A Hybrid Forward Algorithm for RBF Neural Network Construction

This paper proposes a novel hybrid forward algorithm (HFA) for the construction of radial basis function (RBF) neural networks with tunable nodes. The main objective is to efficiently and effectively produce a parsimonious RBF neural network that generalizes well. In this study, it is achieved through simultaneous network structure determination and parameter optimization on the continuous parameter space. This is a mixed integer hard problem and the proposed HFA tackles this problem using an integrated analytic framework, leading to significantly improved network performance and reduced memory usage for the network construction. The computational complexity analysis confirms the efficiency of the proposed algorithm, and the simulation results demonstrate its effectiveness

Places making: participatory construction of scientifi c culture cities

In the framework of the European project Platform of Local Authorities and Communicators Engaged in Science (PLACES), we analyse the articulations between scientifi c communication, public perception of science, processes of citizen participation and apropiation of space, based on a case study of the inhabitants of Teruel city, Autonomous Community of Aragon, Spain. On the interrelationships between these issues, there are a number of contradictions, such as the difference between a high interest for information about science and technology and a low level of recognition and interaction with local institutions involved in those activities, the complex conceptualization of scientifi c space in relation to the “public-private” pair, or an articulation of a claiming civic rethoric and an insuffi cient co-responsibility. We conclude that, in a local context, the dimension of territoriality and, in particular, the identifi cation with the town, is a central mediation for activating citizen participation as part of processes of appropriation of space for setting up cities of scientifi c culture.