2 resultados para multi-scale

em Université de Lausanne, Switzerland


Relevância:

100.00% 100.00%

Publicador:

Resumo:

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Relevância:

30.00% 30.00%

Publicador:

Resumo:

This study presents the validation of a French version of the Career Adapt-Abilities Scale in four Francophone countries. The aim was to re-analyze the item selection and then compare this newly developed French-language form with the international form 2.0. Exploratory factor analysis was used as a tool for item selection, and confirmatory factor analysis (CFA) verified the structure of the CAAS French-language form. Measurement equivalence across the four countries was tested using multi-group CFA. Adults and adolescents (N=1,707) participated from Switzerland, Belgium, Luxembourg, and France. Items chosen for the final version of the CAAS French-language form are different to those in the CAAS international form 2.0 and provide an improvement in terms of reliability. The factor structure is replicable across country, age, and gender. Strong evidence for metric invariance and partial evidence for scalar invariance of the CAAS French-language form across countries is given. The CAAS French-language and CAAS international form 2.0 can be used in a combined form of 31 items. The CAAS French-language form will certainly be interesting for practitioners using interventions based on the life design paradigm or aiming at increasing career adapt-ability.