Neural networks, which make no assumption about data distribution, have achieved improved image classification results compared to traditional methods. Unfortunately, a neural network is generally perceived as being a ‘black box’. It is extremely difficult to document how specific classification decisions are reached. Fuzzy systems, on the other hand, have the capability to represent classifica...

Censored Production Rule is an extension of standard production rule, which is concerned with problems of reasoning with incomplete information, subject to resource constraints and problem of reasoning efficiently with exceptions. A CPR has a form: IF A (Condition) THEN B (Action) UNLESS C (Censor), Where C is the exception condition. Fuzzy CPR are obtained by augmenting ordinary fuzzy producti...

this paper develops an automatic parking algorithm based on a fuzzy logic controller with the vehicle pose for the input and the steering angle for the output. in this way some feasible reference trajectory path have been introduced according to geometric and kinematic constraints and nonholonomic constraints to simulate motion path of car. also a novel method is used for parking space detectio...

In this paper we extend the problem of classification using Fuzzy Association Rule Mining and propose the concept of Fuzzy Weighted Associative Classifier (FWAC). Classification based on Association rules is considered to be effective and advantageous in many cases. Associative classifiers are especially fit to applications where the model may assist the domain experts in their decisions. Weigh...

This paper presents an extension of the method presented by Benitez et al (1997) for extracting fuzzy rules from an artificial neural network (ANN) that express exactly its behavior. The extraction process provides an interpretation of the ANN in terms of fuzzy rules. The fuzzy rules presented are in accordance with the domain of the input variables. These rules use a new operator in the antece...

This paper describes an interval type-2 fuzzy modeling framework, reduced-set vector-based interval type-2 fuzzy neural network (RV-based IT2FNN), to characterize the representation in fuzzy logic inference procedure. The model proposed introduces the concept of interval kernel to interval type-2 fuzzy membership, and provides an architecure to extract reduced-set vectors for generating interva...

In this paper we present an approach to visualize a potentially high-dimensional and large number of (fuzzy) rules in two dimensions. This visualization presents the entire set of rules to the user as one coherent picture. We use a gradient descent based algorithm to generate a 2D-view of the rule set which minimizes the error on the pair-wise fuzzy distances between all rules. This approach is...

ISBN 555555555/$10.00  2002 IEEE Abstract – The normal and the abnormal behaviors in networked computers are hard to predict, as the boundaries cannot be well defined. This prediction process usually generates false alarms in many anomaly based intrusion detection systems. However, with fuzzy logic, the false alarm rate in determining intrusive activities can be reduced, where a set of fuzzy r...

This paper proposed a model to predict the stock price based on combining Self-Organizing Map (SOM) and fuzzy – Support Vector Machines (f-SVM). Extraction of fuzzy rules from raw data based on the combining of statistical machine learning models is the base of this proposed approach. In the proposed model, SOM is used as a clustering algorithm to partition the whole input space into several di...

Cardiovascular decision support is one area of increasing research interest. On-going collaborations between clinicians and computer scientists are looking at the application of knowledge discovery in databases to the area of patient diagnosis, based on clinical records. A fuzzy rule-based system for risk estimation of cardiovascular patients is proposed. It uses a group of fuzzy rules as a kno...