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Construção e avaliação de um modelo matematico para predizer a evolução do cancer de prostata e descrever seu crescimento utilizando a teoria dos conjuntos fuzzy / Mathematical models to predict the pathological stage and to describe the growth of the prostate cancer based on the fuzzy sets theoryCastanho, Maria Jose de Paula 17 March 2005 (has links)
Orientadores: Akebo Yamakami, Laecio Carvalho de Barros, Laercio Luis Vendite / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T04:11:06Z (GMT). No. of bitstreams: 1
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Previous issue date: 2005 / Resumo: O câncer de próstata é, atualmente, o segundo tipo de câncer com maior incidência entre a população masculina, no Brasil. Estimar o seu estágio, com as informações clínicas disponíveis para decidir a terapia a ser aplicada, é uma tarefa árdua. Neste trabalho, um modelo matemático é elaborado para auxiliar o médico na tomada de decisão. A teoria dos conjuntosfuzzy, por sua capacidade em lidar com incertezas, inerentes aos conceitos médicos, é a ferramenta utilizada, não só para desenvolver o modelo, como também para desenvolver a metodologia para sua avaliação, baseada na análise ROC (Receiver Operating Characteristic). A avaliação foi feita utilizando-se dados obtidos junto ao Instituto Americano do Câncer e permite afinnar que o sistema especialista construí do discrimina pacientes com câncer confinado à próstata daqueles com câncer não-confinado. Considerando a taxa de crescimento como um parâmetro incerto e variável na população, também é apresentado um modelo para descrever o crescimento do tumor / Abstract: Nowadays, prostate cancer is the second most common man cancer diagnosed in Brazil. Predicting the cancer stage from available clinical information to decide the therapy to be used is hard work. ln this study a mathematical model is developed to assist the physician in this task. The fuzzy sets theory provides effective tools to handle and manipulate imprecise data and to make decisions based on such data. As imprecision is a characteristic of medical concepts, this theory is utilized not oniy to develop the model as to develop the methodology for its evaluation, based on ROC (Receiver Operating Characteristic) analysis. To evaluate its performance, data from the American Cancer lnstitute were used. The results indicate that the model is able to discriminate patients with organ-confined disease from those with non-confined cancer. In addition, considering the growth rate as an uncertain, changeable parameter in the population, a model to describe the tumor growth is suggested. / Doutorado / Automação / Doutor em Engenharia Elétrica
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The principle of inclusion-exclusion and möbius function as counting techniques in finite fuzzy subsetsTalwanga, Matiki January 2009 (has links)
The broad goal in this thesis is to enumerate elements and fuzzy subsets of a finite set enjoying some useful properties through the well-known counting technique of the principle of inclusion-exclusion. We consider the set of membership values to be finite and uniformly spaced in the real unit interval. Further we define an equivalence relation with regards to the cardinalities of fuzzy subsets providing the Möbius function and Möbius inversion in that context.
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Studies of equivalent fuzzy subgroups of finite abelian p-Groups of rank two and their subgroup latticesNgcibi, Sakhile Leonard January 2006 (has links)
We determine the number and nature of distinct equivalence classes of fuzzy subgroups of finite Abelian p-group G of rank two under a natural equivalence relation on fuzzy subgroups. Our discussions embrace the necessary theory from groups with special emphasis on finite p-groups as a step towards the classification of crisp subgroups as well as maximal chains of subgroups. Unique naming of subgroup generators as discussed in this work facilitates counting of subgroups and chains of subgroups from subgroup lattices of the groups. We cover aspects of fuzzy theory including fuzzy (homo-) isomorphism together with operations on fuzzy subgroups. The equivalence characterization as discussed here is finer than isomorphism. We introduce the theory of keychains with a view towards the enumeration of maximal chains as well as fuzzy subgroups under the equivalence relation mentioned above. We discuss a strategy to develop subgroup lattices of the groups used in the discussion, and give examples for specific cases of prime p and positive integers n,m. We derive formulas for both the number of maximal chains as well as the number of distinct equivalence classes of fuzzy subgroups. The results are in the form of polynomials in p (known in the literature as Hall polynomials) with combinatorial coefficients. Finally we give a brief investigation of the results from a graph-theoretic point of view. We view the subgroup lattices of these groups as simple, connected, symmetric graphs.
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Counting of finite fuzzy subsets with applications to fuzzy recognition and selection strategiesTalwanga, Matiki January 2015 (has links)
The counting of fuzzy subsets of a finite set is of great interest in both practical and theoretical contexts in Mathematics. We have used some counting techniques such as the principle of Inclusion-Exclusion and the Mõbius Inversion to enumerate the fuzzy subsets of a finite set satisfying different conditions. These two techniques are interdependent with the M¨obius inversion generalizing the principle of Inclusion-Exclusion. The enumeration is carried out each time we redefine new conditions on the set. In this study one of our aims is the recognition and identification of fuzzy subsets with same features, characteristics or conditions. To facilitate such a study, we use some ideas such as the Hamming distance, mid-point between two fuzzy subsets and cardinality of fuzzy subsets. Finally we introduce the fuzzy scanner of elements of a finite set. This is used to identify elements and fuzzy subsets of a set. The scanning process of identification and recognition facilitates the choice of entities with specified properties. We develop a procedure of selection under the fuzzy environment. This allows us a framework to resolve conflicting issues in the market place.
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Fire Detection Robot using Type-2 Fuzzy Logic Sensor FusionLe, Xuqing January 2015 (has links)
In this research work, an approach for fire detection and estimation robots is presented. The approach is based on type-2 fuzzy logic system that utilizes measured temperature and light intensity to detect fires of various intensities at different distances. Type-2 fuzzy logic system (T2 FLS) is known for not needing exact mathematic model and for its capability to handle more complicated uncertain situations compared with Type-1 fuzzy logic system (T1 FLS). Due to lack of expertise for new facilities, a new approach for training experts’ expertise and setting up T2 FLS parameters from pure data is discussed in this thesis. Performance of both T1 FLS and T2 FLS regarding to same fire detection scenario are investigated and compared in this thesis. Simulation works have been done for fire detection robot of both free space scenario and new facility scenario to illustrate the operation and performance of proposed type-2 fuzzy logic system. Experiments are also performed using LEGO MINDSTROMS NXT robot to test the reliability and feasibility of the algorithm in physical environment with simple and complex situation.
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Placement of Utilities in Right of Way Model using Fuzzy and Probabilistic Objective CoefficientsShanmugam, Vijayakumar S 03 April 2003 (has links)
This thesis focuses on a decision-making model for finding the locations for placement of utilities in roadway corridors. In recent years, there has been a rapid growth in the volume of traffic on roadways and in the number of utilities placed in Right of Ways. The increase in the demand for utilities is making it more difficult to place all the utilities within the Right of Way and also provide safe roads and highways with good carrying capacity. The public agencies approving the location for utilities are now using a first come first served method, which provide neither an efficient nor good economic solution. This model considers all the utilities within the corridor as a single system, including factors like installation costs, maintenance costs and also some future factors such as accident costs. A weighted coefficient optimization approach is used to find the solution in this model. These costs are modeled as fuzzy numbers or probabilistic random numbers depending on their characteristics. This algorithm will locate each utility at all its possible locations and find the total cost of all the utilities at all these locations, i.e. cost of the system. The least cost locations among all the possible locations are the good locations for utilities in the utility system. When utilities are placed in these locations the overall cost of the system will be lower compared to other locations. This model provides a flexible and interactive method for finding cost saving locations for the utilities in the highway corridor. Users will be able to change the parameters of the utility system according to their requirements and get reduced cost solutions.
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Characterizations, solution techniques, and some applications of a class of semi-infinite and fuzzy set programming problemsParks, Melvin Lee January 1981 (has links)
This dissertation examines characteristics of a class of semi-infinite linear programming problems designated as C/C semi-infinite linear programming problems. Semi-infinite programming problems which belong to this class are problems of the form
[See document]
where S is a compact, convex subset of Euclidean m space and u<sub>i</sub> : S→R, i=1,...,n are strictly concave functions while u <sub> n+1</sub> : S→R is convex.
Certain properties of the C/C semi-infinite linear programming problems give rise to efficient solution techniques. The solution techniques are given as well as examples of their use.
Of significant importance is the intimate relationship between the class of C/C semi-infinite linear programming problems and certain convex fuzzy set programming problems. The fuzzy set programming problem is defined as
[See document]
The convex fuzzy set programming problem is transformed to an equivalent semi-infinite linear programming problem. Characterizations of the membership functions are given which cause the equivalent semi-infinite linear programming problems to fall within the realm of C/C semi-infinite linear programming problems. Some extensions of the set inclusive programming problem are also given. / Ph. D.
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An investment analysis model using fuzzy set theorySaboo, Jai Vardhan January 1989 (has links)
Traditional methods for evaluating investments in state-of-the-art technology are sometimes found lacking in providing equitable recommendations for project selection. The major cause for this is the inability of these methods to handle adequately uncertainty and imprecision, and account for every aspect of the project, economic and non-economic, tangible and intangible. Fuzzy set theory provides an alternative to probability theory for handling uncertainty, while at the same time being able to handle imprecision. It also provides a means of closing the gap between the human thought process and the computer, by enabling the establishment of linguistic quantifiers to describe intangible attributes. Fuzzy set theory has been used successfully in other fields for aiding the decision-making process.
The intention of this research has been the application of fuzzy set theory to aid investment decision making. The research has led to the development of a structured model, based on theoretical algorithms developed by Buckley and others. The model looks at a project from three different standpoints- economic, operational, and strategic. It provides recommendations by means of five different values for the project desirability, and results of two sensitivity analyses. The model is tested on a hypothetical case study. The end result is a model that can be used as a basis for promising future development of investment analysis models. / Master of Science / incomplete_metadata
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Applications of fuzzy logic to mechanical reliability analysisTouzé, Patrick A. 14 March 2009 (has links)
In this work, fuzzy sets are used to express data or model uncertainty in structural systems where random numbers used to be utilized. / Master of Science
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A fuzzy set paradigm for conceptual system design evaluationVerma, Dinesh 26 October 2005 (has links)
A structured and disciplined system engineering process is essential for the efficient and effective development of products and systems which are both responsive to customer needs and globally competitive. Rigor and discipline during the later life-cycle phases of design and development (preliminary and detailed) cannot compensate for an ill-conceived system concept and for premature commitments made during the conceptual design phase. This significance notwithstanding, the nascent stage of system design has been largely ignored by the research and development community.
This research is unique. It focuses on conceptual system design and formalizes analysis and evaluation activities during this important life-cycle phase. The primary goal of developing a conceptual design analysis and evaluation methodology has been achieved, including complete integration with the system engineering process. Rather than being a constraint, this integration led to a better definition of conceptual design activity and the coordinated progression of synthesis, analysis, and evaluation.
Concepts from fuzzy set theory and the calculus of fuzzy arithmetic were adapted to address and manipulate imprecision and subjectivity. A number of design decision aids were developed to reduce the gap between commitment and project specific knowledge, to facilitate design convergence, and to help realize a preferred system design concept. / Ph. D.
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