Génération automatique de bases de connaissances floues pour les systèmes d'aide à la décision

Préparation de la base de connaissances pour le SAD "Fuzzy-Flow" -- Fuzzy decision support system knowledge base generation using a genetic algorithm -- Genetic-based learning process -- Numerical validation -- Influence des paramètres d'optimisation et de sélection -- Système d'aide à la décision -- Paramètres de l'AG -- Paramètres de sélection et d'optimisation -- Tool wear monitoring using genetically-generated fuzzy knowledge bases -- Monitoring systems

Modified Fuzzy FMEA Application in the Reduction of Defective Poultry Products

Failure mode and effects analysis (FMEA) consists of the famous qualitative management methods used for improvements in management processes. This paper aims to determine the factors of defective products in the processing of poultry products in the industry. The causes of problems have been analyzed by systematic brainstorming of specialist consensus in the evaluation of problems to achieve unanimity on the violence level. The FMEA method uses the risk priority number (RPN), which indicates the priorities of risk problems and can evaluate three components: severity, occurrence and detection. Sometimes, this risk assessment leads to the wrong priorities. Therefore, we propose fuzzy FMEA methods for priority ranking of RPN and efficiently reducing poultry product defects, which are established based on fuzzy systems followed by comparison with conventional FMEA. The results indicate that the fuzzy FMEA method can efficiently and feasibly reduce poultry product defects

Fuzzy decision support system knowledge base generation using a genetic algorithm

AbstractThis paper presents a genetic algorithm (GA) that automatically constructs the knowledge base used by fuzzy decision support systems (FDSS). The GA produces an optimal approximation of a set of sampled data from a very small amount of input information. The main interest of this method is that it can be used to automatically generate (without the help of an expert) a fuzzy knowledge base – i.e., the fuzzy sets for premises, conclusions and the fuzzy rules. This knowledge base is composed of the minimum number of fuzzy sets and rules. This minimalist approach produces fuzzy knowledge bases that are still manageable a posteriori by a human expert for fine tuning. The GA is validated through several examples of known behaviors and, finally, applied to experimental data

Automatisation du processus de construction des structures de données floues

Notion de base sur la logique floue -- Problématique et motivation de la recherche -- Systèmes à base de connaissances -- Génération automatique de bases de connaissances floues -- Généralités sur les algorithmes génétiques -- Généralités sur le procédé de pâtes thermomécanique -- Recherche proposée -- algorithmes génétiques hybride et binaire pour la génération automatique de bases de connaissances -- Stratégies multicombinatoires pour éviter la convergence prématurée dans les algorithmes génétiques -- Prédiction en ligne de la blancheur ISO de la pâte thermomécanique -- Real/binary-like coded versus binary coded genetic algorithms to automatically generate fuzzy knowledge bases : a comparative study -- Fuzzy decision support system -- Automatic generation of fuzzy knowledge bases using GAs -- Learning process -- Validation results -- Multi-combinative strategy to avoid premature convergence in genetically-generated fuzzy knowledge bases -- Introduction and problem definition -- Real/binary like coded genetic algorithm -- Performance criteria -- Evolutionary strategy -- Application to experimental data -- Online prediction of pulp brightness using fuzzy logic models -- The Chips management system -- Experiment plan for data collection -- Selection of the influencing variables -- Genetic-based learning process -- Performance criterion -- Evolutionary strategy -- Learning the FKBs for brightness prediction -- Learning the FKBs using laboratory variables