Analysis of Blast Furnace Data Based on Association Rules

Ze-kai CHENG, Qi ZHANG, Feng QIN, Li-qin ZHU

Abstract


In this paper, taking the blast furnace temperature data as the data source, using association rules in data mining. Firstly, the practical significance of temperature data analysis of blast furnace in a steel plant is introduced. Secondly, the theory of data mining and association rules is given, detailed description of the principle of Apriori algorithm. This paper selects the temperature data of B blast furnace in a steel plant in September 2015 as the research object. Association Rule Mining for temperature data of blast furnace in a steel plant, and the association results are analyzed.

Keywords


Blast furnace, Data mining, Association rules, Apriori algorithm


DOI
10.12783/dtetr/eeta2017/7764

Refbacks

  • There are currently no refbacks.