Extension of multivariate regression trees to interval data. Application to electricity load profiling |
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Authors: | Véronique Cariou |
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Institution: | (1) EDF R&D, 1 av. du Général de Gaulle, 92140 Clamart, France;(2) ENITIAA, rue de la Géraudière, 44 322 Nantes Cedex 3, France |
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Abstract: | Summary Several data can be presented as interval curves where intervals reflect a within variability. In particular, this representation
is well adapted for load profiles, which depict the electricity consumption of a class of customers. Electricity load profiling
consists in assigning a daily load curve to a customer based on their characteristics such as energy requirement. Within the
load profiling scope, this paper investigates the extension of multivariate regression trees to the case of interval dependent
(or response) variables. The tree method aims at setting up simultaneously load profiles and their assignment rules based
on independent variables. The extension of multivariate regression trees to interval responses is detailed and a global approach
is defined. It consists in a first stage of a dimension reduction of the interval response variables. Thereafter, the extension
of the tree method is applied to the first principal interval components. Outputs are the classes of the interval curves where
each class is characterized both by an interval load profile (e.g. the class prototype) and an assignment rule based on the
independent variables. |
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Keywords: | Interval data Load profiling Multivariate regression trees Symbolic Data Analysis |
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