Fuzzy ARTMAP neural networks have been proven to be good classifiers on a variety of classification problems. However, the time that Fuzzy ARTMAP takes to converge to a solution increases rapidly as the number of patterns used for training is increased. In this paper we examine the time Fuzzy ARTMAP takes to converge to a solution and we propose a coarse grain parallelization technique, based o...

Artificial intelligent techniques have been widely used in high voltage insulation technology application. In this paper, the effectiveness of artificial intelligent technique to apply for pattern recognition and classification of Partial Discharge (PD) is presented. Partial discharge signal was generated and measured by using an artificial partial discharge source. Characteristics of PD signal...

An incremental, nonparametric probability estimation procedure using a variation of the Fuzzy ARTMAP (FAM) neural network is introduced. The resulted network, called Fuzzy ARTMAP with Relevance factor (FAMR), uses a relevance factor assigned to each sample pair, proportional to the importance of that pair during the learning phase. We prove that our probability estimator is correct. The FAMR ca...

An incremental, nonparametric probability estimation procedure using the fuzzy ARTMAP (adaptive resonance theory-supervised predictive mapping) neural network is introduced. In the slow-learning mode, fuzzy ARTMAP searches for patterns of data on which to build ever more accurate estimates. In max-nodes mode, the network initially learns a fixed number of categories, and weights are then adjust...

Critical care providers are faced with resource shortages and must find ways to effectively plan their resource utilization. Neural networks provide a new method for evaluating trauma patient (and other medical patient) level of illness and accurately predicting a patient’s length of stay at the critical care facility. Backpropagation, radial-basis-function, and fuzzy ARTMAP neural networks are...

The article presents ARTMAP and Fuzzy BKProduct approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and obstacles that is might meet in its way and whom AUV might avoid. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BKProduct cont...

In this paper, the impact on fuzzy ARTMAP performance of decisions taken for batch supervised learning is assessed through computer simulation. By learning different realworld and synthetic data, using different learning strategies, training set sizes, and hyperparameter values, the generalization error and resources requirements of this neural network are compared. In particular, the degradati...

Self-organized maps (SOM) have been applied to analyze the similarities of chemical compounds and to select from a given pool of descriptors the smallest and more relevant subset needed to build robust QSAR models based on fuzzy ARTMAP. First, the category maps for each molecular descriptor and for the target activity variable were created with SOM and then classified on the basis of topology a...

In the last years have seen a strong increase in the 802.11 wireless local area network (WLAN) technologies use, and the security mechanisms implemented by amendments IEEE 802.11i and IEEE 802.11w have proven not very effective in combating attacks against availability of WLAN services. Intrusion detection systems emerge as a way to help computer networks in this combat against the deny of serv...