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首页> 外文期刊>Journal of the Institute of Brewing >Optimization of Operating Conditions in Rice Heat Blast Process for Chinese Rice Wine Production by Combinational Utilization of Neural Network and Genetic Algorithms
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Optimization of Operating Conditions in Rice Heat Blast Process for Chinese Rice Wine Production by Combinational Utilization of Neural Network and Genetic Algorithms

机译：利用神经网络和遗传算法的结合优化我国黄酒生产中的稻瘟病热操作条件。

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摘要

The rice heat blast process is a novel technique for gelatinizing raw starch. It uses heated air to replace steam for processing rice under high temperature fluidization in a short time period. This is a new technique for making rice wine with the characteristics of easy storage and zero water pollution. This study focused on three major performance indexes (starch gelatinization ratio, total fat content, and amino nitrogen content in the roasted rice), which largely affect the performance of the rice heat blast process and the rice wine quality. The relationship between these performance indexes and the corresponding operation variables were modeled by an artificial neural network (ANN) via learning sets of experimental data. Based on the ANN models obtained, genetic algorithms were used to optimize the operating conditions of the rice heat blast process. The results showed the power in determination of optimal operating conditions by the combinational utilization of artificial neural network and genetic algorithms.
机译：大米热风工艺是一种用于糊化生淀粉的新技术。它使用热空气代替蒸汽在短时间内在高温流化条件下处理大米。这是一种生产米酒的新技术，具有易于保存和零水污染的特点。这项研究的重点是三个主要性能指标（淀粉糊化率，总脂肪含量和烤米中的氨基氮含量），它们在很大程度上影响了稻米热风过程的性能和米酒的质量。这些性能指标与相应的操作变量之间的关系通过人工神经网络（ANN）通过学习实验数据集进行建模。基于获得的ANN模型，使用遗传算法优化水稻热风过程的运行条件。结果表明，通过结合人工神经网络和遗传算法，可以确定最佳运行条件。

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