to store these retention data directly in the microprocessor. Therefore, it is clever to find a suitable method under the guidance of chromatographic retention theory so that the retention index of each component on different stationary phases can be accurately predicted. We take this as a shame, into