Orientador: Laécio Carvalho de Barros / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica / Made available in DSpace on 2018-08-20T13:51:43Z (GMT). No. of bitstreams: 1 Bacani_Felipo_M.pdf: 2024723 bytes, checksum: badf6f6540880c17a7c2ffbf9d211db0 (MD5) Previous issue date: 2012 / Resumo: O presente trabalho tem por objetivo aplicar a teoria de conjuntos fuzzy a modelos de predição (inferência) de dados. O modelo utilizado baseia-se fortemente nas relações fuzzy em espaços contínuos (caso não matricial) e na regra de inferência modus ponens, utilizando t-normas (que neste contexto são similares à operação de cópula em estatística). é do modus ponens que surge o caráter \condicional" de alguns dos termos envolvidos, e a partir daí é que a analogia com a inferência bayesiana é feita. Entretanto, são apenas analogias conceituais: o presente trabalho não lida com nenhuma distribuição de probabilidades. Na verdade, conjuntos fuzzy são tratados como distribuições de possibilidades. A metodologia proposta é utilizada com o objetivo de tornar mais precisa a previsão de um especialista, levando em conta um registro histórico sobre o problema. Ou seja, melhorar a previsão do especialista levando em conta o que ocorreu com as previsões anteriores. Para testar a metodologia, utilizou-se dados meteorológicos de temperatura e umidade provenientes de lavouras de café. Os dados foram gentilmente cedidos pelo CEPAGRI/Unicamp. Os testes foram avaliados através de dois indicadores estatísticos, 'D' de Willmott e MAPE (Mean Absolute Percentage Error), mostrarando que a metodologia foi capaz de melhorar a previsão do especialista na maioria das situações estudadas / Abstract: This work aims to apply Fuzzy set theory in forecasting models. The modeling methodology is largely based on continuous fuzzy relations and in the modus ponens, using t-norms (that in this context are similar to the copula operations in statistics). It is from the modus ponens that arises the \conditional" interpretation of some of the terms involved, and it is from there that an analogy with the Bayesian inference is made. However, it is only a conceptual analogy: this work do not involve probability distributions. Actually, fuzzy sets are treated as possibility distributions. The methodology is used to improve the accuracy of expert forecasting considering a historic data. Namely, to improve expert prediction based on past performance. To evaluate the test the methodology, temperature and humidity data from coffee crop was used. The data was gently provided by CEPAGRI/Unicamp. Results were validated using two different statistic indicators, MAPE (mean absolute percentage error) and Willmott 'D', showing that the methodology was able to improve the expert prediction in most cases / Mestrado / Matematica Aplicada / Mestre em Matemática Aplicada

Orientador : Sergio Nascimento Bordalo / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-02T22:23:03Z (GMT). No. of bitstreams: 1 Bezerra_MuriloValenca_M.pdf: 5666584 bytes, checksum: 4e3ea2021ba8f915134ec420233a656f (MD5) Previous issue date: 2002 / Resumo: A avaliação do método de elevação para determinada aplicação representa um passo importante no gerenciamento da produção de petróleo. Cada uma das tecnologias existentes apresenta vantagens e desvantagens específicas em termos de projeto e configuração dos equipamentos, custos de aquisição, confiabilidade, procedimentos de operação, intervenção e reparos. As atividades de análise e seleção de um método de elevação envolvem a pesquisa e organização de várias informações relativas ao reservatório, ao projeto do poço e às características dos fluidos que serão produzidos, além das considerações de especialistas envolvidos com a produção dos poços. O presente trabalho procura reunir estas informações e sistematizar os diferentes parâmetros envolvidos na análise e seleção de métodos de elevação, e propõe uma metodologia utilizando conceitos da lógica nebulosa, que possa simular o processo de avaliação realizado por especialistas ao considerar o contexto de produção existente / Abstract: The evaluation of artificial lift methods for a given field application represents an important step in the oil production management. There are some advantages and disadvantages for each of the technology applied, covering a number of different attributes such as well design, equipment installation and reability, capital costs, operation and maintenance practices. The activities of evaluation and selection demands research and organization in order to identify the necessary information from the reservoir, fluids and well design which will help the experts to decide. This work aims to set a artificial lift evaluation methodology which can be able to simulate the expert knowledge using fuzzy set and fuzzy logic theory / Mestrado / Mestre em Ciências e Engenharia de Petróleo

L'Extraction de connaissances dans les bases de données est un processus qui vise à extraire un ensemble réduit de connaissances à fortes valeurs ajoutées à partir d'un grand volume de données. La fouille de données, l'une des étapes de ce processus, regroupe un certain nombre de taches, telles que : le clustering, la classification, l'extraction de règles d'associations, etc.La problématique d'extraction de règles d'association nécessite l'étape d'extraction de motifs fréquents. Nous distinguons plusieurs catégories de motifs : les motifs classiques, les motifs flous, les motifs graduels, les motifs séquentiels. Ces motifs diffèrent selon le type de données à partir desquelles l'extraction est faite et selon le type de corrélation qu'ils présentent.Les travaux de cette thèse s'inscrivent dans le contexte d'extraction de motifs graduels, flous et clos. En effet, nous définissons de nouveaux systèmes de clôture de la connexion de Galois relatifs, respectivement, aux motifs flous et graduels. Ainsi, nous proposons des algorithmes d'extraction d'un ensemble réduit pour les motifs graduels et les motifs flous.Nous proposons également deux approches d'extraction de motifs graduels flous, ceci en passant par la génération automatique des fonctions d'appartenance des attributs.En se basant sur les motifs flous clos et graduels clos, nous définissons des bases génériques de toutes les règles d'association graduelles et floues. Nous proposons également un système d'inférence complet et valide de toutes les règles à partir de ces bases. / Knowledge discovery in databases is a process aiming at extracting a reduced set of valuable knowledge from a huge amount of data. Data mining, one step of this process, includes a number of tasks, such as clustering, classification, of association rules mining, etc.The problem of mining association rules requires the step of frequent patterns extraction. We distinguish several categories of frequent patterns: classical patterns, fuzzy patterns, gradual patterns, sequential patterns, etc. All these patterns differ on the type of the data from which the extraction is done and the type of the relationship that represent.In this thesis, we particularly contribute with the proposal of fuzzy and gradual patterns extraction method.Indeed, we define new systems of closure of the Galois connection for, respectively, fuzzy and gradual patterns. Thus, we propose algorithms for extracting a reduced set of fuzzy and gradual patterns.We also propose two approaches for automatically defining fuzzy modalities that allow obtaining relevant fuzzy gradual patterns.Based on fuzzy closed and gradual closed patterns, we define generic bases of fuzzy and gradual association rules. We thus propose a complet and valid inference system to derive all redundant fuzzy and gradual association rules.

This diploma thesis deals with the design of models for rating of suppliers in public procurement tender. Describes used methods and procedures for the rating of suppliers using fuzzy logic and fuzzy sets. The goal is to design a functional and comprehensible model, possible to use repeatedly with small variations.

This master thesis deals with the use of fuzzy logic to evaluate the quality customers of the company TILL Ltd. The evaluation is done using Microsoft EXCEL and MathWorks MATLAB, using the main attributes and characteristics of customers. The thesis results are clear and functional fuzzy models that can be used to effectively evaluate potential and existing customers.

Master's thesis deals with a design of models that allow selection of the most suitable contractor for construction of a company's new branch. Models are based on utilization of basic principles of fuzzy logic. Proposed fuzzy models allow evaluation of individual offers and serve as support in decision-making process.

The thesis focuses on European countries which underwent so-called partial democratization in the last quarter of the 20th century. It starts from the polemic with Mansfield and Snyder who claim that a (partial) democratization leads to war. The development in Europe of the last quarter of the 20th century, however, seems to contradict this notion. The aim of the thesis is, thus, to contribute to the debate of war-proneness of democratizing states by answering the following question: What caused that the democratization did not lead to war in many cases? Due to the nature of the research question as well as to the number of cases (i.e. 20) the method applied here is qualitative comparative analysis using the so-called fuzzy set method. The application of this method as such is a secondary aim of the thesis. Possible causal conditions of the absence of war which are under study here also derive mostly from the conclusions made by Mansfield and Snyder. The main focus is put on the so-called golden parachute. Among other causes are strong institutions - conceptualized here as weak and weakened executive, political integration into international community, duration of independent statehood and at least some experience with democracy - and developed economy - conceptualized through GDP, economic...

<p>Intuicionistički rasplinuti skupovi su već proučavani i definisani u kontekstu mrežnovrednosnih struktura, ali svaka od postojećih definicija imala je odgovarajuće nedostatke. U ovom radu razvijena je definicija intuicionističkog poset-vrednosnog rasplinutog skupa, kojom se poset predstavlja kao podskup distributivne mreže. Na ovaj način možemo ispitivati funkcije pripadanja i nepripadanja i njihove odnose bez upotrebe komplementiranja na posetu. Takođe, u ovako postavljenim okvirima, svaki poset (a samim tim i mreža) može biti kodomen intuicionističkog rasplinutog skupa (čime se isključuje uslov ograničenosti poseta). Primenom uvedene definicije razmatrane su IP-vrednosne rasplinute relacije, x-blokovi ovih relacija i familije<br />njihovih nivoa.Razvijene su jake poset vrednosne relacije reciprociteta koje&nbsp; predstavljaju uop&scaron;tenje relacija reciprociteta sa intervala [0,1]. Pokazano je da ovakve relacije imaju svojstva slična poset-vrednosnim relacijama preferencije. Međutim, postoje velika ograničenja za primenu ovakvih relacija jer su zahtevi dosta jaki.<br />Uvedene su IP-vrednosne relacije reciprociteta koje se mogu definisati za veliku klasu poseta.Ovakve relacije pogodne su za opisivanje preferencija. Posmatrana je intuicionistička poset-vrednosna relacija preferencije, koja je refleksivna rasplinuta relacija, nad skupom alternativa. U samom procesu vi&scaron;ekriterijumskog odlučivanja<br />može se pojaviti situacija kada alternative nisu međusobno uporedive u odnosu na relaciju preferencije, kao i nedovoljna određenost samih alternativa. Da bi se prevazi&scaron;li ovakvi problemi uvodi se intuicionistička poset-vrednosna relacija preferencije kao intuicionistička rasplinuta relacija na skupu alternativa sa vrednostima u uređenom skupu. Analizirana su neka njena svojstva. Ovakav model pogodan je za upoređivanje alternativa koje nisu, nužno, u linearnom poretku. Dato je nekoliko opravdanja za uvodjenje oba tipa definisanih relacija. Jedna od mogućnosti jeste preko mreže intervala elemenata iz konačnog lanca S, a koji predstavljaju ocene određene alternative. Relacije preferencije mogu uzimati vrednosti sa ove mreže i time se može prevazići nedostatak informacija ili neodlučnost donosioca odluke.</p> / <p>Intuitionistic fuzzy sets have already been explored in depth and defined in the context of lattice-valued intuitionistic fuzzy sets, however, every existing definition has certain drawbacks. In this thesis, a definition of poset-valued intuitionistic fuzzy sets is developed, which introduces a poset as a subset of a distributive lattice. In this manner, functions of membership and non-membership can be examined as well as&nbsp; their relations without using complement in the poset. Also, in such framework, each poset (and the lattice) can be a co-domain of an intuitionistic fuzzy set (which excludes the condition of the bounded poset). Introduced definition defines IP-valued fuzzy relations, x-blocks of these relations andfamilies of their levels. Strong IP-valued&nbsp; reciprocialy relations have been developed as a generalization of reciprocal relations from interval [0,1]. It has been shown that these relations have properties similar to the P-valued preferences relations. However, there are great constraints on the application of these relations because the requirements are quite strong.IP- valued reciprocial relations have been introduced, which can be defined for a large class of posets. Such relations are suitable for describing preferences.An intuitionistic poset-valued preference relation, which is a reflexive fuzzy relation, over the set of&nbsp; alternatives, has been examined. In the process of a multi-criteria decision making, a situation can occur that the alternatives cannot be compared by the preference relation, as well as insufficient determination of the mentioned alternatives. In order to overcome similar problems, we have introduced an intuitionistic poset-valued preference relation as an intuitionistic fuzzy set over the set of alternatives with values in a certain poset. We have analyzed some its performances. This model is suitable for comparing alternatives which are not necessarily linearly ordered. There are several justifications for the introduction of&nbsp; both types of defined relations. One of the possibilities is via the lattice of the intervals&nbsp; of elements from the finite chain S, which represent the preference of a particular alternative. Preferences relations can take values from this lattice and this can overcome the lack of informations or the decisiveness of the decision maker.</p>

The number of trips on highways and urban networks has significantly increased in the recent decades in many cities across the world. At the same time, the road network capacities have not kept up with this increase in travel demand. Urban road networks in many countries are severely congested, resulting in increased travel times, increased number of stops, unexpected delays, greater travel costs, inconvenience to drivers and passengers, increased air pollution and noise level, and increased number of traffic accidents. Expanding traffic network capacities by building more roads is extremely costly as well as environmentally damaging. More efficient usage of the existing supply is vital in order to sustain the growing travel demand. Travel Demand Management (TDM) techniques involving various strategies that increase the travel choices to the consumers have been proposed by the researchers, planners, and transportation professionals. TDM helps create a well balanced, less automobile dependent transportation system. In the past, several TDM strategies have been proposed and implemented in several cities around the world. All these TDM strategies, with very few exceptions, are static in nature. For example, in the case of congestion pricing, the toll schedules are previously set and are implemented on a daily basis. The amount of toll does not vary dynamically, with time of day and level of traffic on the highway (though the peak period tolls are different from the off-peak tolls, they are still static in the sense that the tolls don't vary continuously with time and level of traffic). The advent of Electronic Payment Systems (EPS), a branch of the Intelligent Transportation Systems (ITS), has made it possible for the planners and researchers to conceive of dynamic TDM strategies. Recently, few congestion pricing projects are beginning to adopt dynamic tolls that vary continuously with the time of day based on the level of traffic (e.g. I-15 value pricing in California). Dynamic TDM is a relatively new and unexplored topic and the future research attempts to provide answers to the following questions: 1) How to propose and model a Dynamic TDM strategy, 2) What are the advantages of Dynamic TDM strategies as compared to their Static counterparts, 3) What are the benefits and costs of implementing such strategies, 4) What are the travel impacts of implementing Dynamic TDM strategies, and 5) How equitable are the Dynamic TDM strategies as compared to their Static counterparts. This dissertation attempts to address question 1 in detail and deal with the remaining questions to the extent possible, as questions 2, 3, 4, and 5, can be best answered only after some real life implementation of the proposed Dynamic TDM strategies. Two novel Dynamic TDM strategies are proposed and modeled in this dissertation -- a) Dynamic Congestion Pricing and b) Dynamic Highway Space Inventory Control System. In the first part, dynamic congestion pricing, a real-time road pricing system in the case of a two-link parallel network is proposed and modeled. The system that is based on a combination of Dynamic Programming and Neural Networks makes "on-line" decisions about road toll values. In the first phase of the proposed model, the best road toll sequences during certain time period are calculated off-line for many different patterns of vehicle arrivals. These toll sequences are computed using Dynamic Programming approach. In the second phase, learning from vehicle arrival patterns and the corresponding optimal toll sequences, neural network is trained. The results obtained during on-line tests are close to the best solution obtained off-line assuming that the arrival pattern is known. Highway Space Inventory Control System (HSICS), a relatively new demand management concept, is proposed and modeled in the second half of this dissertation. The basic idea of HSICS is that all road users have to make reservations in advance to enter the highway. The system allows highway operators to make real-time decisions whether to accept or reject travellers' requests to use the highway system in order to achieve certain system-wide objectives. The proposed HSICS model consists of two modules -- Highway Allocation System (HAS) and the Highway Reservation System (HRS). The HAS is an off-line module and determines the maximum number of trips from each user class (categorized based on time of departure, vehicle type, vehicle occupancy, and trip distance) to be accepted by the system given a pre-defined demand. It develops the optimal highway allocations for different traffic scenarios. The "traffic scenarios-optimal allocations" data obtained in this way enables the development of HRS. The HRS module operates in the on-line mode to determine whether a request to make a trip between certain origin-destination pair in certain time interval is accepted or rejected. / Ph. D.

In the early design stage of automotive joints, fuzziness is omnipresent because designers reason in non quantitative terms and deal with imprecise data. Consequently, they need a design methodology that accounts for vagueness. Fuzzy sets and utility theory are appropriate tools because they link the vagueness in a problem formulation and the precise nature of mathematical models. Fuzzy multiobjective optimizations are performed on an automotive joint to maximize the overall designer's satisfaction. Several methods that account for all the attributes and the fuzziness in the goals are used. Three multiobjective fuzzy approaches, namely, the conservative, the aggressive and the moderate methods are investigated. Utility theory is also considered to optimize the joint. One of the performance attributes of the joint, the stiffness, is evaluated rapidly using approximate tools (neural networks and response surface polynomials) to overcome the high computational cost of PEA, which is traditionally used to calculate the stiffness. This research compares fuzzy set methods and utility theory in design of automotive components. These methods are applied on two examples where the same B-pillar to rocker joint of an actual car is optimized. Fuzzy set based methods and utility theory appear to be suitable for optimizing automotive joints because they allow for trading conflicting objectives. Fuzzy set based methods avoid trading objectives to the point of having a level of satisfaction equal to zero. When using the fuzzy set based methods investigated in this research, the trade-offs among the attributes are not explicitly defined by the user. Utility theory requires the user to quantify precisely the trade-offs among the attributes. When using utility theory, the overall satisfaction of a design can be non zero even if one or more attributes has a level of satisfaction equal to zero. The approximate tools enable us to perform the optimization efficiently by reducing considerably the computational cost. / Master of Science