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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Application of multifractal wavelet analysis to spontaneous fermentation processes
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Application of multifractal wavelet analysis to spontaneous fermentation processes

机译:多重分形小波分析在自然发酵过程中的应用

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An algorithm is presented here to get more detailed information, of mixed-culture type, based exclusively on the biomass concentration data for fermentation processes. The analysis is performed with only the on-line measurements of the redox potential being available. It is a two-step procedure which includes an Artificial Neural Network (ANN) that relates the redox potential to the biomass concentrations in the first step. Next, a multifractal wavelet analysis is performed using the biomass estimates of the process. In this context, our results show that the redox potential is a valuable indicator of microorganism metabolic activity during the spontaneous fermentation. In this paper, the detailed design of the multifractal wavelet analysis is presented, as well as its direct experimental application at the laboratory level. (C) 2008 Elsevier B.V. All rights reserved.
机译:此处仅基于发酵过程中的生物量浓度数据,提出了一种算法,以获取混合培养类型的更多详细信息。仅使用氧化还原电势的在线测量进行分析。这是一个分为两个步骤的过程,其中包括一个人工神经网络(ANN),该过程将氧化还原电势与第一步中的生物质浓度相关联。接下来,使用该过程的生物量估计执行多重分形小波分析。在这种情况下,我们的结果表明,氧化还原电位是自发发酵过程中微生物代谢活性的重要指标。本文介绍了多重分形小波分析的详细设计及其在实验室水平的直接实验应用。 (C)2008 Elsevier B.V.保留所有权利。

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