3.8 Proceedings Paper

IMOptimizer: An Online Interactive Parameter Optimization System Based on Big Data

期刊

DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
卷 11448, 期 -, 页码 581-584

出版社

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-030-18590-9_91

关键词

-

资金

  1. NSFC [61472099, 61602129, U1509216, U1866602]
  2. National Key Research and Development Program of China [2016YFB1000703]

向作者/读者索取更多资源

Intelligent manufactory is a typical application of big data analysis. Flexible production line is an essential fundamental of intelligent manufactory. Producing different types of similar products alternately in one line with fixed stations but varying parameters is a typical kind of flexibility. In this case, the quality of products is directly determined by the parameter setting. However, the relation between parameters and product quality are too complicated to model. Consequently, current solution is bound to tune the parameters manually, which highly relies on expertise and is very costly. Inspired by recommender systems, we develop IMOptimizer, a novel online interactive processing parameter setting system. IMOptimizer holds the features of Configurable, Interactive, High Efficiency and Friendly UI. To the best of our knowledge, our system is the first big-data-driven generic platform focusing on online process optimization. In this demonstration, we will present our prototype.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

3.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据