International Journal of Computer Applications

Foundation of Computer Science (FCS), NY, USA

Year of Publication: 2015

10.5120/ijca2015907398 |

Dima Alberg. Article: An Interval Tree Approach to Predict Forest Fires using Meteorological Data. *International Journal of Computer Applications* 132(4):17-22, December 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

@article{key:article, author = {Dima Alberg}, title = {Article: An Interval Tree Approach to Predict Forest Fires using Meteorological Data}, journal = {International Journal of Computer Applications}, year = {2015}, volume = {132}, number = {4}, pages = {17-22}, month = {December}, note = {Published by Foundation of Computer Science (FCS), NY, USA} }

Interval prediction can be more useful than single value prediction in many continuous data streams. This paper introduces a novel Interval Prediction Tree IP3 algorithm for interval prediction of numerical target variables from temporal mean-variance aggregated continuous data. This algorithm characterized by: processing incoming mean-variance aggregated multivariate temporal data, splitting each of the continuous features of the input according to the best mean-variance and making stable interval predictions of a target numerical variable with a given degree of statistical confidence. As shown by empirical evaluations in forest fires data set the proposed method provides better performance than existing regression tree models.

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Interval Prediction, Mean-Variance Aggregation, Prediction Tree, Forest Fires.