Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An Algorithm for Privacy-Preserving Quantitative Association Rules Mining
DASC '06 Proceedings of the 2nd IEEE International Symposium on Dependable, Autonomic and Secure Computing
Time Series Data Mining Method Based on Lightly-Supported Boolean Association Rules
FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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We proposed a new data mining algorithm on finding the cyclical data sets in database based on basic ant colony algorithm and definition of cyclical data sets. The algorithm improved the movement mode of ants in ant colony algorithm; making it no longer a global optimization algorithm, but has a strong classification ability and memory capacity, and reduce the number of the search on data item sets. Compared with other cyclical data item sets mining algorithm, its efficiency has greatly improved, so the algorithm can actually be used for cyclical data item sets mining projects. By changing the number of colony's ants, the cyclical data item set search capabilities of the algorithm can be optimized, so as to further enhance the efficiency of the algorithm. In this paper, we apply the algorithm in the Electric Power Dispatching Automation System, to find the alarm cyclical data sets. We find that the algorithm has very good efficiency and it provides important data information for recurrence of incidents and retrospective of incidents of Electric Power Dispatching Automation System.