PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Using Qualitative Information to Predict Citizens’ Satisfaction
MARTA DOMINGO, NURIA AGELL, XAVIER PARRA, MÓNICA SÁNCHEZ and CECILIO ANGULO
AI Communications Volume 20, Number 1, pp. 59-66, 2007. ISSN 0921-7126

Abstract

In studies concerned with sustainability the underlying models are, in most cases, not strictly numerical since they depend on many conditions that can be regarded as qualitative. In this paper, a model to evaluate citizens’ satisfaction learnt from data collected from a survey is presented. The model, which involves the use of RBF neural networks, will provide local councillors with useful information, enabling them to evaluate trends and improve strategies focused on enhancing sustainability. In this paper a contribution describing a practical experience with a model-based system applied to a study commissioned by the town council of Vilanova i la Geltrú (Catalonia, Spain) is presented

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:3363
Deposited By:Cecilio Angulo
Deposited On:09 February 2008