As customers are the main asset of any organization, customer churn management is becoming a major task for organizations to retain their valuable customers. In the previous studies, the applicability and efficiency of hierarchical data mining techniques for churn prediction by combining two or more techniques have been proved to provide better performances than many single techniques over a nu...

This paper deals with two aspects of the application of ARTMAP neural networks for classification of satellite images obtained by remote sensing of the Earth. The first part contains an analysis of the influence of data representation and cluster determination method on classification accuracy. Three types of representation/determination are analyzed. Best results are obtained for Gaussian ARTM...

Default ARTMAP combines winner-take-all category node activation during training, distributed activation during testing, and a set of default parameter values that define a ready-to-use, general-purpose neural network system for supervised learning and recognition. Winner-take-all ARTMAP learning is designed so that each input would make a correct prediction if re-presented immediately after it...

This paper introduces an automated medical data classification method using wavelet transformation (WT) and interval type-2 fuzzy logic system (IT2FLS). Wavelet coefficients, which serve as inputs to the IT2FLS, are a compact form of original data but they exhibits highly discriminative features. The integration between WT and IT2FLS aims to cope with both high-dimensional data challenge and un...

The computer network flow controlproblem has been a recurring theme for long time. The main objective has always been to use network resources efficiently where to prevent the data packet loss, which requires retransmission of the lost information. This article presents the theoretical background necessary to understand the flow control, the existing research in this area and a theoretical back...

In this paper, a hybrid classifier using fuzzy clustering and several neural networks has been proposed. With using the fuzzy C-means algorithm, training samples will be clustered and the inappropriate data will be detected and moved to another dataset (RemovedDataset) and used differently in the classification phase. Also, in the proposed method using the membership degree of samples to the cl...

Vehicle license plate recognition is one of the techniques that can be used for the identification of vehicles. It is useful to be applied to many applications such as entrance admission, security, parking control, airport or harbour cargo control, road traffic control, speed control and so on. In this paper, we present an approach of recognising vehicle license plate using the Fuzzy ARTMAP neu...

This paper presents research into the application of the fuzzy ARTMAP neural network model to medical pattern classification tasks. A number of domains, both diagnostic and prognostic, are considered. Each such domain highlights a particularly useful aspect of the model. The first coronary care patient prognosis, demonstrates the ARTMAP voting strategy involving 'pooled' decision-making using a...

Fuzzy ARTMAP (FAM) is a neural network architecture that can establish the correct mapping between real-valued input patterns and correct labels in a variety of classification problems. Nevertheless, as the size of the dataset grows to thousands and hundreds of thousands, FAM’s convergence time slows down considerably. In this paper we focus on a FAM variant called no-match tracking FAM (NMT-FA...