Modelagem fuzzy aplicada a políticas públicas: proposta de um indice municipal de qualidade ambiental

Pós-graduação em Ciências Ambientais - Sorocaba

Prediction of genomic-enabled breeding values and genome-wide association study for feedlot average daily weight gain in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Mapeamento de cianobactérias por meio da fluorescência da ficocianina e de análise geoestatística

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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.

Reproduction and management of the mangrove crab Ucides cordatus (Crustacea, Brachyura, Ucididae) at Iguape, Sao Paulo, Brazil

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

Análise geoestatística para geração de superfícies a partir de dados de clorofila-a adquiridos em transectos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Construção de uma escala para avaliação da pro ciência em conteúdos matemáticos básicos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelos para dados grupados e sensurados aplicados à área biológica: comparação usando fator de Bayes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise genética de escores visuais e sua relação com características reprodutivas de animais da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Diversidade genética em populações de Candidatus Liberibacter asiaticus determinada por marcadores SSR

Pós-graduação em Agronomia (Genética e Melhoramento de Plantas) - FCAV

Filogeografia de Nasutitermes corniger (Isoptera: Termitidae: Nasutitermitinae) na região Neotropical

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estrutura genômica de uma população de suínos base Landrace

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Formação de professores e a escola de tempo integral no município de Araçatuba: práticas, desafios e possibilidades

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

Estudo genético do escore de condição corporal de vacas Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Metodologia de determinação de funções de pertinência de controla-dores fuzzy para a avaliação energética de empresas de avicultura de postura

The objective of this work is to determine the membership functions for the construction of a fuzzy controller to evaluate the energy situation of the company with respect to load and power factors. The energy assessment of a company is performed by technicians and experts based on the indices of load and power factors, and analysis of the machines used in production processes. This assessment is conducted periodically to detect whether the procedures performed by employees in relation to how of use electricity energy are correct. With a fuzzy controller, this performed can be done by machines. The construction of a fuzzy controller is initially characterized by the definition of input and output variables, and their associated membership functions. We also need to define a method of inference and a processor output. Finally, you need the help of technicians and experts to build a rule base, consisting of answers that provide these professionals in function of characteristics of the input variables. The controller proposed in this paper has as input variables load and power factors, and output the company situation. Their membership functions representing fuzzy sets called by linguistic qualities, as “VERY BAD” and “GOOD”. With the method of inference Mandani and the processor to exit from the Center of Area chosen, the structure of a fuzzy controller is established, simply by the choice by technicians and experts of the field energy to determine a set of rules appropriate for the chosen company. Thus, the interpretation of load and power factors by software comes to meeting the need of creating a single index that indicates an overall basis (rational and efficient) as the energy is being used.