An algorithm to classify the network traffic based on improved support vector machine (SVM) is presented in this paper. Each feature of the traditional support vector machine (SVM) algorithm has the same effect on classification rather than considering its practical effect. To improve the classification accuracy of SVM, the probabilistic distributing area of a feature in a kind of network traff...

The well known fuzzy partition clustering algorithms are most based on Euclidean distance function, which can only be used to detect spherical structural clusters. Gustafson-Kessel (GK) clustering algorithm and Gath-Geva (GG) clustering algorithm, were developed to detect non-spherical structural clusters, but both of them based on semi-supervised Mahalanobis distance needed additional prior in...

In this paper, the development of an improved Takagi Sugeno (TS) fuzzy model for identification and chaotic time series prediction of nonlinear dynamical systems is proposed. This model combines the advantages of fuzzy systems and Infinite Impulse Response (IIR) filters, which are autoregressive moving average models, to create internal dynamics with just the control input. The structure of Fuz...

In this paper, we propose a context-sensitive technique for unsupervised change detection in multitemporal remote sensing images. The technique is based on fuzzy clustering approach and takes care of spatial correlation between neighboring pixels of the difference image produced by comparing two images acquired on the same geographical area at different times. Since the ranges of pixel values o...

For the problem of change detection it is difficult to have sufficient amount of ground truth information that is needed in supervised learning. On the contrary it is easy to identify a few labeled patterns by the experts. In this situation to avoid wastage of available information semi-supervision is suggestible to enhance the performance of unsupervised ones. Here we present the fuzzy cluster...

Systematic information on the rarely collected Holarctic platypezid genus Seri Kessel & Kessel is reviewed. Two species are included, S. obscuripennis (Oldenberg) from the Palaearctic Region and S. dymka (Kessel) from the Nearctic Region. The two species are diagnosed and the male of S. dymka is described for the first time. New records of S. dymka, previously recorded only from western North A...

Fuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applied successfully in various fields including finance and marketing. Despite the successful applications, there are a number of issues that must be dealt with in practical applications of fuzzy clustering algorithms. This technical report proposes two extensions to the objective function based fuzzy...

Fuzzy clustering is well known as a robust and efficient way to reduce computation cost to obtain the better results. In the literature, many robust fuzzy clustering models have been presented such as Fuzzy C-Mean (FCM) and Possibilistic C-Mean (PCM), where these methods are Type-I Fuzzy clustering. Type-II Fuzzy sets, on the other hand, can provide better performance than Type-I Fuzzy sets, es...

This article presents the viability analysis and the development of heart disease identification embedded system. It offers a time reduction on electrocardiogram - ECG signal processing by reducing the amount of data samples, without any significant loss. The goal of the developed system is the analysis of heart signals. The ECG signals are applied into the system that performs an initial filte...