Sistema especialista para a monitoração do processo de degradação de medidores tipo indução de energia elétrica ativa

This paper presents a methodology and software for hazard rate analysis of induction type watt-hour meters, considering the main variables related with the degradation process of these meters, for the Elektro Electricity and Services SA. The modeling developed to calculate the watt-hour meters hazard rate was implemented in a tool through a user friendly platform, in Delphi language, enabling not only hazard rate analysis, but also a classification by risk range, localization of installation for the analyzed meters, and, allowing, through an expert system, the sampling of induction type watt-hour meters, based on the model risk developed with artificial intelligence, with the mainly goal of follow and manage the process of degradation, maintenance and replacement of these meters. © 2010 IEEE.

Mapeamento da sensibilidade ambiental a derramentos de óleo para a região costeira de São Sebastião e Caraguatatuba, litoral norte de São Paulo (SP), com uso de modelagem em SIG de sistema especialista baseado em conhecimento e árvore de decisão

Pós-graduação em Geociências e Meio Ambiente - IGCE

Sistema especialista para automação do processo de aeração de grãos de milho em pequenas propriedades

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Auxílio a tomada de decisão na inclusão de sobressalentes de manutenção em estoque utilizando um sistema especialista fuzzy

In the current economic scenario of constant changes, industries seek to increase their profitability decreasing inventory levels. Maintenance and maintenance management, combined with the inventory management of spare parts, has assumed a position of competitive advantage in business. Stock only what you need has become a difficult decision for managers, who are faced with the lack of models and criteria to assist this decision-making. This work proposes a method which supports decision making, on a MATLAB modeling, using criteria established by an expert and his maintenance workers team, focusing on no regular demand of spare parts. The proposed model was adequate to the needs of the company and the maintenance manager in the decision on the storage

Nova versão do sistema de avaliação de terras - SIAT

O SIAT é um sistema especialista para Avaliação de Terras derivado do MicroLEIS - Land Evaluation Information System desenvolvido na Espanha. Na primeira versão, as 12 variáveis foram adaptadas e ajustadas para condições tropicais, assim como a estrutura do programa e o banco de dados. Os testes de campo mostraram que os melhores resultados foram obtidos para escalas próximas de 1:100.000. Nesta segunda versão, os intervalos das variáveis foram redefinidos e uma interface de comunicação com o SIG IDRISI foi introduzida, permitindo a troca de dados entre os dois programas. Outra modificação importante foi a adoção de uma equação para calcular a erosividade no lugar de mapa apresentado no Manual do Usuário. Os testes de campo mostraram que o uso do SIAT é agora mais funcional, com melhor resolução, permitindo trabalhar com escalas em torno de 1:50.000, além de ser adaptável para todo o território brasileiro. A versão do SIAT pode ser obtida pelo endereço www.rc.unesp.br/igce/ceapla/biblioteca/softwares/siat.html.

Proposta de etapas de implementação de WMS: um estudo de caso em um varejista moveleiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelo fuzzy estimando tempo de internação por doenças cardiovasculares

Abstract A fuzzy linguistic model based on the Mamdani method with input variables, particulate matter, sulfur dioxide, temperature and wind obtained from CETESB with two membership functions each was built to predict the average hospitalization time due to cardiovascular diseases related to exposure to air pollutants in São José dos Campos in the State of São Paulo in 2009. The output variable is the average length of hospitalization obtained from DATASUS with six membership functions. The average time given by the model was compared to actual data using lags of 0 to 4 days. This model was built using the Matlab v. 7.5 fuzzy toolbox. Its accuracy was assessed with the ROC curve. Hospitalizations with a mean time of 7.9 days (SD = 4.9) were recorded in 1119 cases. The data provided revealed a significant correlation with the actual data according to the lags of 0 to 4 days. The pollutant that showed the greatest accuracy was sulfur dioxide. This model can be used as the basis of a specialized system to assist the city health authority in assessing the risk of hospitalizations due to air pollutants.

Preventive diagnosis of dairy cow lameness

This research aimed to develop a Fuzzy inference based on expert system to help preventing lameness in dairy cattle. Hoof length, nutritional parameters and floor material properties (roughness) were used to build the Fuzzy inference system. The expert system architecture was defined using Unified Modelling Language (UML). Data were collected in a commercial dairy herd using two different subgroups (H-1 and H-2), in order to validate the Fuzzy inference functions. The numbers of True Positive (TP), False Positive (FP), True Negative (TN), and False Negative (FN) responses were used to build the classifier system up, after an established gold standard comparison. A Lesion Incidence Possibility (LIP) developed function indicates the chances of a cow becoming lame. The obtained lameness percentage in H-1 and H-2 was 8.40% and 1.77%, respectively. The system estimated a Lesion Incidence Possibility (LIP) of 5.00% and 2.00% in H-1 and H-2, respectively. The system simulation presented 3.40% difference from real cattle lameness data for H-1, while for H-2, it was 0.23%; indicating the system efficiency in decision-making.

Sistema fuzzy para estimativa do bem-estar de matrizes pesadas

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

O sistema agroindustrial do leite na região de Presidente Prudente-SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)