基于BP神经网络和遗传算法的催化剂离心喷雾干燥工艺参数优化

Yunfei Liu, Jingjing Xu, Tianyang Ye
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引用次数: 0

摘要

催化剂离心喷雾干燥中合理有效的工艺参数对催化剂的质量和工业生产具有重要意义。以细粉比和水分蒸发的总体理想为目标,基于遗传算法的BP神经网络优化工艺参数,获得较好的干燥性能。优化结果为催化剂离心喷雾干燥的工业生产工艺参数的设定和催化剂产品质量的提高提供了依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameters Optimization for Catalyst Centrifugal Spray Drying Process Based on BP Neural Network and Genetic Algorithm
Reasonable and effective process parameters in the catalyst centrifugal spray drying are of significance for the quality and industrial production of the catalyst. The overall desirability of fine powder ratio and water evaporation is defined as the goal and the process parameters are optimized based on BP neural network with genetic algorithm, which obtains the better drying performance. The optimization results provide a basis for setting the process parameters of the industrial production of catalyst centrifugal spray drying and improve the quality of the catalyst product.
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