RÉSUMÉ. La caractérisation est une tâche supervisée de fouille de données qui permet de résumer de manière succincte et concise un ensemble de données. Cette tâche est intéressante dans la mesure où elle ne nécessite pas de contre exemples. Nous proposons un cadre général pour la caractérisation d’un ensemble d’objets, appelé ensemble ’cible’, en nous basant non seulement sur leurs propriétés p...

The diversity of an ensemble can be calculated in a variety of ways. Here a diversity metric and a means for altering the diversity of an ensemble, called “thinning”, are introduced. We experiment with thinning algorithms evaluated on ensembles created by several techniques on 22 publicly available datasets. When compared to other methods, our percentage correct diversity measure algorithm show...

The existing techniques of forecasting a future count either treat the time series of counts as a Gaussian time series or use a random effects based dynamic Poisson model. The normality based approach may not yield valid forecasting, whereas the random effects based model usually generates a complex correlation structure for the time series of counts which may be impractical to use for forecast...

Accurate electricity price forecasting plays an important role in the profits of electricity market participants and the healthy development of electricity market. However, the electricity price time series hold the characteristics of volatility and randomness, which make it quite hard to forecast electricity price accurately. In this paper, a novel hybrid model for electricity price forecastin...

Hantaviral diseases have been recognized as ‘place diseases’ from their earliest identification and, epidemiologically, are tied to single host species with transmission occurring infectious hosts humans. As such, human populations most at risk when they in physical proximity suitable habitats for reservoir populations, numbers of greatest. Because the lags between improving habitat conditions ...

This paper describes three software applications for distribution network load forecasting in a Smart Grid environment: (i) short-term feeder load forecasting, (ii) shortterm substation transformer load forecasting and transformer rating, and (iii) next-year load pocket forecasting. The shortterm feeder load forecasting allows a utility to reduce the possibility of feeder overloading. The subst...

It has been deemed as an effective tool of forecasting performance improvement to combine different component forecasting models. However, current nonlinear combining models are not able to meet the requirement of high forecasting accuracy in practice. To tackle this challenge, this paper constructs a hybrid, named genetic programming and least squared estimation based nonlinear combining metho...

The field of ecology has changed to a data-rich enterprise, largely due to rapid development of measurement sensors and long-term accumulation of data from research networks. With implementation of the National Ecological Observatory Network (NEON), a network with different kinds of sensors and measurements at many locations over the United States, large volumes of ecological data will be gener...

The CMIP3 multi-model ensemble has been widely utilised for climate research and prediction, but the properties and behavior of the ensemble are not yet fully understood. Here we present some investigations into various aspects of the ensemble’s behaviour, in particular focussing on the performance of the multi-model mean. We present an explanation of this phenomenon in the context of the stati...