O reconhecimento aproximado de cadeias de texto é um problema recorrente em diversas aplicações onde o computador é utilizado como meio de processamento de uma massa de dados sujeita a imprecisões, erros e distorções. Existem inúmeras metodologias, técnicas e métricas criadas e empregadas na resolução deste tipo de problema, mas a maioria delas é inflexível em pelo menos um dos seguintes pontos: arquitetura, métrica utilizada para aferir o erro encontrado ou especificidade na aplicação. Esse trabalho propõe e analisa a utilização dos Autômatos Finitos Nebulosos para a resolução desse tipo de problema. A teoria nebulosa oferece uma base teórica sólida para o tratamento de informações inexatas ou sujeita a erros, enquanto o modelo matemático dos autômatos finitos é uma ferramenta consolidada para o problema de reconhecimento de cadeias de texto. Um modelo híbrido não só oferece uma solução flexível para a resolução do problema proposto, como serve de base para a resolução de inúmeros outros problemas que dependem do tratamento de informações imprecisas. / The approximate string matching problem is recurring in many applications where computer is used to process imprecise, fuzzy or spurious data. An uncountable number of methods, techniques and metrics to solve this class of problem are available, but many of them are inflexible at least in one of following: architecture, metric or application specifics. This work proposes and analyzes the use of Fuzzy Finite State Automata to solve this class of problems. The fuzzy theory grants a solid base to handle imprecise or fuzzy information; the finite state automata is a classic tool in string matching problems. A hybrid model offers a flexible solution for this class of problem and can be a base for other problems related with imprecise data processing.

O reconhecimento aproximado de cadeias de texto é um problema recorrente em diversas aplicações onde o computador é utilizado como meio de processamento de uma massa de dados sujeita a imprecisões, erros e distorções. Existem inúmeras metodologias, técnicas e métricas criadas e empregadas na resolução deste tipo de problema, mas a maioria delas é inflexível em pelo menos um dos seguintes pontos: arquitetura, métrica utilizada para aferir o erro encontrado ou especificidade na aplicação. Esse trabalho propõe e analisa a utilização dos Autômatos Finitos Nebulosos para a resolução desse tipo de problema. A teoria nebulosa oferece uma base teórica sólida para o tratamento de informações inexatas ou sujeita a erros, enquanto o modelo matemático dos autômatos finitos é uma ferramenta consolidada para o problema de reconhecimento de cadeias de texto. Um modelo híbrido não só oferece uma solução flexível para a resolução do problema proposto, como serve de base para a resolução de inúmeros outros problemas que dependem do tratamento de informações imprecisas. / The approximate string matching problem is recurring in many applications where computer is used to process imprecise, fuzzy or spurious data. An uncountable number of methods, techniques and metrics to solve this class of problem are available, but many of them are inflexible at least in one of following: architecture, metric or application specifics. This work proposes and analyzes the use of Fuzzy Finite State Automata to solve this class of problems. The fuzzy theory grants a solid base to handle imprecise or fuzzy information; the finite state automata is a classic tool in string matching problems. A hybrid model offers a flexible solution for this class of problem and can be a base for other problems related with imprecise data processing.

Recent technical progress has made new forms of controller implementations on computers possible. Especially the technique of Fuzzy Logic Control has found a growing number of applications. Also the development of fast A/D converters has made the acquisation of data with vision based systems possible. In this project we combine the two techniques of Fuzzy Logic Control and Vision Feedback to control an inverted pendulum and to determine their usefulness and limitations. The experiment was conducted and provided us with the data necessary to judge the performance of the new control strategy. The gathered data support the hypothesis that it is possible to control the inverted pendulum with Fuzzy Logic Control using Vision Feedback, though not without limitations. / Graduation date: 1995

Adequate control of the position of the plasma column within the STOR-M tokamak is a chief requirement in order for experimental quality discharges to be obtained. Optimal control over tokamak discharge parameters, including the plasma position, is very difficult to achieve. This is due in large part to the difficulty in modelling the tokamak discharge parameters, as they are highly nonlinear and time varying in nature. The difficulty of modelling the tokamak discharge parameters suggests that a control system, such as a fuzzy logic based controller, which does not require a system model may be well suited to the control of fusion plasma. In order to improve the quality of control over the plasma position within the STOR-M tokamak, the existing analog PID controller was modified. These modifications facilitate the application of a digital controller by a personal computer via the Advantech PCL-711B data acquisition card. The performance of the modified plasma position controller and an Arbitrary Signal Generator developed by the author was evaluated. This modified plasma position controller was applied successfully to the STOR-M tokamak during both normal mode and A.C. mode operation. In both cases, the modified controller provided adequate control over the position of the plasma column within the discharge chamber. Furthermore, the modified controller was more convenient to optimize than the original, existing analog PID controller. By taking advantage of the modifications that were made to the plasma position controller, a fuzzy logic controller was developed by the author. The fuzzy logic based plasma position controller was also successfully applied to the STOR-M tokamak during both normal mode and A.C. operation. The fuzzy controller was demonstrated to reliably provide a higher degree of control over the position of the plasma column within the STOR-M tokamak than the modified PID controller.

Adequate control of the position of the plasma column within the STOR-M tokamak is a chief requirement in order for experimental quality discharges to be obtained. Optimal control over tokamak discharge parameters, including the plasma position, is very difficult to achieve. This is due in large part to the difficulty in modelling the tokamak discharge parameters, as they are highly nonlinear and time varying in nature. The difficulty of modelling the tokamak discharge parameters suggests that a control system, such as a fuzzy logic based controller, which does not require a system model may be well suited to the control of fusion plasma. In order to improve the quality of control over the plasma position within the STOR-M tokamak, the existing analog PID controller was modified. These modifications facilitate the application of a digital controller by a personal computer via the Advantech PCL-711B data acquisition card. The performance of the modified plasma position controller and an Arbitrary Signal Generator developed by the author was evaluated. This modified plasma position controller was applied successfully to the STOR-M tokamak during both normal mode and A.C. mode operation. In both cases, the modified controller provided adequate control over the position of the plasma column within the discharge chamber. Furthermore, the modified controller was more convenient to optimize than the original, existing analog PID controller. By taking advantage of the modifications that were made to the plasma position controller, a fuzzy logic controller was developed by the author. The fuzzy logic based plasma position controller was also successfully applied to the STOR-M tokamak during both normal mode and A.C. operation. The fuzzy controller was demonstrated to reliably provide a higher degree of control over the position of the plasma column within the STOR-M tokamak than the modified PID controller.

In this thesis, we propose an improved fuzzy GBML¡]genetic-based machine learning¡^algorithm to construct a FRBCS¡]fuzzy rule-based classification system¡^for pattern classification problem. Existing hybrid fuzzy GBML algorithm is consuming more computational time since it used the SS fuzzy model and combined with the Michigan-style algorithm for increasing the convergent rate of the Pittsburgh-style algorithm. By contrast, our improved fuzzy GBML algorithm is consuming less computational time since it used the MW fuzzy model and instead of the role of the Michigan-style algorithm by a heuristic procedure. Experimental results show that improved fuzzy GBML algorithm possesses the shorter computational time, the faster convergent rate, and the slightly better classification rate.

In the book of ¡§The Practice of Management.¡¨ Peter Drucker (1989), one of the most famous masters of management field, noted that being the only dynamic element of the company, the quality and performance of managers determine the fate of the company. Indeed, as the world changes getting faster and faster, the role manger played is becoming more and more important. In order to advance the competency managers need, enterprises worldwide are putting more and more effort to develop all kinds of competency assessment models that they can use as the base to make decision about managerial competency activities. Limited by the skill or ability of assessor, the traditional general assessment was unable to make fare judgments and the effect is hard to see. On the other hand, because the Assessment Center often takes longer time and more money to implement, it also limits the number of people to be assessed. Therefore, by using the AHP method of Multi-Criteria Evaluation to construct a new managerial competency assessment model, the assessor would be able to obtain the information needed to assist the relative managerial competency activities with a more systematic ways and fewer steps than before. The study adopted Borda Function and AHP method conduct a further survey and analysis with the semi-conductor industries. The findings are list as bellows: 1. Constructing the managerial competency assessment weighting system, is consisted of 8 main indicators and 39 sub-indicators, which shows a correct direction to conduct activities 2. Meaning on the scale of weighting indicators, indicates the relative degree of importance between indicators, which can show the key points to accelerate the effects of relative activities. 3. The AHP Management Competency Assessment Model is developed from the mathematics which can reflect the impact on decision making, caused by fuzzy situations and which can provide valuable information about the assessment management of management competency. 4. An empirical study was conducted to examine this model. The target of this empirical study is one electronics company. Top executives of the company heavily recognize this analytical result of the main evaluative indicator and sub-indicator. They consider this research¡¦s model having highly explanative capacity and can be reference of future managerial related activities. Keyword: Management Competency, Fuzzy Theory, Fuzzy Analytic Hierarchy Process (FAHP).

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Nowadays, the administration environment is changing rapidly. Since International Institute for Management Development¡]IMD¡^selects ¡§government efficiency¡¨ and ¡§business efficiency¡¨ as the major factors and criteria to compute the rankings of world competitiveness in the World Competitiveness Yearbook. Both governments and enterprises force to innovate and need to strengthen organizational performance to promote work efficiency, and to improve the strategic management system. This research applies the organizational performance theme in public institutions as well as in the operations of private enterprises by using the Balanced Scorecard¡¦s concept for measuring the scale operational activities of organization. To verify the performance of organization management, the questionnaire picks ¡§Likert Scale¡¨ criteria, and adopts the fuzzy membership function transformation to obtain measuring results. The purposes of this research are: 1) to design a performance measure scale with content validity based on Balanced Scorecord; 2) to compare weighted and fuzzy algorithm; 3) to to verify the worth of fuzzy algorithm. The results of this research are: 1) fuzzy algorithm is better than weighted algorithm in validity; 2) the Balance Scorecard helps organizational performance; 3) customer perspective is the first priority of performance measures in the Balanced Scorecard.

published_or_final_version / abstract / toc / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy