Performance assessment of a wind energy conversion system using a hierarchical controller structure

This paper deals with a hierarchical structure composed by an event-based supervisor in a higher level and two distinct proportional integral (PI) controllers in a lower level. The controllers are applied to a variable speed wind energy conversion system with doubly-fed induction generator, namely, the fuzzy PI control and the fractional-order PI control. The event-based supervisor analyses the operation state of the wind energy conversion system among four possible operational states: park, start-up, generating or brake and sends the operation state to the controllers in the lower level. In start-up state, the controllers only act on electric torque while pitch angle is equal to zero. In generating state, the controllers must act on the pitch angle of the blades in order to maintain the electric power around the nominal value, thus ensuring that the safety conditions required for integration in the electric grid are met. Comparisons between fuzzy PI and fractional-order PI pitch controllers applied to a wind turbine benchmark model are given and simulation results by Matlab/Simulink are shown. From the results regarding the closed loop point of view, fuzzy PI controller allows a smoother response at the expense of larger number of variations of the pitch angle, implying frequent switches between operational states. On the other hand fractional-order PI controller allows an oscillatory response with less control effort, reducing switches between operational states. (C) 2015 Elsevier Ltd. All rights reserved.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Municipal solid waste management system: decision support through systems analysis

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering

Providing Adaptation for an Adaptive Hypermedia System

O ensino à distância cresceu consideravelmente nos últimos anos e a tendência é para que continue a crescer em anos vindouros. No entanto, enquanto que a maioria das plataformas de ensino à distância utilizam a mesma abordagem de ensino para todos os utilizadores, os estudantes que as usam são na realidade pessoas de diferentes culturas, locais, idades e géneros, e que possuem diferentes níveis de educação. Ao contrário do ensino à distância tradicional, os sistemas de hipermédia adaptativa educacional adaptam interface, apresentação de conteúdos e navegação, entre outros, às características, necessidades e interesses específicos de diferentes utilizadores. Apesar da investigação na área de sistemas de hipermédia adaptativa já estar bastante desenvolvida, é necessário efetuar mais desenvolvimento e experimentação de modo a determinar quais são os aspetos mais eficazes destes sistemas e avaliar o seu sucesso. A Plataforma de Aprendizagem Colaborativa da Matemática (PCMAT) é um sistema de hipermédia adaptativa educacional com uma abordagem construtivista, que foi desenvolvido com o objetivo de contribuir para a investigação na área de sistemas de hipermédia adaptativa. A plataforma avalia o conhecimento do utilizador e apresenta conteúdos e atividades adaptadas às características e estilo de aprendizagem dominante de estudantes de matemática do segundo ciclo. O desenvolvimento do PCMAT tem também o propósito de auxiliar os alunos Portugueses com a aprendizagem da matemática. De acordo com o estudo PISA 2012 da OCDE [OECD, 2014], o desempenho dos alunos Portugueses na área da matemática melhorou em relação à edição anterior do estudo, mas os resultados obtidos permanecem abaixo da média da OCDE. Por este motivo, uma das finalidades deste projeto é desenvolver um sistema de hipermédia adaptativa que, ao adequar o ensino da matemática às necessidades específicas de cada aluno, os assista com a aquisição de conhecimento. A adaptação é efetuada pelo sistema usando a informação constante no modelo do utilizador para definir um grafo de conceitos do domínio específico. Este grafo é adaptado do modelo do domínio e utilizado para dar resposta às necessidades particulares de cada aluno. Embora a trajetória inicial seja definida pelo professor, o percurso percorrido no grafo por cada aluno é determinado pela sua interação com o sistema, usando para o efeito a representação do conhecimento do aluno e outras características disponíveis no modelo do utilizador, assim como avaliação progressiva. A adaptação é conseguida através de alterações na apresentação de conteúdos e na estrutura e anotações das hiperligações. A apresentação de conteúdos é alterada mostrando ou ocultando cada um dos vários fragmentos que compõe as páginas dum curso. Estes fragmentos são compostos por diferentes objetos de aprendizagem, tais como exercícios, figuras, diagramas, etc. As mudanças efetuadas na estrutura e anotações das hiperligações têm o objetivo de guiar o estudante, apontando-o na direção do conhecimento mais relevante e mantendo-o afastado de informação inadequada. A escolha de objectos de aprendizagem adequados às características particulares de cada aluno é um aspecto essencial do modelo de adaptação do PCMAT. A plataforma inclui para esse propósito um módulo responsável pela recomendação de objectos de aprendizagem, e um módulo para a pesquisa e recuperação dos mesmos. O módulo de recomendação utiliza lógica Fuzzy para converter determinados atributos do aluno num conjunto de parâmetros que caracterizam o objecto de aprendizagem que idealmente deveria ser apresentado ao aluno. Uma vez que o objecto “ideal” poderá não existir no repositório de objectos de aprendizagem do sistema, esses parâmetros são utilizados pelo módulo de pesquisa e recuperação para procurar e devolver ao módulo de recomendação uma lista com os objectos que mais se assemelham ao objecto “ideal”. A pesquisa é feita numa árvore k-d usando o algoritmo k-vizinhos mais próximos. O modelo de recomendação utiliza a lista devolvida pelo módulo de pesquisa e recuperação para seleccionar o objecto de aprendizagem mais apropriado para o aluno e processa-o para inclusão numa das páginas Web do curso. O presente documento descreve o trabalho desenvolvido no âmbito do projeto PCMAT (PTDS/CED/108339/2008), dando relevância à adaptação de conteúdos.

Fuzzy maintenance costs of a wind turbine pitch control device

This paper deals with the problem of estimation maintenance costs for the case of the pitch controls system of wind farms turbines. Previous investigations have estimated these costs as (traditional) “crisp” values, simply ignoring the uncertainty nature of data and information available. This paper purposes an extended version of the estimation model by making use of the Fuzzy Set Theory. The results alert decision-makers to consequent uncertainty of the estimations along with their overall level, thus improving the information given to the mainte-nance support system.

Fuzzy-Clusteranalyse : Methoden zur Exploration von Daten mit fehlenden Werten sowie klassifizierten Daten

Fuzzy-Clusteranalyse, Fuzzy-Datenanlayse

Objective function based fuzzy clustering in air traffic management

Data analysis, fuzzy clustering, fuzzy rules, air traffic management

Partially supervised learning of fuzzy classification rules

Fuzzy classification, semi-supervised learning, data mining

Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods

Experten-System zur Koordination von Schutzsystemen

Expert System, Inference Engine, Protection Coordination, Protection Device

Application of Fuzzy Variables for Systems of Management Decision Support

The following article describes an approach covering the variety of opinions and uncertainties of estimates within the chosen technique of decision support. Mathematical operations used for assessment of options are traced to operations of working with functions that are used for assessment of possible options of decision-making. Approach proposed could be used within any technique of decision support based on elementary mathematical operations. In this article the above-mentioned approach is described under analytical hierarchy process.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Discovering similarities in the time use patterns of the Spanish Autonomous Communities by Fuzzy techniques

In 2000 the European Statistical Office published the guidelines for developing theHarmonized European Time Use Surveys system. Under such a unified framework,the first Time Use Survey of national scope was conducted in Spain during 2002–03. The aim of these surveys is to understand human behavior and the lifestyle ofpeople. Time allocation data are of compositional nature in origin, that is, they aresubject to non-negativity and constant-sum constraints. Thus, standard multivariatetechniques cannot be directly applied to analyze them. The goal of this work is toidentify homogeneous Spanish Autonomous Communities with regard to the typicalactivity pattern of their respective populations. To this end, fuzzy clustering approachis followed. Rather than the hard partitioning of classical clustering, where objects areallocated to only a single group, fuzzy method identify overlapping groups of objectsby allowing them to belong to more than one group. Concretely, the probabilistic fuzzyc-means algorithm is conveniently adapted to deal with the Spanish Time Use Surveymicrodata. As a result, a map distinguishing Autonomous Communities with similaractivity pattern is drawn.Key words: Time use data, Fuzzy clustering; FCM; simplex space; Aitchison distance

De novo characterization of the Timema cristinae transcriptome facilitates marker discovery and inference of genetic divergence.

Adaptation to different ecological environments can promote speciation. Although numerous examples of such 'ecological speciation' now exist, the genomic basis of the process, and the role of gene flow in it, remains less understood. This is, at least in part, because systems that are well characterized in terms of their ecology often lack genomic resources. In this study, we characterize the transcriptome of Timema cristinae stick insects, a system that has been researched intensively in terms of ecological speciation, but for which genomic resources have not been previously developed. Specifically, we obtained >1 million 454 sequencing reads that assembled into 84,937 contigs representing approximately 18,282 unique genes and tens of thousands of potential molecular markers. Second, as an illustration of their utility, we used these genomic resources to assess multilocus genetic divergence within both an ecotype pair and a species pair of Timema stick insects. The results suggest variable levels of genetic divergence and gene flow among taxon pairs and genes and illustrate a first step towards future genomic work in Timema.

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.