Fuzzy environmental quality index

This paper presents the construction of a fuzzy environmental quality index for decision support in municipal environmental management. Five groups of indicators were selected in order to obtain an equation that best represented reality in terms of environmental quality. The calculation was carried out using fuzzy mathematical concepts, with the aid of the package Fuzzy Logical Toolbox 2.1 for Matlab ® 6.1, which provides functions and some applications of the theory of fuzzy sets. The work seeks to create a method of inference concerning the nature of urban areas that are unsustainable with respect to the environment, an issue that is often relegated to the background during public policy discussions. The development of this index, together with its implementation and dissemination, could improve public awareness of environmental issues, and promote mobilization towards the use of best practices in local development. © 2010 IEEE.

A proposal for reliability evaluation of components on electric power distribution system integrating probabilistic models and fuzzy inference systems

The system reliability depends on the reliability of its components itself. Therefore, it is necessary a methodology capable of inferring the state of functionality of these components to establish reliable indices of quality. Allocation models for maintenance and protective devices, among others, have been used in order to improve the quality and availability of services on electric power distribution systems. This paper proposes a methodology for assessing the reliability of distribution system components in an integrated way, using probabilistic models and fuzzy inference systems to infer about the operation probability of each component. © 2012 IEEE.

Novel expert system for defining power quality compensators

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Social support and infant malnutrition: a case-control study in an urban area of Southeastern Brazil

The relationship between malnutrition and social support was first suggested in the mid-1990s. Despite its plausibility, no empirical studies aimed at obtaining evidence of this association could be located. The goal of the present study was to investigate such evidence. A case-control study was carried out including 101 malnourished children (weight-for-age National Center for Health Statistics/WHO 5th percentile) aged 12-23 months, who were compared with 200 well-nourished children with regard to exposure to a series of factors related to their social support system. Univariate and multiple logistic regressions were carried out, odds ratios being adjusted for per capita family income, mother's schooling, and number of children. The presence of an interaction between income and social support variables was also tested. Absence of a partner living with the mother increased risk of malnutrition (odds ratio 2.4 (95 % CI 1.19, 4.89)), even after adjustment for per capita family income, mother's schooling, and number of children. The lack of economic support during adverse situations accounted for a very high risk of malnutrition (odds ratio 10.1 (95 % CI 3.48, 29.13)) among low-income children, but had no effect on children of higher-income families. Results indicate that receiving economic support is an efficient risk modulator for malnutrition among low-income children. In addition, it was shown that the absence of a partner living with the mother is an important risk factor for malnutrition, with an effect independent from per capita family income, mother's schooling, and number of children.

The impact of soybean expansion on mammal and bird, in the Balsas region, north Brasilian Cerrado

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Simulation of active control using fuzzy logic applied to a pulse combustor

This work analyzes an active fuzzy logic control system in a Rijke type pulse combustor. During the system development, a study of the existing types of control for pulse combustion was carried out and a simulation model was implemented to be used with the package Matlab and Simulink. Blocks which were not available in the simulator library were developed. A fuzzy controller was developed and its membership functions and inference rules were established. The obtained simulation showed that fuzzy logic is viable in the control of combustion instabilities. The obtained results indicated that the control system responded to pulses in an efficient and desirable way. It was verified that the system needed approximately 0.2 s to increase the tube internal pressure from 30 to 90 mbar, with an assumed total delay of 2 ms. The effects of delay variation were studied. Convergence was always obtained and general performance was not affected by the delay. The controller sends a pressure signal in phase with the Rijke tube internal pressure signal, through the speakers, when an increase the oscillations pressure amplitude is desired. On the other hand, when a decrease of the tube internal pressure amplitude is desired, the controller sends a signal 180° out of phase.

Application of an iterative method and an evolutionary algorithm in fuzzy optimization

This work develops two approaches based on the fuzzy set theory to solve a class of fuzzy mathematical optimization problems with uncertainties in the objective function and in the set of constraints. The first approach is an adaptation of an iterative method that obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. The second one is a metaheuristic approach that adapts a standard genetic algorithm to use fuzzy numbers. Both approaches use a decision criterion called satisfaction level that reaches the best solution in the uncertain environment. Selected examples from the literature are presented to compare and to validate the efficiency of the methods addressed, emphasizing the fuzzy optimization problem in some import-export companies in the south of Spain. © 2012 Brazilian Operations Research Society.

Implementation of an AC model for transmission expansion planning considering reliability constraints

In this paper, a hybrid heuristic methodology that employs fuzzy logic for solving the AC transmission network expansion planning (AC-TEP) problem is presented. An enhanced constructive heuristic algorithm aimed at obtaining a significant quality solution for such complicated problems considering contingency is proposed. In order to indicate the severity of the contingency, 2 performance indices, namely the line flow performance index and voltage performance index, are calculated. An interior point method is applied as a nonlinear programming solver to handle such nonconvex optimization problems, while the objective function includes the costs of the new transmission lines as well as the real power losses. The performance of the proposed method is examined by applying it to the well-known Garver system for different cases. The simulation studies and result analysis demonstrate that the proposed method provides a promising way to find an optimal plan. Obtaining the best quality solution shows the capability and the viability of the proposed algorithm in AC-TEP. © Tübi̇tak..

Sistema de informação sobre violência urbana (SiViU) como apoio à tomada de decisão em políticas públicas de cidades médias

Pós-graduação em Geografia - IGCE

Estudo exploratório da integração de processos em uma instituição pública de ensino superior a partir das funcionalidades de um sistema de gestão de processos de negócio

Pós-graduação em Engenharia de Produção - FEB

Sistema baseado em regras fuzzy do tipo Takagi-Sugeno aplicado a ecos de radares meteorológicos

Pós-graduação em Ciências Ambientais - Sorocaba