It is a difficult challenge to develop a feedback control system for Statistical Process Control (SPC) because there is no effective method that can be used to calculate the accurate magnitude of feedback control actions in traditional SPC. Suitable feedback adjustments are generated from the experiences of process engineers. This drawback means that the SPC technique can not be directly applied in an automatic system. This thesis is concerned with Fuzzy Sets and Fuzzy Logic applied to the uncertainty of relationships between the SPC (early stage) alarms and SPC implementation. Based on a number of experiments of the frequency distribution for shifts of abnormal process averages and human subjective decision, a Fuzzy-SPC control system is developed to generate the magnitude of feedback control actions using fuzzy inference. A simulation study which is written in C++ is designed to implement a Fuzzy-SPC controller with satisfactory results. To further reduce the control errors, a NeuroFuzzy network is employed to build NNFuzzy- SPC system in MATLAB. The advantage of the leaning capability of Neural Networks is used to optimise the parameters of the Fuzzy- X and Fuzzy-J? controllers in order to obtain the ideal consequent membership functions to adapt to the randomness of various processes. Simulation results show that the NN-Fuzzy-SPC control system has high control accuracy and stable repeatability. To further improve the practicability of a NN-Fuzzy-SPC system, a combined forecaster with EWMA chart and digital filter is designed to reduce the NN-Fuzzy-SPC control delay. For the EWMA chart, the smoothing constant 0 is investigated by a number of experiments and optimised in the forecast process. The Finite Impulse Response (FIR) lowpass filter is designed to smooth the input data (signal) fluctuations in order to reduce the forecast errors. An improved NN-Fuzzy-SPC control system which shows high control accuracy and short control delay can be applied in both automatic control and online quality control.

Sistemas de previsão de cheias podem ser adequadamente utilizados quando o alcance é suficiente, em comparação com o tempo necessário para ações preventivas ou corretivas. Além disso, são fundamentalmente importantes a confiabilidade e a precisão das previsões. Previsões de níveis de inundação são sempre aproximações, e intervalos de confiança não são sempre aplicáveis, especialmente com graus de incerteza altos, o que produz intervalos de confiança muito grandes. Estes intervalos são problemáticos, em presença de níveis fluviais muito altos ou muito baixos. Neste estudo, previsões de níveis de cheia são efetuadas, tanto na forma numérica tradicional quanto na forma de categorias, para as quais utiliza-se um sistema especialista baseado em regras e inferências difusas. Metodologias e procedimentos computacionais para aprendizado, simulação e consulta são idealizados, e então desenvolvidos sob forma de um aplicativo (SELF – Sistema Especialista com uso de Lógica “Fuzzy”), com objetivo de pesquisa e operação. As comparações, com base nos aspectos de utilização para a previsão, de sistemas especialistas difusos e modelos empíricos lineares, revelam forte analogia, apesar das diferenças teóricas fundamentais existentes. As metodologias são aplicadas para previsão na bacia do rio Camaquã (15543 km2), para alcances entre 10 e 48 horas. Dificuldades práticas à aplicação são identificadas, resultando em soluções as quais constituem-se em avanços do conhecimento e da técnica. Previsões, tanto na forma numérica quanto categorizada são executadas com sucesso, com uso dos novos recursos. As avaliações e comparações das previsões são feitas utilizandose um novo grupo de estatísticas, derivadas das freqüências simultâneas de ocorrência de valores observados e preditos na mesma categoria, durante a simulação. Os efeitos da variação da densidade da rede são analisados, verificando-se que sistemas de previsão pluvio-hidrométrica em tempo atual são possíveis, mesmo com pequeno número de postos de aquisição de dados de chuva, para previsões sob forma de categorias difusas. / Flood forecasting systems are only useful when the forecast lead time is longer than the time required to activate preventive or remedial actions. In addition, the reliability and accuracy of forecasts are of prime importance. Flood level forecasts are always approximations, and confidence intervals are not always suitable, particularly with low confidence probabilities, which results intervals that are too wide. These intervals are troublesome, therefore, in the presence of very low and very high river levels. In this study, flood level forecasts are tried, both in the traditional, numerical form, and in the form of vague categories. It is accomplished using an expert system based on fuzzy rules and fuzzy inference. Methodologies and computational procedures for learning, simulation and consultation are idealised and then developed as a software (SELF - Sistema Especialista com uso de Lógica Fuzzy), which is aimed at research and practical operation. Comparisons between the use for prediction of fuzzy systems and empirical linear models revealed strong similarities, in spite of the fundamental differences in theory. The methodologies are applied to real time river level forecasts in the Camaquã river basin (15543 km2), for lead times ranging from one half to two days. Practical difficulties related to the use of fuzzy systems are identified and explored. The solutions found offer some advances to knowledge and practical application. Forecasts, both in the numerical and categorical forms, are made successfully, using the new resources. Evaluation and comparison of the predictions in symbolic form are made with the use of a proposed new group of statistics, derived from frequencies of simultaneous occurrences of observed and predicted values at the same categories. The effects of raingauge network density are analysed, and it is found that forecasting systems may be operated even where network density is sparse, given that fuzzy expert systems are available for symbolic predictions.

Este trabalho busca o estudo da segurança em redes de computadores através da implementação de um sistema detector de intrusão embasado na captura de informações pela utilização do protocolo SNMP. Para alcançar-se a diminuição no número de falsos positivo e negativo, problema peculiar à maioria dos IDS, utiliza-se a lógica difusa para, com o auxilio dos administradores de segurança de cada rede, possibilitar a construção de um sistema detector de intrusão que melhor se adeque às características das redes monitoradas. Posteriormente, utilizando o monitoramento de uma rede de produção, avalia-se a melhora na segurança obtida com o uso do IDS implementado por esse trabalho que, atuando quase em tempo real, propicia sua adoção como mecanismo complementar à segurança de redes. / This work develops a study about Computer Network Security through the implementation of an Instruction Detection System (IDS) based on system information captured by the SNMP protocol. To reach a reduction in the number of false positive and false negative, a peculiar problem to the majority of the IDS, it is used fuzzy logic and the assistance of Network Security Administrators. Thus it is possible to build an Intrusion Detection System better adjusted to the network characteristics that must be monitored. At last, by monitoring a production network, it is evaluated the overall security improvement obtained by the IDS proposed in this work and considers its adoption as a complementary network security mechanism.

Este volume descreve o trabalho multi e interdisciplinar de pesquisa realizado na área de Inteligência Artificial aplicada à Educação, tendo como objetivo principal à proposta de uma metodologia de trabalho suportada por um ambiente na Web como recurso de apoio à aprendizagem almejada pela subárea de Programação Computacional, nos cursos de graduação em Informática. O trabalho investigativo e experimental foi desenvolvido com base na teoria proposta por Ausubel e o ambiente desenvolvido possui arquitetura baseada nos Sistemas Tutores Inteligentes, onde se buscou criar um Assistente Virtual de Ensino Inteligente, cujo comportamento é modelado a partir de um conjunto de regras oriundas da Lógica Fuzzy. Esta base de regras busca estabelecer uma nova forma de análise e assistência no acompanhamento da evolução de aprendizagem do aluno, tendo por base os pressupostos da teoria ausubeliana. A organização dos conteúdos na base de domínio utiliza uma estrutura organizada na forma de Mapas Conceituais, os quais possuem relação com as funções de pertinência associadas aos objetivos destes conteúdos. O trabalho experimental foi realizado na universidade onde o autor trabalha como docente, permitindo que fossem realizadas as análises e entrevistas de forma facilitada. O protótipo, criado para validar alguns aspectos da tese, obteve sucesso e constatou um aproveitamento médio melhor na aprendizagem em Programação Computacional. / This volume describe the multi and interdisciplinary work of made research in the Artificial Intelligence area applied to Education, with the main objective to the purpose of one methodology of work that has the support by Web environment as a way of support for the expected learning by the Computational Programming sub area in the graduation courses of Informatics. The investigative and experimental work was developed based in the theory proposed by Ausubel and the developed environment has the architecture based in the Intelligent Tutoring Systems, looking for a creation of one Intelligent Teaching Assistant, which the behavior is model from the rule group with origin in Fuzzy Logic. This base of rules search to establish one new form of analysis and assistance to go along with evolution of student knowledge, basing in the presuppositions of Subsumption Theory. The organization of contents in the base of dominion use one organized structure in Conceptual Maps form, that have the relation with functions of associated relevant to the objectives of these contents. The experimental work was realized in university where the author works as a teacher, giving the permission to realize the analysis and interviews in the easy way. The prototype, created for some aspect validation of the thesis it was obtained success and it was consisted a medium development better than the learning in the Computacional Programming.

This work has as main proposal, supported by resources of geoprocessing and fuzzy logic, select and prioritize areas for deployment of landfill in the metropolitan region of Aracaju. To start of the study, it was made an approach about the generation of solid waste household and sweeping in the municipalities of Greater Aracaju, getting to the size of the area required to accommodate the trash of the next fifteen and twenty years in the region. Soon after, were initially created eight macro-areas of restriction arising from the approach of legal and operational, which derived more twenty-nine other new areas with greater detail, resulting in only nine, as being of greater ability. Once these areas are subjected to an analysis mult- criterion under environmental, operational and human, applied to the fuzzy logic, aimed at making numerical values in linguistic expressions and reverse, with the objective of scoring each area under the aspect of various topics and can classify and prioritize in order to denote those of the more minor suitability for the deployment of landfill in the metropolitan area of Aracaju. Finally, reached a final classification of the areas, however, it was found that only technical criteria not enough to indicate an area as perfect for the deployment of a landfill, it must be accepted politically, which had not been considered in this work, which has the main function used to support the decision, giving support to public managers. / Fundação de Amparo a Pesquisa do Estado de Alagoas / Este trabalho tem como principal proposta selecionar e hierarquizar áreas para implantação do aterro sanitário da região metropolitana de Aracaju, apoiando-se em recursos de geoprocessamento e lógica fuzzy. Para início do estudo, fez-se uma abordagem acerca da geração de resíduos sólidos domiciliares e de varrição nos municípios da Grande Aracaju, chegando-se ao tamanho da área necessária para acolher o lixo nos próximos quinze e vinte anos na região. Logo após, foram criadas inicialmente oito macro-áreas de restrição, originadas da abordagem de ordem legal e operacional, que em seguida derivou mais vinte e nove outras novas áreas estudadas com maior detalhamento, resultando em nove, como sendo as de maior aptidão. Após estas áreas serem submetidas a uma análise multicritério, sob condicionantes ambientais, operacionais e antrópicas, aplicou-se a lógica fuzzy, visando transformar valores numéricos em expressões lingüísticas e vice-versa, com o objetivo de pontuar cada área sob o aspecto de vários temas, podendo assim, classificá-las e hierarquizá-las de modo a se denotar as de maior a menor aptidão para a implantação do aterro sanitário da região metropolitana de Aracaju. Por fim, chegou-se a uma classificação final das áreas, quando verificou-se que, apenas critérios técnicos não bastam para se indicar uma área como ideal para a implantação de um aterro sanitário, esta deve ser aceita politicamente, o que não fora considerado nesse trabalho, o qual tem como principal função servir de apoio à decisão, dando suporte aos gestores públicos.

MACIEL, Wlisses Matos. Montagem e instalação de um sistema de controle automático de irrigação. 2005. 85 f. Dissertação (Mestrado em engenharia agrícola)- Universidade Federal do Ceará, Fortaleza-CE, 2005. / Submitted by Elineudson Ribeiro (elineudsonr@gmail.com) on 2016-06-28T19:28:16Z No. of bitstreams: 1 2005_dis_wmmaciel.pdf: 1582032 bytes, checksum: 45d12f1338751fa3fbd6a49b302faf2c (MD5) / Approved for entry into archive by José Jairo Viana de Sousa (jairo@ufc.br) on 2016-06-30T22:48:21Z (GMT) No. of bitstreams: 1 2005_dis_wmmaciel.pdf: 1582032 bytes, checksum: 45d12f1338751fa3fbd6a49b302faf2c (MD5) / Made available in DSpace on 2016-06-30T22:48:21Z (GMT). No. of bitstreams: 1 2005_dis_wmmaciel.pdf: 1582032 bytes, checksum: 45d12f1338751fa3fbd6a49b302faf2c (MD5) Previous issue date: 2005 / This work had as objectives to set up and to install overhead irrigations with different automation levels: automatic intelligent, automatic for temporizador and no automatic. An experiment was driven in the experimental area of the Laboratory of Hydraulics and Irrigation of the Federal University of Ceará, in Fortaleza, CE, in the period of October of 2004 to January of 2005. Those three systems were distributed in a statistical delineamento in blocks casualizados. The delineamento consisted of 6 blocks and three treatments distributed in 18 experimental portions measuring 4m of width and 12m of length, occupying a total area of 1600m2. The assembly was divided in two phases, the first phase consisted of the assembly of the electronic and electric systems composed for sensor of humidity (resistance blocks), sensor of temperature (termopares), datalogger, multiplexador, digital plate of E/S pattern ISA, conditioning plate of relés, temporizador, contactores, relés, departure key, cabeamento, aterramento and Monday of the waterworks and of irrigation composed of bombs, piping, reservoirs, manômetros, hydrometers, venturis, pressure sockets and connections; all of the extolled systems were mounted and installed in the field. / Este trabalho teve como objetivos montar e instalar sistemas de irrigação com diferentes níveis de automação: automático inteligente, automático por temporizador e não automático. Foi conduzido um experimento na área experimental do Laboratório de Hidráulica e Irrigação da Universidade Federal do Ceará, em Fortaleza, CE, no período de outubro de 2004 a janeiro de 2005. Esses três sistemas foram distribuídos em um delineamento estatístico em blocos casualizados. O delineamento constou de 6 blocos e três tratamentos distribuídos em 18 parcelas experimentais medindo 4m de largura e 12m de comprimento, ocupando uma área total de 1600m2. A montagem foi dividida em duas fases, a primeira fase consistiu na montagem dos sistemas eletrônico e elétrico composto por sensores de umidade (blocos de resistência), sensores de temperatura (termopares), datalogger, multiplexador, placa digital de E/S padrão ISA, placa condicionadora de relés, temporizador, contactores, relés, chave de partida, cabeamento, aterramento e a segunda dos sistemas hidráulico e de irrigação composto de bombas, tubulações, reservatórios, manômetros, hidrômetros, venturis, tomadas de pressão e conexões; todos os sistemas preconizados foram montados e instalado no campo.

The Generalized Constraint Language (GCL), introduced by Zadeh, is the essence of Computing with Words (CW). It provides an genda to represent the meaning of imprecise words and phrases in natural language and introduces advanced techniques to perform reasoning on imprecise knowledge. Despite its fundamental role, the definition of GCL has remained informal since its introduction by Zadeh and, to our knowledge, no attempt has been made to formalize GCL or to build a working GCL deduction system. In this dissertation, two main interrelated objectives are pursued: First, the syntax and semantics of GCL are formalized in a logical setting. The notion of soundness of a GCL argument is defined and Zadeh's inference rules are proven sound in the defined language. Second, a CW Expert System Shell (CWSHELL) is implemented for the realization of a GCL deduction system. The CWSHELL software allows users to express their knowledge in terms of GCL formulas and pose queries to a GCL knowledge base. The richness of GCL language allows CWSHELL to greatly surpass current fuzzy logic expert systems both in its knowledge representation and reasoning capabilities. While many available fuzzy logic toolboxes can only represent knowledge in terms of fuzzy-if-then rules, CWShell goes beyond simple fuzzy conditional statements and performs a chain of reasoning on complex fuzzy propositions containing generalized constraints, fuzzy arithmetic expressions, fuzzy quantifiers, and fuzzy relations. To explore the application of CWSHELL, a realistic case study is developed to compute the auto insurance premium based on an imprecise knowledge base. The alpha version of CWSHELL along with the case study and documentation is available for download at http://cwjess.cs.siu.edu/.

Computing with words (CW) provides symbolic and semantic methodology to deal with imprecise information associated with natural language. The CW paradigm rooted in fuzzy logic, when coupled with an expert system, offers a general methodology for computation with fuzzy variables and a fusion of natural language propositions for this purpose. Fuzzy variables encode the semantic knowledge, and hence, the system can understand the meaning of the symbols. The use of words not only simplifies the knowledge acquisition process, but can also eliminate the need of a human knowledge engineer. CW encapsulates various fuzzy logic techniques developed in past decades and formalizes them. Z-number is an emerging paradigm that has been utilized in computing with words among other constructs. The concept of Z-number is intended to provide a basis for computation with numbers that deals with reliability and likelihood. Z-numbers are confluence of the two most prominent approaches to uncertainty, probability and possibility, that allow computations on complex statements. Certain computations related to Z-numbers are ambiguous and complicated leading to their slow adaptation into areas such as computing with words. Moreover, as acknowledged by Zadeh, there does not exist a unique solution to these problems. The biggest contributing factor to the complexity is the use of probability distributions in the computations. This dissertation seeks to provide an applied model of Z-number based on certain realistic assumptions regarding the probability distributions. Algorithms are presented to implement this model and integrate it into an expert system shell for computing with words called CWShell. CWShell is a software tool that abstracts the underlying computation required for computing with words and provides a convenient way to represent and reason on a unstructured natural language.

Risk management is an essential tool for ensuring the safety and timeliness of maritime operations and transportation. Some of the many risk factors that can compromise the smooth operation of maritime activities include harsh weather and pirate activity. However, identifying and quantifying the extent of these risk factors for a particular vessel is not a trivial process. One challenge is that processing the vast amounts of automatic identification system (AIS) messages generated by the ships requires significant computational resources. Another is that the risk management process partially relies on human expertise, which can be timeconsuming and error-prone. In this thesis, an existing Risk Management Framework (RMF) is augmented to address these issues. A parallel/distributed version of the RMF is developed to e ciently process large volumes of AIS data and assess the risk levels of the corresponding vessels in near-real-time. A genetic fuzzy system is added to the RMF's Risk Assessment module in order to automatically learn the fuzzy rule base governing the risk assessment process, thereby reducing the reliance on human domain experts. A new weather risk feature is proposed, and an existing regional hostility feature is extended to automatically learn about pirate activity by ingesting unstructured news articles and incident reports. Finally, a geovisualization tool is developed to display the position and risk levels of ships at sea. Together, these contributions pave the way towards truly automatic risk management, a crucial component of modern maritime solutions. The outcomes of this thesis will contribute to enhance Larus Technologies' Total::Insight, a risk-aware decision support system successfully deployed in maritime scenarios.

Sistemas de previsão de cheias podem ser adequadamente utilizados quando o alcance é suficiente, em comparação com o tempo necessário para ações preventivas ou corretivas. Além disso, são fundamentalmente importantes a confiabilidade e a precisão das previsões. Previsões de níveis de inundação são sempre aproximações, e intervalos de confiança não são sempre aplicáveis, especialmente com graus de incerteza altos, o que produz intervalos de confiança muito grandes. Estes intervalos são problemáticos, em presença de níveis fluviais muito altos ou muito baixos. Neste estudo, previsões de níveis de cheia são efetuadas, tanto na forma numérica tradicional quanto na forma de categorias, para as quais utiliza-se um sistema especialista baseado em regras e inferências difusas. Metodologias e procedimentos computacionais para aprendizado, simulação e consulta são idealizados, e então desenvolvidos sob forma de um aplicativo (SELF – Sistema Especialista com uso de Lógica “Fuzzy”), com objetivo de pesquisa e operação. As comparações, com base nos aspectos de utilização para a previsão, de sistemas especialistas difusos e modelos empíricos lineares, revelam forte analogia, apesar das diferenças teóricas fundamentais existentes. As metodologias são aplicadas para previsão na bacia do rio Camaquã (15543 km2), para alcances entre 10 e 48 horas. Dificuldades práticas à aplicação são identificadas, resultando em soluções as quais constituem-se em avanços do conhecimento e da técnica. Previsões, tanto na forma numérica quanto categorizada são executadas com sucesso, com uso dos novos recursos. As avaliações e comparações das previsões são feitas utilizandose um novo grupo de estatísticas, derivadas das freqüências simultâneas de ocorrência de valores observados e preditos na mesma categoria, durante a simulação. Os efeitos da variação da densidade da rede são analisados, verificando-se que sistemas de previsão pluvio-hidrométrica em tempo atual são possíveis, mesmo com pequeno número de postos de aquisição de dados de chuva, para previsões sob forma de categorias difusas. / Flood forecasting systems are only useful when the forecast lead time is longer than the time required to activate preventive or remedial actions. In addition, the reliability and accuracy of forecasts are of prime importance. Flood level forecasts are always approximations, and confidence intervals are not always suitable, particularly with low confidence probabilities, which results intervals that are too wide. These intervals are troublesome, therefore, in the presence of very low and very high river levels. In this study, flood level forecasts are tried, both in the traditional, numerical form, and in the form of vague categories. It is accomplished using an expert system based on fuzzy rules and fuzzy inference. Methodologies and computational procedures for learning, simulation and consultation are idealised and then developed as a software (SELF - Sistema Especialista com uso de Lógica Fuzzy), which is aimed at research and practical operation. Comparisons between the use for prediction of fuzzy systems and empirical linear models revealed strong similarities, in spite of the fundamental differences in theory. The methodologies are applied to real time river level forecasts in the Camaquã river basin (15543 km2), for lead times ranging from one half to two days. Practical difficulties related to the use of fuzzy systems are identified and explored. The solutions found offer some advances to knowledge and practical application. Forecasts, both in the numerical and categorical forms, are made successfully, using the new resources. Evaluation and comparison of the predictions in symbolic form are made with the use of a proposed new group of statistics, derived from frequencies of simultaneous occurrences of observed and predicted values at the same categories. The effects of raingauge network density are analysed, and it is found that forecasting systems may be operated even where network density is sparse, given that fuzzy expert systems are available for symbolic predictions.