Mining fuzzy generalized association rules from quantitative data under fuzzy taxonomic structures

We try to explore category and association rules of customer questions by applying customer analysis and the combination of data mining and rough set theory.. We use customer

Secondly then propose a Fuzzy ISM method to taking account the Fuzzy linguistic consideration to fit in with real complicated situation, and then compare difference of the order of

According to the related researches the methods to mine association rules, they need too much time to implement their algorithms; therefore, this thesis proposes an efficient

(1999), "Mining Association Rules with Multiple Minimum Supports," Proceedings of ACMSIGKDD International Conference on Knowledge Discovery and Data Mining, San Diego,

This research is to integrate PID type fuzzy controller with the Dynamic Sliding Mode Control (DSMC) to make the system more robust to the dead-band as well as the hysteresis

In order to improve the aforementioned problems, this research proposes a conceptual cost estimation method that integrates a neuro-fuzzy system with the Principal Items

In each window, the best cluster number of each technical indicator is derived through Fuzzy c-means, so as to calculate the coincidence rate and determine number of trading days

It applied Data Mining technology about clustering and association rules to figure out optimal short-turn service route and optimal express service route, with the objective to