Interestingness measures for data mining: A survey
ACM Computing Surveys (CSUR)
First approach toward on-line evolution of association rules with learning classifier systems
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
An empirical study on sea water quality prediction
Knowledge-Based Systems
Rough particle swarm optimization and its applications in data mining
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue (1143 - 1198) " Distributed Bioinspired Algorithms"; Guest editors: F. Fernández de Vega, E. Cantú-Paz
Expert Systems with Applications: An International Journal
Integrated Computer-Aided Engineering
Pattern recognition to forecast seismic time series
Expert Systems with Applications: An International Journal
A review on time series data mining
Engineering Applications of Artificial Intelligence
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Nowadays, much effort is being devoted to develop techniques that forecast natural disasters in order to take precautionary measures. In this paper, the extraction of quantitative association rules and regression techniques are used to discover patterns which model the behavior of seismic temporal data to help in earthquakes prediction. Thus, a simple method based on the k-smallest and k-greatest values is introduced for mining rules that attempt at explaining the conditions under which an earthquake may happen. On the other hand patterns are discovered by using a tree-based piecewise linear model. Results from seismic temporal data provided by the Spanish's Geographical Institute are presented and discussed, showing a remarkable performance and the significance of the obtained results.