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FuNN/2—a fuzzy neural network architecture for adaptive learning and knowledge acquisition
Fuzzy neural networks have several features that make them well suited to a wide range of knowledge engineering applications. These strengths include fast and accurate learning, good generalisation capabilities, excellent ...
A fuzzy neural network model for the estimation of the feeding rate to an anaerobic waste water treatment process
Biological processes are among the most challenging to predict and control. It has been recognised that the development of an intelligent system for the recognition, prediction and control of process states in a complex, ...
Connectionist methods for classification of fruit populations based on visible-near infrared spectrophotometry data
Variation in fruit maturation can influence harvest timing and duration, post-harvest fruit attributes and consumer acceptability. Present methods of managing and identifying lines of fruit with specific attributes both ...
Hybrid neuro-fuzzy inference systems and their application for on-line adaptive learning of nonlinear dynamical systems
In this paper, an adaptive neuro-fuzzy system, called HyFIS, is proposed to build and optimise fuzzy models. The proposed model introduces the learning power of neural networks into the fuzzy logic systems and provides ...