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In this paper, a novel clustering-based classifier using Support Vector Machines criterion (called CBCSVM) is presented for pattern classification. This algorithm involves three steps. At first, the robust clustering algorithm Kernelized Fuzzy c-means is utilized to yield the clustering centers. Then, a set of Gaussian functions associated with these obtained centers are adopted to map the samples...
Clustering algorithms are increasingly employed for the image segmentation. By incorporating the spatial information and the term used in the punishing the distance, a new robust fuzzy c-means (NRFCM) algorithm was proposed for effectively improving the quality of the image segmentation. Its main characteristics are as follows:(1) The negative influence of the noise can be effectively reduced by using...
This paper presents an online real-time network response system, which can determine whether a LAN is suffering from a flooding attack within a very short time unit. The detection engine of the system is based on the incremental mining of fuzzy association rules from network packets, in which membership functions of fuzzy variables are optimized by a genetic algorithm. The proposed online system belongs...
Initialization of fuzzy k-means algorithm decreases the convergent rate of clustering and leads to plenty of calculation. Thus, we propose an improved fuzzy k-means clustering based on k-center algorithm and binary tree in this paper, which firstly reduces redundant attributes while too many irrespective attributes affect the efficiency of clustering. Secondly, we remove the differences of units of...
A method to online detect and diagnose brick interior different types of faults was proposed based on striking sound. Applied spectrum analysis to striking sound signals of bricks, picked out characteristic frequencies of every spectrum to form a data matrix, then applied fuzzy cluster analysis to get classification, next computed corresponding average similarity to every cluster, judged bricks fault...
Based on analyzing the factors affecting the longitudinal motion performance of SWATH, this paper establishes the layered evaluating index system of the longitudinal motion performance of SWATH. The analytic hierarchy process is used to determine the weight coefficients of the evaluating index. Then this paper evaluates the longitudinal motion performance of SWATH using the fuzzy comprehensive evaluation...
In order to solve the problem of user-classification to reflect the features of Web users inflexible, a novel user classification model was presented in this paper. By introducing the concept of time discretization and applying fuzzy equivalence relation clustering to classify Web users, the model can rationally solve the user classification problems. Empirical results showed that the output of user...
Feature selection is an important problem for pattern classification systems. There are many methods for feature selection available, in which the feature selection method based on mutual information proposed by authors of Ref.[13] is one of the more effective approaches. However, it is often difficult to compute the mutual information for the continuous data whether using discretization strategy...
Fuzzy relational classifier (FRC) is the recently proposed two-step nonlinear classifiers, which effectively integrates the formed clusters and the given classes. However, FRC can not copy with the influence of those irrelevant or redundant features. To effectively filter out those irrelevant features and preserve the internal structure hidden in the given data, in this paper, a simultaneous clustering...
Human behavior models (HBMs) are increasingly used in complex domains such as military or manufacturing domains, for no man ever looks at the world with pristine eyes. In this context, we glean appropriate theories and pragmatic findings on human culture, and report in this paper a framework to model and simulate the behavior of an individual as well as of a group of individuals. For this purpose,...
To improve the fidelity and automation of simulation exercises, human behavior models have become key components in most military simulations. In this paper, we present a fuzzy Petri nets-based method for verification and validation of fuzzy rules-based human behavior models. This method consists of three parts: verification of fuzzy rule bases, static validation of human behavior models, and dynamic...
The fuzzy association rule has been proven to be effective to present userspsila network behavior offline from a huge amount of collected packets. However, not only effectiveness, efficiency is important as well for Network Intrusion Detection Systems (NIDSs). None of those proposed NIDSs subject to fuzzy association rule can meet the real-time requirement because they all applied static mining approach...
Rough set approach is one of effective attribute reduction (also called a feature selection) methods that can preserve the meaning of the attributes(features). However, most of existing algorithms mainly aim at information systems or decision tables with discrete values. Therefore, in this paper, we introduce a novel rough set-based method followed by establishing a fuzzy discernibility matrix by...
Command and control models, often represented as rules or fuzzy rules, are key components in most military simulations. Although there exist some verification techniques for rule bases, they are not enough to assure the correctness of command and control models. Based on an analysis of the characteristics of command and control models, this paper presents a fuzzy causality diagram-based verification...
Human decision models, often represented as rules or predicates, are key components in most military simulations. Although there exist some verification techniques for rule bases, they are not enough to assure the correctness of human decision models. Based on an analysis of the characteristics of human decision models in military simulations, this paper presents a method for verifying human decision...
Hybrid assembly line referred to a kind of assembly line with more than one operation mode. Multi-objective optimization is a more practical method for hybrid assembly line design optimization because several design objectives could included in optimization process, such as cost, workload balance, reconfigurability and so on. Multi-objective optimization for assembly line design is an active research...
This paper proposes a fuzzy-based error correction mechanism (FECM) to improve the precision of an online data-driven fuzzy clustering (ODDFC) used in the maneuvering target tracking and trajectory prediction. In the ODDFC, the observed data are extracted automatically by fuzzy inference mechanism without much computation and training costs. But the improvement performance of ODDFC is slightly due...
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