This paper presents a two-stage handwriting recognizer for classification of isolated characters that exploits explicit knowledge on characters’ shapes and execution plans. The first stage performs prototype extraction of the training data using a Fuzzy ARTMAP based method. These prototypes are able to improve the performance of the second stage consisting of LVQ codebooks by means of providing...

This paper presents the application of Fuzzy ARTMAP neural network for evaluating on-line load forecasting in short term case. A new approach using artificial neural networks (ANNs) is proposed for short term load forecasting. To forecast loads of a day, the hourly load pattern and the maximum and minimum and average of temprature must be determined. To demonstrate the effectiveness of the prop...

Intrusion Detection System (IDS) deals with a very large amount of data that includes redundant and irrelevant features. Therefore, feature selection is a necessary data pre-processing step to design IDSs that are lightweight. In this paper, a novel feature selection method based on data mining techniques is proposed, which uses fuzzy association rules to obtain the optimum feature subset. In t...

This paper presents a new method for the recognition of Arabic text using global fmtures and Fuzzy ARTMAP neural network The method is divided into three major steps. The first step is digitization and pre-processing to create connected component. The secondstep is concerned with fmture extraction, where global f w r e s of the input word are used to extract features such as number of suhvorch,...

The capability of Kasuba’s Simplified Fuzzy ARTMAP (SFAM) to behave as a Pattern Recognizer/Classifier of images both noisy and noise free has been investigated in this paper. This calls for augmenting the original Neuro–Fuzzy model with a modified moment-based RST invariant feature extractor. The potential of the SFAM based Pattern Recognizer to recognize patterns — monochrome and color, noisy...

Computational Intelligence (CI) consists of an evolving collection of methodologies often inspired from nature (Bonissone, Chen, Goebel & Khedkar, 1999, Fogel, 1999, Pedrycz, 1998). Two popular methodologies of CI include neural networks and fuzzy systems. Lately, a unification was proposed in CI, at a “data level”, based on lattice theory (Kaburlasos, 2006). More specifically, it was shown tha...

This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected...

Fusion ARTMAP is a selforganizing neural network architecture for multiMchannel, or InultiMscnsor, data fusion. Fusion ARTMAP generalizes the fuzzy ARTMAP architecture in order to adaptively classify multi-channel data. The network has a sy1nmetric organization such that each channel can be dynamically configured to serve as either a data input or a teaching input to the system. An ART module f...