Análise da rede política do turismo brasileiro.

The dissertation examines the influence of relationships among actors from Brazilian Tourism Political Network who compose the National Council of Tourism in the drafting of the National Tourism Plans (PNT) - PNTs 2003/2007 and 2007/2010, focusing on two main types of interaction: cooperation and information exchange. Therefore, the study departed from the understanding that the concept of tourism as a human phenomenon is configured as an essential conceptual basis for the development, implementation and analysis of public policies. The application of Network Theory and Social Network Analysis serves as an analytical tool, in addition, the use of concepts of Policy Networks enabled to interpret, in distinct aspects, the social reality of tourism in a more precise and detailed way. The study had a cross-sectional with a longitudinal perspective and case study was adopted, thus enabling to apply the model of social network analysis and qualitative approach. Through the survey conducted, it was found that the drafting process of National Tourism Plans was the result of the interaction of a complex network of actors from public and private initiatives, who compose the National Council of Tourism, and that their power of influence came out simultaneously, but not symmetrically, for both their performance/intervention in the meetings, and the possession of economic and organizational resources. Hence, the establishment of partnerships and information exchanges among the actors were underlying to the PNT drafting process, both in problems perception and insertion in the government agenda, as in making proposals to solve them, thus guiding the construction of large programs and programs contained in both investigated plans.

Identificação não linear usando uma rede fuzzy wavelet neural network modificada

In last decades, neural networks have been established as a major tool for the identification of nonlinear systems. Among the various types of networks used in identification, one that can be highlighted is the wavelet neural network (WNN). This network combines the characteristics of wavelet multiresolution theory with learning ability and generalization of neural networks usually, providing more accurate models than those ones obtained by traditional networks. An extension of WNN networks is to combine the neuro-fuzzy ANFIS (Adaptive Network Based Fuzzy Inference System) structure with wavelets, leading to generate the Fuzzy Wavelet Neural Network - FWNN structure. This network is very similar to ANFIS networks, with the difference that traditional polynomials present in consequent of this network are replaced by WNN networks. This paper proposes the identification of nonlinear dynamical systems from a network FWNN modified. In the proposed structure, functions only wavelets are used in the consequent. Thus, it is possible to obtain a simplification of the structure, reducing the number of adjustable parameters of the network. To evaluate the performance of network FWNN with this modification, an analysis of network performance is made, verifying advantages, disadvantages and cost effectiveness when compared to other existing FWNN structures in literature. The evaluations are carried out via the identification of two simulated systems traditionally found in the literature and a real nonlinear system, consisting of a nonlinear multi section tank. Finally, the network is used to infer values of temperature and humidity inside of a neonatal incubator. The execution of such analyzes is based on various criteria, like: mean squared error, number of training epochs, number of adjustable parameters, the variation of the mean square error, among others. The results found show the generalization ability of the modified structure, despite the simplification performed