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To improve the reality and whole performance of network Intrusion Detection System(IDS) ,the approach in which an optimal combination of ( >; ) features used to classification of IDS were selected from, features, was presented, which was based on Genetic Algorithms. The optimal set of features was best for recognizing intruder, which made classification evaluation target to reach maximum. Tests...
The emerging computational grid infrastructure consists of widely distributed heterogeneous resources, which makes mapping of increasingly complex applications a very challenging task. Utility Management Systems (UMS) manage large number of workflows with high resource requirements and thereby optimization of resource utilization has to be adapted. In this work we propose the architecture that implements...
The emerging computational grid infrastructure consists of heterogeneous resources in widely distributed autonomous domains, which makes job scheduling very challenging. Although there is much work on static scheduling approaches for workflow applications in parallel environments, little work has been done on a real-world Grid environment for industrial systems. Utility Management Systems (UMS) are...
Water quality model is a useful tool to evaluate the future state of river water through evaluation of actual pollution loading or different management options. Based on the human brain physiology research, artificial neural network(ANN), which simulates the structure and mechanism of the human brain, is a kind of dynamic information processing system that eventually achieves certain functions of...
In this paper, the application of neural networks is proposed to solve the problem of voltage sags state estimation. This problem is based on estimating the voltage sags occurrence frequency at non monitored buses from the recorded voltage sags occurrence frequency at a limited number of monitored buses. The fault position method is used to formulate the optimization problem. The methodology is implemented...
By using steepest descend algorithm to calculate the networks weights, traditional BP networks model in the dam safety monitoring is complex in calculation process and will easily fall into local extreme point. To solve the shortages, the cooperative particle swarm optimization algorithm is proposed to optimize the weights of the neural networks for dam safety monitoring. Firstly, the calculation...
This paper proposes a method of applying BP neural network model of DNA-based genetic algorithm to monitor and forecast cutting tool wear. Through the optimization by training, that is adopts DNA genetic algorithm to optimize the initial figure of BP neural networks and increases the speed of convergence and avoid local minimum, the BP neural network model can effectively extract the characteristic...
Using particle swarm optimization (PSO) to optimize BP neural network model is proposed in this paper. The new model is more quickly and accurate. The basic idea of this model is: Firstly PSO is used to optimize the BP neural network's initialized weights, an optimized result is got; then based on the optimized result the BP neural network is used for further optimization. We can use this model for...
The application of wavelet neural network based on Levenberg-Marquardt Optimization to predict heat exchanger fouling is reported in this paper. We construct a 6-6-1 network according to the fouling monitor principle and parameters, the modeling of the wavelet neural network programmed with MATLAB, and trained with Levenberg-Marquarde Optimization algorithm, all training data came from the Automatic...
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