This master thesis present a method for building topological maps for mobile robot navigation using neural network and neural fuzzy network. The master thesis concentrates on classification method. Neural fuzzy network is compared with two neural networks. It was also designed control algorithm exploration environment for autonomous mobile robot. This will rereduce the time to build the map. I developed simulation program in Matlab, which simulate move mobile robot in unknown environment.

Submitted by ERIK SARTORI JEUNON GONTIJO null (sartori_jg@hotmail.com) on 2017-04-20T15:59:08Z No. of bitstreams: 1 Erik Sartori Jeunon Gontijo - Tese.pdf: 6303649 bytes, checksum: e2379a13e7e45d2ce94323eddce0a8bc (MD5) / Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-04-25T17:47:27Z (GMT) No. of bitstreams: 1 gontijo_esj_dr_soro.pdf: 6303649 bytes, checksum: e2379a13e7e45d2ce94323eddce0a8bc (MD5) / Made available in DSpace on 2017-04-25T17:47:27Z (GMT). No. of bitstreams: 1 gontijo_esj_dr_soro.pdf: 6303649 bytes, checksum: e2379a13e7e45d2ce94323eddce0a8bc (MD5) Previous issue date: 2017-03-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Deutscher Akademischer Austauschdienst (DAAD) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / O As está distribuído em diversas formas químicas em sistemas aquáticos, o que determina o seu comportamento e destino no ambiente. Nesse contexto, as substâncias húmicas (SH) têm um importante papel por serem capazes de complexar esse metaloide e alterar sua mobilidade e biodisponibilidade. O Fe também tem grande importância por poder formar complexos ternários SH-Fe-As. Apesar da química do As já ter sido bem estudada, o seu comportamento em ambientes ricos em SH e Fe ainda não é totalmente compreendido. Os objetivos desse trabalho foram investigar a distribuição do As, Al e Fe em águas superficiais de uma região mineira no sudeste do Brasil (Quadrilátero Ferrífero, QF) e entender como características de SH extraídas de diferentes regiões (Brasil e Alemanha) afetam a complexação do As(V) na presença de Fe(III). Amostras de águas foram coletadas em 12 pontos do QF, filtradas (0,45 µm) e ultrafiltradas (1 kDa) para separar as frações particulada (>0,45 µm), coloidal (<0,45 µm e >1 kDa) e livre (<1 kDa) de As, Al e Fe. A técnica de difusão em filmes finos por gradientes de concentração (DGT) foi usada em 5 dos 12 pontos para estudar a fração lábil dos elementos estudados. Carbono orgânico total (COT) e dissolvido (COD) também foram medidos. SH foram extraídas de quatro pontos (um no Brasil nas estações seca e chuvosa e três na Alemanha) para testar a influência de diferentes tipos de SH e Fe(III) na complexação do As(V). As SH foram caracterizadas e foram feitos testes de complexação utilizando sistema de ultrafiltração com membrana de 1 kDa. Todos os dados foram analisados pela rede neural de Kohonen. Os resultados mostraram que a maior parte do Al e Fe total no QF estava presente na fração particulada e o As na fração livre. A maior parte do Al e Fe dissolvido estava na fração coloidal e inerte, diferente do As que era mais lábil e potencialmente biodisponível. A maioria das amostras apresentou comportamento similar nas estações seca e chuvosa no QF. Diferenças entre os resultados de ultrafiltração e DGT foram atribuídos a distinções metodológicas e processos químicos. Os resultados de caracterização dos extratos mostraram que a maior parte do As e Fe estavam predominantemente nas frações de maior tamanho molecular. Todos os extratos de SH complexaram quantidades similares de As(V) nos testes de complexação, exceto o extrato do rio Selke, onde foi encontrado menos As(V) livre (mais complexado). Essa diferença foi atribuída ao S e à grupos N-C aromático na estrutura de SH. Isso reforça que a qualidade das SH é um importante fator capaz de influenciar o comportamento do As em ambientes ricos em matéria orgânica e Fe, que também pareceram ser fatores limitantes nas interações com o As. A rede neural de Kohonen foi uma ferramenta importante nas investigações de distribuição do As e complexação do As(V) por Fe(III) e SH. / As is distributed in different chemical forms in aquatic systems. These different forms control its behaviour and fate in the environment. The humic substances (HS) have an important role in the As cycle since they can complex this metalloid and change its mobility and bioavailability. Fe is also important because it can form ternary complexes HS-Fe-As. Although the As chemistry is well studied, the behaviour of As in HS and Fe-rich environments is not totally known. This thesis aimed to investigate the distribution of As, Al and Fe in surface waters from a mining region in the southeast of Brazil (Quadrilátero Ferrífero, QF) and understand how characteristics of HS extracted from different regions (Brazil and Germany) affect the complexation of As(V) in the presence of Fe(III). Water samples were taken in 12 points in QF, filtered (0.45 µm) and ultrafiltered (1 kDa) to separate the fractions particulate (>0.45 µm), colloidal (<0.45 µm and >1 kDa) and free (<1 kDa) of As, Al and Fe. The technique of diffusive gradients in thin films (DGT) was used in 5 of the 12 points to study the labile fraction of the elements studied. Total organic carbon (TOC) and dissolved organic carbon (DOC) were also measured. HS were extracted from four points (one in Brazil in dry and rainy seasons and three in Germany) to analyse the influence of HS from different origins and Fe(III) on the complexation of As(V). The HS were characterised and complexation experiments were performed using an ultrafiltration system with 1 kDa membrane. All data were analysed using the Kohonen neural network. The results showed that most of total Al and Fe in QF was in the particulate fraction and As was in the free fraction. Most of the dissolved Al and Fe was in the colloidal and inert fraction, while As was more labile and potentially more bioavailable. Most samples had similar behaviour in the dry and rainy seasons in the QF. Differences between results of ultrafiltration and DGT were attributed to methodological distinctions and chemical processes. The results of characterisation of extracts showed that most of As and Fe was in the fractions of higher molecular size. All HS extracts complexed similar amounts of As(V), except Selke, where a lower amount of free As(V) was detected (more complexed). This difference was attributed to S and N-aromatic C groups in HS structure. It supports that the quality of HS is an important factor able to influence the behaviour of As in environments rich in organic matter and Fe. The Kohonen neural network was an important tool in the investigation of the distribution of As and As(V) complexation by Fe(III) and HS. / FAPESP: 2012/17727-8

The diploma thesis deal with finding and testing neural networks, whose characteristics and parameters suitable for the active management of network element. Solves optimization task priority switching of data units from input to output. Work is focused largely on the use of Hopfield and Kohonen networks and their optimization. Result of this work are two models. The first theory is solved in Matlab, where each comparing the theoretical results of neural networks. The second model is a realistic model of the active element designed in Simulink