The growing usage of computer networks is requiring improvements in network technologies and management techniques so users will receive high quality service. As more individuals transmit data through a computer network, the quality of service received by the users begins to degrade. A major aspect of computer networks that is vital to quality of service is data routing. A more effective method for routing data through a computer network can assist with the new problems being encountered with today's growing networks. Effective routing algorithms use various techniques to determine the most appropriate route for transmitting data. Determining the best route through a wide area network (WAN), requires the routing algorithm to obtain information concerning all of the nodes, links, and devices present on the network. The most relevant routing information involves various measures that are often obtained in an imprecise or inaccurate manner, thus suggesting that fuzzy reasoning is a natural method to employ in an improved routing scheme. The neural network is deemed as a suitable accompaniment because it maintains the ability to learn in dynamic situations. Once the neural network is initially designed, any alterations in the computer routing environment can easily be learned by this adaptive artificial intelligence method. The capability to learn and adapt is essential in today's rapidly growing and changing computer networks. These techniques, fuzzy reasoning and neural networks, when combined together provide a very effective routing algorithm for computer networks. Computer simulation is employed to prove the new fuzzy routing algorithm outperforms the Shortest Path First (SPF) algorithm in most computer network situations. The benefits increase as the computer network migrates from a stable network to a more variable one. The advantages of applying this fuzzy routing algorithm are apparent when considering the dynamic nature of modern computer networks. / Ph. D.

A pesquisa de cunho qualitativo aqui apresentada tem como propósito discutir o valor e o papel da lógica fuzzy na solução de problemas reais, dada a característica de suas ferramentas para lidar com questões subjetivas, uma vez que as soluções de problemas provenientes do mundo real estão carregadas de relações construídas no mundo interno do resolvedor são oriundas da subjetividade do sujeito resolvedor. Nosso trabalho teve como um dos objetivos responder às questões: Quais os pressupostos teóricos da teoria fuzzy e quais as possibilidades de reconhecimento de seu valor e de seu papel para a Educação Matemática? Como o pensamento matemático do aluno lida com o raciocínio fuzzy? Com essa perspectiva, aproximamo-nos dos alunos do Curso de Licenciatura das Faculdades Unificadas da Fundação Educacional de Barretos UNFEB , na busca de evidências, em termos de pesquisa, por meio de dois questionários e um minicurso ministrado pelo pesquisador, nesta ordem: questionário, minicurso e questionário. O primeiro questionário instigava o uso de variáveis subjetivas na solução de questões. O minicurso teve como foco central a resolução de um mesmo problema, utilizando matemática clássica e matemática fuzzy. O questionário final, de cunho avaliativo, verificava o uso, pelo aluno, das ferramentas da teoria fuzzy em problemas semelhantes aos anteriores. Os resultados da pesquisa indicaram a pouca experiência dos alunos com o raciocínio fuzzy dada, talvez, a dominância da matemática formal/determinística; mostraram, também, evidências de que os mesmos problemas, resolvidos verbalmente, sem o uso da matemática, revelam-se especialmente desafiadores quando é solicitada uma solução matemática fuzzy. / The qualitative research here presented intends to discuss the value and the role of fuzzy logic in the solution of real problems, due to the characteristic of its tools to deal with subjective questions, since the solution of problems originated in the real world are loaded with relationships built in the resolvers internal world they are originated in the subjectresolvers subjectivity. Our work had as one of its goals to answer the questions: Which are Fuzzy Theory theoretical assumptions and what are the possibilities of acknowledgement of its value and role to Mathematical Education?; How does the students mathematical thinking deal with fuzzy reasoning? On this perspective, we approached the students of the Curso de Licenciatura das Faculdades Unificadas da Fundação Educacional de Barretos - UNFEB searching for research evidences by means of two questionnaires and a mini-course taught by the researcher, in the following order: questionnaire, mini-course and questionnaire. The first questionnaire incited the use of subjective variables in the solution of questions. The mini-course, after the questionnaire, had as main focus the solution of one (same) problem using classical mathematics and fuzzy mathematics. The final questionnaire, of evaluative nature, verified the students use of fuzzy theory tools for problems similar to the previous ones. The research results indicated the students little experience with fuzzy reasoning maybe due to the dominance of formal/deterministic mathematics as well as showing evidences that the same problems solved verbally without the use of mathematics were especially challenging when a fuzzy mathematics solution was requested.

In this thesis, Genetic Granular Cognitive Fuzzy Neural Networks (GGCFNN), combining genetic algorithms (GA) and granular cognitive fuzzy neural networks (GCFNN), is proposed for pattern recognition problems. According to cognitive patterns, biological neural networks in the human brain can recognize different patterns. Since GA and neural networks represent two learning methods based on biological science, it is indispensable and valuable to investigate how biological neural networks and artificial neural networks recognize different patterns. The new GGCFNN, based on granular computing, soft computing and cognitive science, is used in the pattern recognition problems. The hybrid forward-wave-backward-wave learning algorithm, as a main learning technology in GCFNN, is used to enhance learning quality. GA optimizes parameters to make GGCFNN get better learning results. Both pattern recognition results generated by human persons and those by GGCFNN are analyzed in terms of computer science and cognitive science.

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A pesquisa de cunho qualitativo aqui apresentada tem como propósito discutir o valor e o papel da lógica fuzzy na solução de problemas reais, dada a característica de suas ferramentas para lidar com questões subjetivas, uma vez que as soluções de problemas provenientes do mundo real estão carregadas de relações construídas no mundo interno do resolvedor são oriundas da subjetividade do sujeito resolvedor. Nosso trabalho teve como um dos objetivos responder às questões: Quais os pressupostos teóricos da teoria fuzzy e quais as possibilidades de reconhecimento de seu valor e de seu papel para a Educação Matemática? Como o pensamento matemático do aluno lida com o raciocínio fuzzy? Com essa perspectiva, aproximamo-nos dos alunos do Curso de Licenciatura das Faculdades Unificadas da Fundação Educacional de Barretos UNFEB , na busca de evidências, em termos de pesquisa, por meio de dois questionários e um minicurso ministrado pelo pesquisador, nesta ordem: questionário, minicurso e questionário. O primeiro questionário instigava o uso de variáveis subjetivas na solução de questões. O minicurso teve como foco central a resolução de um mesmo problema, utilizando matemática clássica e matemática fuzzy. O questionário final, de cunho avaliativo, verificava o uso, pelo aluno, das ferramentas da teoria fuzzy em problemas semelhantes aos anteriores. Os resultados da pesquisa indicaram a pouca experiência dos alunos com o raciocínio fuzzy dada, talvez, a dominância da matemática formal/determinística; mostraram, também, evidências de que os mesmos problemas, resolvidos verbalmente, sem o uso da matemática, revelam-se especialmente desafiadores quando é solicitada uma solução matemática fuzzy. / The qualitative research here presented intends to discuss the value and the role of fuzzy logic in the solution of real problems, due to the characteristic of its tools to deal with subjective questions, since the solution of problems originated in the real world are loaded with relationships built in the resolvers internal world they are originated in the subjectresolvers subjectivity. Our work had as one of its goals to answer the questions: Which are Fuzzy Theory theoretical assumptions and what are the possibilities of acknowledgement of its value and role to Mathematical Education?; How does the students mathematical thinking deal with fuzzy reasoning? On this perspective, we approached the students of the Curso de Licenciatura das Faculdades Unificadas da Fundação Educacional de Barretos - UNFEB searching for research evidences by means of two questionnaires and a mini-course taught by the researcher, in the following order: questionnaire, mini-course and questionnaire. The first questionnaire incited the use of subjective variables in the solution of questions. The mini-course, after the questionnaire, had as main focus the solution of one (same) problem using classical mathematics and fuzzy mathematics. The final questionnaire, of evaluative nature, verified the students use of fuzzy theory tools for problems similar to the previous ones. The research results indicated the students little experience with fuzzy reasoning maybe due to the dominance of formal/deterministic mathematics as well as showing evidences that the same problems solved verbally without the use of mathematics were especially challenging when a fuzzy mathematics solution was requested.

In recent years, the type-2 fuzzy sets theory has been used to model and minimize the effects of uncertainties in rule-base fuzzy logic system. In order to make the type-2 fuzzy logic system reasonable and reliable, a new simple and novel statistical method to decide interval-valued fuzzy membership functions and a new probability type reduced reasoning method for the interval-valued fuzzy logic system are proposed in this thesis. In order to optimize this particle system’s performance, we adopt genetic algorithm (GA) to adjust parameters. The applications for the new system are performed and results have shown that the developed method is more accurate and robust to design a reliable fuzzy logic system than type-1 method and the computation of our proposed method is more efficient.