Twenty-five years ago, the International Institute of Forecasters was established “to bridge the gap between theory and practice.” Its primary vehicle was the Journal of Forecasting and is now the International Journal of Forecasting. The Institute emphasizes empirical comparisons of reasonable forecasting approaches. Such studies can be used to identify the best forecasting procedures to use u...

This research conducts an error analysis between the forecasting value and the actual value of steel demand of 2010 in China, which is based on the analysis of forecasting methods and their results of Chinese steel demand in the existing studies, and then forecasts China’s steel demand in 2015 by making use of a combined forecasting method. The combined forecasting method includes two stages. I...

The increasing availability of large amounts of historical data and the need of performing accurate forecasting of future behavior in several scientific and applied domains demands the definition of robust and efficient techniques able to infer from observations the stochastic dependency between past and future. The forecasting domain has been influenced, from the 1960s on, by linear statistica...

Many studies have demonstrated that combining forecasts improves accuracy relative to individual forecasts. In this paper, the combing forecasts is used to improve on individual forecasts is investigated. A combining approach based on the modified Group Method Data Handling (GMDH) method and genetic algorithm (GA), is called as the GAGMDH model is proposed. Four time series forecasting techniqu...

It is shown how the closure condition for the set of kinetic equations in Zubarev's Nonequilibrium Statistical Operator Method introduces a series of uxes of a reference set of densities. These uxes are the average values, over a Gibbs-like nonequilibrium generalized grandcanonical ensemble, of Hermitian operators for uxes de ned at the microscopic-mechanical level. The equations of evolution f...

applications of supervised and unsupervised ensemble methods What to say and what to do when mostly your friends love reading? Are you the one that don't have such hobby? So, it's important for you to start having that hobby. You know, reading is not the force. We're sure that reading will lead you to join in better concept of life. Reading will be a positive activity to do every time. And do y...

The method of defensive forecasting is applied to the problem of prediction with expert advice for binary outcomes. It turns out that defensive forecasting is not only competitive with the Aggregating Algorithm but also handles the case of “second-guessing” experts, whose advice depends on the learner’s prediction; this paper assumes that the dependence on the learner’s prediction is continuous.

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...