Adaptive resonance theory-based neural algorithms for manufacturing process quality control

Monitoring roundness profiles based on an unsupervised neural network algorithm

“…This drawback can be mainly ascribed to the binary coding of the ART algorithm as it is a less flexible way of using process data than a method based on graded continuous number encoding. In fact, subsequent researches extended this methodology and presented outperforming ART neural networks for unnatural behavior detection (Pacella & Semeraro, 2005;Pacella, Semeraro, & Anglani, 2004a, 2004b. In particular, a simplified Fuzzy ART algorithm, which incorporates computations from fuzzy set theory by which can categorize analog patterns, was presented.…”

“…In Pacella et al (2004a) the neural network was trained using a series of process natural output data. In Pacella et al (2004b) it was demonstrated that the training set can even be limited to a single vector whose components are equal to the process nominal value. Fuzzy ART responses to inputs can be easily explained (Pacella & Semeraro, 2005), in contrast to other neural networks, where typically it is more difficult to realize why an input produces a specific output.…”

Understanding ART-based neural algorithms as statistical tools for manufacturing process quality control

“…In Pacella et al (2004a) the neural network was trained using a series of process natural output data in a similar manner to that of Al-Ghanim. In Pacella et al (2004b) it was demonstrated that the training set can even be limited to a single vector whose components are equal to the process nominal value. In the post-training phase, Fuzzy ART compares input vectors to learned categories and produces a signal if the current input does not fit to any of the natural templates.…”

A fuzzy art neural network based color image processing and recognition scheme

“…Analysis of related literature shows that ART network families are most popular for image segmentation and recognition techniques in many applications that include face recognition in [2,3,4], classification of multivariate chemical data [5], quality control of manufacturing processes [6], and classification of wireless sensor networks with missing data [7]. Models of Fuzzy ART and ART networks have developed to improve the ability of clustering.…”