Mining data from simulation of beer production

Data mining is a methodology for the extraction of knowledge from data, especially, knowledge relating to a problem that we want to solve. Data mining from simulation outputs is performed in this paper, it focuses on techniques for extracting knowledge from simulation outputs for beer production and...

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Bibliographic Details
Main Authors: Yanbing Ju, Aihua Wang, Fengchun Zhu, Chuanliang Xia
Format: Conference Proceeding
Language:English
Subjects:
Analytical models
Clustering algorithms
Data mining
Delta modulation
Educational technology
Machine learning algorithms
Manufacturing systems
Production systems
Technology management
Testing
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Summary:Data mining is a methodology for the extraction of knowledge from data, especially, knowledge relating to a problem that we want to solve. Data mining from simulation outputs is performed in this paper, it focuses on techniques for extracting knowledge from simulation outputs for beer production and optimizing devices and labors with certain target. We first set up one simulation model for beer production process and construct optimization objective. Then we set up one data mining model based on witness miner. The mining results show that the model is able to fund important information affecting target, make manager diagnose the bottlenecks of the beer production process, and help manager to make decisions rapidly under uncertainty.
DOI:10.1109/NLPKE.2005.1598705