(INSTITUTO DE TECNOLOGIA, 2015) AZEVEDO, Manoel S. Santos; NEVES, Cleonor C. das; CASTRO, Adriana Rosa G; LEITE, Jandecy Cabral.; Prof. Dr. Carlos Tavares da Costa Júnior
This paper proposes a system for extracting knowledge from neural networks aided by fuzzy logic, emphasizing the generation of a rule bank representing process behavior. The system enables the construction of models for control or information retrieval, particularly in cases where traditional modeling is unfeasible. The approach employs neuro-fuzzy networks to extract knowledge distributed across network connections.
(INSTITUTO DE TECNOLOGIA, 2010) NOGUEIRA, Maria Amélia Costa Saraiva; COSTA JÚNIOR, Carlos Tavares da; LEITE, Jandecy Cabral.; Prof. Dr. Rui Guilherme Cavaleiro de Macedo Alves
This paper proposes a methodology based on fuzzy logic to evaluate noise quality in industrial workplaces, considering variables such as noise level and working hours. The model uses membership functions and fuzzy rules to classify the environment as "satisfactory" or "at risk." The application of the method in a metalworking industry demonstrated its effectiveness in identifying unhealthy conditions, contributing to the prevention of occupational health problems.
