Analysis of Blast Furnace Data Based on Association Rules

Ann Based Prediction of Blast Furnace Parameters

Blast Furnace Analysis with Neural Networks

Nowadays blast furnace operation is supervised by extensive measurements and controlled accordingly. Characteristic indications concerning process quality are given by the analysis of the radial temperature profile in the upper part of the furnace. Optimising this temperature distribution would lead to considerable savings of input material. To achieve an optimisation, quantitative relations be...

Java-based Integrating Simulator for Blast Furnace

The method of integrating many partial simulators for a complicated system in the consideration of interaction is proposed. Java Native Interface is used to integrate the simulators programmed in different languages. Remote Method Invocation is used to integrate the simulators in different computer environment. By applying the method to the partial simulators on the blast furnace, java-based in...

Medical Data Mining Based on Association Rules

Detailed elaborations are presented for the idea on two-step frequent itemsets Apriori algorithm of Association Rules. An improved method called Improved Apriori algorithm is brought forward owing to the disadvantages of Apriori algorithm. Moreover, based on Improved Apriori algorithm, data mining for breast-cancers is carried out for the relationship between breast-cancer recurrences and other...

A new approach based on data envelopment analysis with double frontiers for ranking the discovered rules from data mining

Data envelopment analysis (DEA) is a relatively new data oriented approach to evaluate performance of a set of peer entities called decision-making units (DMUs) that convert multiple inputs into multiple outputs. Within a relative limited period, DEA has been converted into a strong quantitative and analytical tool to measure and evaluate performance. In an article written by Toloo et al. (2009...