Uniqueness of static decompositions

We classify static manifolds which admit more than one static decomposition whenever a condition on the curvature is fullfilled. For this, we take a standard static vector field and analyze its associated one parameter family of projections onto the base. We show that the base itself is a static manifold and the warping function satisfies severe restrictions, leading us to our classification results. Moreover, we show that certain condition on the lightlike sectional curvature ensures the uniqueness of static decomposition for Lorentzian manifolds.Comment: 14 page

Studying the capacity of cellular encoding to generate feedforward neural network topologies

Proceeding of: IEEE International Joint Conference on Neural Networks, IJCNN 2004, Budapest, 25-29 July 2004Many methods to codify artificial neural networks have been developed to avoid the disadvantages of direct encoding schema, improving the search into the solution's space. A method to analyse how the search space is covered and how are the movements along search process applying genetic operators is needed in order to evaluate the different encoding strategies for multilayer perceptrons (MLP). In this paper, the generative capacity, this is how the search space is covered for a indirect scheme based on cellular systems, is studied. The capacity of the methods to cover the search space (topologies of MLP space) is compared with the direct encoding scheme.Publicad

Decomposing generalized transport costs using index numbers: A geographical analysis of economic and infrastructure fundamentals

We use the economic theory approach to index numbers in order to improve the existing definitions and decompositions of generalized transport costs (GTCs), and thus to obtain a better understanding of their economic and infrastructure determinants. Using this approach we accurately measure the contribution made to reducing GTCs by the variation in operating costs and accessibility variables, and discuss to what extent transportation policy has been successful in reducing GTCs in terms of market competition and infrastructure investments. To implement the optimizing behaviour of transportation firms when choosing minimum cost itineraries, we compile a new economic database on road freight transportation at a highly detailed provincial level, which is then embedded into a GIS to show the digitalized road networks corresponding to five-year intervals between 1980 and 2007. Average GTCs weighted by trade flows have decreased by -16.3% in Spain, with infrastructure policy leading the way in providing notable accessibility improvements in terms of lower times and distances. The contribution of infrastructure is double that of economic cost, whose trends are mainly driven by technological and market determinants rather than by specific competition and regulatory policies promoted by the administrations. We find large territorial disparities in GTC levels and variations, but also significant clusters where the market and network effects on GTC reduction show relevant and diverse degrees of spatial association. We finally conclude that after three decades of active transportation policy aimed mainly at intensifying investment in road infrastructure, there has been a significant increase in territorial cohesion in terms of GTCs and their components.Generalized transport costs; Index number theory; Infrastructure; GIS; Territorial cohesion.

Generative capacities of cellular automata codification for evolution of NN codification

Proceeding of: International Conference on Artificial Neural Networks. ICANN 2002, Madrid, Spain, August 28-30, 2002Automatic methods for designing artificial neural nets are desired to avoid the laborious and erratically human expert’s job. Evolutionary computation has been used as a search technique to find appropriate NN architectures. Direct and indirect encoding methods are used to codify the net architecture into the chromosome. A reformulation of an indirect encoding method, based on two bi-dimensional cellular automata, and its generative capacity are presented.Publicad

Evolutionary cellular configurations for designing feed-forward neural networks architectures

Proceeding of: 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001 Granada, Spain, June 13–15, 2001In the recent years, the interest to develop automatic methods to determine appropriate architectures of feed-forward neural networks has increased. Most of the methods are based on evolutionary computation paradigms. Some of the designed methods are based on direct representations of the parameters of the network. These representations do not allow scalability, so to represent large architectures, very large structures are required. An alternative more interesting are the indirect schemes. They codify a compact representation of the neural network. In this work, an indirect constructive encoding scheme is presented. This scheme is based on cellular automata representations in order to increase the scalability of the method