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Alternative TitleA Study for Liquor Blending Intelligent Model
Thesis Advisor马增良
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword白酒勾调 线性规划 人工神经网络 专家系统 理化感观模型 Liquor Blending Linear Programming Artificial Neural Network Expert System Physic-chemical And Sensory Model
Abstract白酒生产是我国的传统产业,历史悠久,具有独特的传统工艺流程,但是这种工艺流程中由于主要以人工品尝的方法来进行勾兑调味,而口感具有个体差异,并受很多主客观因素影响,且理化指标根本不能通过品尝准确控制,因此明显存在白酒品质不稳定、难以控制指标、难以降低生产成本的致命弱点。并且人工品尝需要经过多次勾调尝试,生产效率低,专家的宝贵经验也无法形成知识长期为企业生产服务。 随着分析手段及科技水平的日益提高,白酒中许多微量香味成份的作用得到了充分认识,给探索勾兑酒的奥秘创造了重要条件。在对白酒中微量香味成份与酒香、酒味、风格的关系逐步有了较清楚的认识基础上,应用现代的计算机技术继承发展提高传统勾兑调味技术,无疑是对白酒技术水平的巨大推动。 本文在白酒勾调的智能模型上作了一些探索研究,构建了基于神经网络的理化->感观模型和感观->理化模型。首先通过线性规划给出成本最低的勾兑组合,然后把勾兑酒的理化指标输入理化->感观模型预测出感观指标,这相当于人工品尝勾兑的过程,将感观指标作为专家系统的输入,结合专家知识给出调味方案;也可以把期望的感观指标输入感观->理化模型预测出理化指标,通过线性规划给出满足目标酒并且成本最低的组合方案。
Other AbstractLiquor production is a traditional industry of china which has a long history and has a unique traditional process. But artificial taste is the main approach to liquor blending in the process. Taste varies from person to person, and is subject to many subjective and objective factors. Also physical and chemical indicators can not accurately controlled by taste, so the quality of liquor is instability, and it is difficult to reduce production costs. On the other hand, artificial taste need blending many attempts, so productivity is low. The valuable knowledge of experts can not form a long-term production which can service for the enterprise. With the improving of analytical tools and scientific and technology, the role of trace fragrance ingredients in liquor has been fully understood which creates an important condition for exploring the mysteries of liquor blending. On the basis of understanding of the relation between trace fragrance ingredients and the style of liquor, the application of modern computer technology to enhance the development of the traditional blending technology, is a undoubtedly driving force to promote the liquor technological level. In this paper, a number of studies are made to explore the intelligent model of liquor blending. A neural network model based on the relation between physic-chemical and sensory is built. First the lowest cost of blending is given through linear programming and then physic-chemical indicators are inputted into the model which predicts the sense indicators. This process is similar to blending through artificial taste. The sense indicators are given as an input into the expert system which produces the blending program. Also the sense indicators can be input into the model which produces the physic-chemical indicators, and then the combination program of lowest-cost is given through the linear programming.
Other Identifier200628014628026
Document Type学位论文
Recommended Citation
GB/T 7714
郑明宝. 白酒勾调智能模型的研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2009.
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