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Information Fusion is a valid way which can decrease the uncertainty of making decision, and is also a hotspot. The paper makes some work on a important problem about Fuzzy Integral, that is how to get the Fuzzy Density, and compares two typical means. Based on 11 UCI data set, this paper conducts the compared experiment of several Information Fusion methods. It is compared with references 4 and 5...
As the common queue management strategy of Router, queue trail dropping has serious limitations such as full queue, whole synchronization and dead lock which leads to passive congestion management after the queue is full. Therefore the strategy easily leads to network congestion even crash. There are some good research fruits of active queue management (AQM) in keeping short queue length and keeping...
Semi-supervised classification algorithms attempt to overcome this major limitation by also using unlabelled examples. In this framework, This paper proposes a method working under a multi-view setting. we motivate BIC to optimize classifiers selection and use DCCA (Detrended Canonical Correspondence Analysis) to complete unlabeled examples selection by eliminating the arch effect. We empirically...
Grid computing provides the infrastructure necessary to access and use distributed resources as part of virtual organizations. When used in this way, grid computing makes it possible for users to participate in collaborative and distributed applications. This class of applications must adhere to stringent real-time constraints and Quality-of-Service (QoS) requirements. We discuss the design and a...
In the paper, a micro-genetic algorithm (MGA) based approach to the optimization of reactive power and voltage profiles improvement and real power loss minimization is present. The proposed strategy aims to prevent voltage fluctuations and unconvergence cases by coordinating the operation of reactive power and voltage control equipments. The problem is formulated as a combinatorial nonlinear optimization...
Clustering Ensemble is more and more becoming a new hotspot to improve clustering performance since it was firstly presented in 2002. Through using the mechanism of the integrate mechanism of testing and information rolling method to decrease the error probability of matching cluster members, and using a method of category weight to ensemble clustering members, this paper proposes a novel Clustering...
Fuzzy Integral is a valid method which can decrease the uncertainty of making decision. During this researching field how to get the fuzzy density is a difficult problem ,and is also a hotspot. This paper brings forward a new algorithm to determine fuzzy density compared with the existing algorithms this method the emulational result testifies its validity.
Since clustering ensemble was firstly presented in 2002, it is more and more becoming a new hotspot to improve clustering performance. Through using the mechanism of information rolling and selecting component clusters with the help of mutual information weight, this paper proposes a new clustering ensemble algorithm. Experiments show that this algorithm could effectively improve the clustering results.
Fuzzy Integral is compared with other two methods which are hot in studying of classifiers' fusion. The standard model of fuzzy integral and its general solution are introduced. Then, the state of the art and the challenge problems in fuzzy integral research field are discussed. The algorithms for standard and extended fuzzy integral models are briefly analyzed. Finally, the open areas of theoretic...
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