Support vector machines (SVMs) proved to be highly efficient computational tools in various classification tasks. However, SVMs are nonlinear classifiers and the knowledge learned by an SVM is encoded in a long list of parameter values, making it difficult to comprehend what the SVM is actually computing. We show that certain types of SVMs are mathematically equivalent to a specific fuzzy–rule ...

The paper presents an evolutionary approach for generating fuzzy rule based classifier. First, a classification problem is divided into several two-class problems following a fuzzy unordered class binarization scheme; next, a fuzzy rule is evolved (not only the condition but the fuzzy sets are evolved (tuned) too) for each two-class problem using a Michigan iterative learning approach; finally,...

Predicting different behaviors in computer networks is the subject of many data mining researches. Providing a balanced Intrusion Detection System (IDS) that directly addresses the trade-off between the ability to detect new attack types and providing low false detection rate is a fundamental challenge. Many of the proposed methods perform well in one of the two aspects, and concentrate on a su...

In this study, the roll, yaw and depth fuzzy control of an Au- tonomous Underwater Vehicle (AUV) are addressed. Yaw and roll angles are regulated only using their errors and rates, but due to the complexity of depth dynamic channel, additional pitch rate quantity is used to improve the depth loop performance. The discussed AUV has four aps at the rear of the vehicle as actuators. Two rule bases...

Fuzzy modeling of high-dimensional systems is a challenging topic. This study proposes an effective approach to data-based fuzzy modeling of high-dimensional systems. The proposed method works on the fuzzification layer and tries to use two-dimensional membership functions instead of onedimensional ones. This approach reduces fuzzy rule base radically due to using of two-dimensional membership ...

When designing any type of fuzzy rule based system, considerable effort is placed in identifying the correct number of fuzzy sets and the fine tuning of the corresponding membership functions. Once a rule base has been formulated a fuzzy inference strategy must be applied in order to combine grades of membership. Considerable time and effort is spent trying to determine the number of fuzzy sets...

In this paper we present the application of a particular neuro-fuzzy system, named KERNEL, to the problem of differential diagnosis of erythematosquamous diseases, which represents a major problem in dermatology. A multistep learning strategy is adopted to obtain, starting directly from available data, a fuzzy rule base that can be used to identify the particular disease. The obtained classific...

Nodes in sensor networks can be easily compromised by an adversary due to hostile environments in which compromised nodes could be used to inject false reports into the network. The dynamic en-route scheme can detect and drop such false reports during the forwarding phase. In this scheme, choosing a threshold value is important as this gives a trade off between security of power and energy cons...

On this paper, an application of a high performance fuzzy logic hardware controller is explained, a model car is given autonomous character. Development of a fuzzy rule base, aided by a simulator program, is followed by trials made to come to conclusions regarding ideal and real functioning of the hardware developed.