ACADSTAFF UGM
| Title | : | Prediction of forest fire using ensemble method |
| Author | : |
Prof. Dr.rer.nat. Dedi Rosadi, S.Si., M.Sc. (1) WIDYASTUTI ANDRIYANI (2) |
| Date | : | 15 2021 |
| Keyword | : | AdaBoost, forest fire AdaBoost, forest fire |
| Abstract | : | In this paper we consider the application of ensemble classification method, which is called as the Adaptive Boosting (AdaBoost) method, to predict the occurrencesof forest fire. To illustrate the method, we consider the application of the method using the same public data set, which has been used in the previous studies, but the ensemble approach is not considered in these studies yet.We also compare the performance of the ensemble method with several other classical classification methods, such as the Decision tree and SVM method. All computation are done using open source software R. We find that in the empirical study, the hybrid algorithms between the fuzzy c-means clustering andthe ensemble approach will outperform the other classification methods considered in the study |
| Group of Knowledge | : | |
| Level | : | Internasional |
| Status | : |
Published
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