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In wireless monitoring networks, multi-radio wireless sniffers are distributed for capturing and analyzing user activities in order to realize network monitoring, fault diagnosis, resource management, etc. Therefore, it is a key topic to optimize the channel selection for sniffers to maximize the information collected, so as to maximize the Quality of Monitoring (QoM) of the network. In this paper,...
This paper presents a design for testability technique to avoid scan shift failure due to flip–flop simultaneous triggering. The proposed technique changes test clock domains of flip–flops in the regions where severe IR-drop problems occur. A massive parallel algorithm using a graphic processor unit is adopted to speed up the IR-drop simulation during optimization. The experimental data on large benchmark...
Spectral band selection is a fundamental problem in hyperspectral classification. This paper addresses the problem of band selection for hyperspectral remote sensing image and SVM parameter optimization. We propose an evolutionary classification system based on particle swarm optimization (PSO) to improve the generalization performance of the SVM classifier. The proposed PSO-SVM algorithm is performed...
Co-evolutionary algorithm behaves in a complicated and counterintuitive way for some complex problems. The introduction of interactive immune concept can increase its convergence rate and effectiveness. This paper represents an optimization process of polyester filament in melt spinning with the interactive immune co-evolutionary design approach and also the expert evaluation with entropy-based fuzzy...
This paper presents the clonal selection algorithm (CSA) to select a proper subset of features and optimal parameters of support vector machines (SVMs) classifier. Like the genetic algorithm, clonal selection algorithm is a tool for optimum solution to select better parameters, in our experiment, to improve classification accuracy, the clonal selection algorithm and genetic algorithm are used to reach...
This study proposes a new strategy combining with the SVM(support vector machine) classifier for features selection that retains sufficient information for classification purpose. Our proposed approach uses F-score models to optimize feature space by removing both irrelevant and redundant features. To improve classification accuracy, the parameters optimization of the penalty constant C and the bandwidth...
The QoS is a key measure for satisfaction level of next-generation network (NGN). QoS multicast routing is becoming an urgent problem to promote NGN. An optimization mode is proposed for it, and an immune inspired algorithm is designed to solve the model. The simulation study shows the promising effects of the model and the algorithm. The study can meet the requirements of NGN performance optimization.
When the framework of next-generation network (NGN) is built upon bio-network, the SLEE domains and dispatched business processes gain the capability to be aware of the computation resources and communication loads. The dispatcher of NGN then can optimize the loads among domains by balancing the resources and communication bandwidth. First, a model is built. Second, the simulation results show its...
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