The Design and Implementation of KDD System for Industrial Flow Object
Ming Cai1, Jing Cai2, Shouning Qu3
1Ming Cai, School of Information Science and Engineering, University of Jinan, Jinan, China.
2Jing Cai, School of Information Science and Engineering, University of Jinan, Jinan, China.
3Shouning Qu, The Center of Information and Network, University of Jinan, Jinan, China.
Manuscript received on january 17, 2012. | Revised Manuscript received on February 05, 2012. | Manuscript published on February 29, 2012. | PP: 131-136 | Volume-1 Issue-3, February 2012. | Retrieval Number: C0208021312/2011©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: KDD is an important research and application area. This paper is aimed at the application of flow object’s association rules extraction and object modeling in the cement industry. We adopt the improved Apriori algorithm and the flexible neural tree model of the structure optimization algorithm, designing and implementing the KDD system for industrial flow object by J2EE. The whole system is mainly divided into two functions: one function module is association rules extraction, the other one is object modeling, and the original data were collected from the decomposing furnace production link, which is one of the most important processes of the cement industry.
Keywords: Association Rule, Flow Object, J2EE, KDD, Object Modeling.