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The 2012 FUZZ-IEEE conference competition “Learning Fuzzy Systems from Data” aims to establish the empirical accuracy of fuzzy forecasting algorithms in the domain of prediction of the sales volume of petroleum products. Currently, there are no guidelines or consensus on a best practice methodology. This paper proposes evolving fuzzy linear regression trees (eFT) to extract from both, daily prices...
This paper introduces an approach to evolve fuzzy modeling that simultaneously performs adaptive feature selection. The model is a fuzzy linear regression tree whose topology can be continuously updated using statistical tests. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The number of tree nodes and the number of inputs can be updated for each new input. The precision...
This paper introduces a new approach for evolving fuzzy modeling based on a tree structure. The system is a fuzzy linear regression tree whose topology can be continuously updated using a statistical model selection test. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The evolving linear regression approach is evaluated on a forecasting problem and its performance compared...
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