As a generalization of simple correspondence analysis, multiple correspondence analysis
(MCA) is a powerful technique for handling larger, more complex datasets, including the …

In this paper, we present an application of Artificial Neural Networks (ANNs) in the
renewable energy domain. We particularly look at the Multi-Layer Perceptron (MLP) network …

Considering the grid manager′ s point of view, needs in terms of prediction of intermittent
energy like the photovoltaic resource can be distinguished according to the considered …

This paper presents an application of Artificial Neural Networks (ANNs) to predict daily solar
radiation. We look at the Multi-Layer Perceptron (MLP) network which is the most used of …

En la pasada década hemos asistido a la irrupción de un nuevo concepto en el mundo
empresarial: el data mining (minería de datos). Algunas empresas han implementado …

Quantification of categorical, or non-numerical, data is a problem that scientists face across
a wide range of disciplines. Exploring data analysis in various areas of research, such as the …

Ce fascicule est dédié à la Régression Logistique. Il s' agit d'une technique de modélisation
qui, dans sa version la plus répandue, vise à prédire et expliquer les valeurs d'une variable …

The renewable energies prediction and particularly global radiation forecasting is a
challenge studied by a growing number of research teams. This paper proposes an original …

The purpose of this paper is to identify the drivers of eco-innovation in start-ups. Firstly, a
discriminant analysis (DA) is applied to study what is distinctive about eco-innovative start …

In this paper, we present an application of neural networks in the renewable energy domain.
We have developed a methodology for the daily prediction of global solar radiation on a …