this paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. the classification performance andinterpretability are of major importance in these systems. in this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). ourapproach uses a punish...

recently, tuning the weights of the rules in fuzzy rule-base classification systems is researched in order to improve the accuracy of classification. in this paper, a margin-based optimization model, inspired by support vector machine classifiers, is proposed to compute these fuzzy rule weights. this approach not only  considers both accuracy and generalization criteria in a single objective fu...

nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...

Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only  considers both accuracy and generalization criteria in a single objective fu...

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...

fuzzy rule-based classification system (frbcs) is a popular machine learning technique for classification purposes. one of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. however many cases the minority classes are more important than the majority ones. in this paper, we have extended ...

land cover information is one of the most important prerequisite in urban management system. in this way remote sensing, as the most economic technology, is mainly used to produce land cover maps. considering the complicated and dense urban areas in third world countries, object based approaches are suggested as an effective image processing technique. the purpose of this paper are the introduc...

This paper proposes fuzzy modeling using obtained data. Fuzzy system is known as knowledge-based or rule-bases system. The most important part of fuzzy system is rule-base. One of problems of generation of fuzzy rule with training data is inconsistence data. Existence of inconsistence and uncertain states in training data causes high error in modeling. Here, Probability fuzzy system presents to...