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The cellular genetic algorithm with disaster (CDGA) puts individuals into a toridal grid or presudo landscape which behave "active" or "inactive" state. The genetic operator of individuals is restricted to within neighborhood. In this paper, we evaluate combinational effects on size of neighborhood and size of disaster. We have tackled this research by considering two typical functions...
As a type of layout which can bring the material transport high flexibility, unidirectional loop layout is widely used in modern workshop layout. This paper deploys research around how to apply a unidirectional loop layout to optimize the facility layout in workshop. Firstly, it establishes a mathematic model of the optimization problem according to optimization objective and restriction condition...
The cellular genetic algorithm (CGA) is growing which combines GAs with cellular automata. The individuals are distributed in a toridal grid or presudo landscape and their genetic operator is restricted to within neighborhood. In this paper, we present a cellular genetic algorithm with evolutional rule (CGAE) which more closely mimics the process of evolvement in ecology by cellular automata. It provides...
Feature extraction and feature selection of fracture surface images provided by scanning electron microscopy (SEM) are two main challenges in classification of metal fracture surface images. In extracting features, the statistical characteristics of gray-level co-occurrence matrix and the fractal dimension of fracture surface images are computed as feature sets; and then , a genetic algorithm (GA)...
Considering the dynamic characteristic of wind farms, especially the wind turbines' output fluctuate with wind speed, the optimal reactive power compensation problem for wind farms is formulated and solved by genetic/tabu search hybrid algorithm (GATS). A mathematical model of reactive power compensation, focused on voltage stability and power losses of wind farms, is developed, and the reactive power...
This article use the Brushless DC Motor as the plant, to compare the genetic algorithm back propagation neural network PID controller with the traditional PID controller. It proves that adopting genetic algorithm optimization back propagation neural network PID controller to determine the PID parameters has made the kinetic characteristic and the robustness of the system much better.
Traditional Grey GM(1,1) Model had its defect when it was applied to forecast relative data series. The relationship between different data series can't be reflected properly. In order to solve the problem, artificial neural network (ANN) is combined to forecast multi-series data. Then the network optimization is aided by improved genetic algorithm (GA). So the network weights and thresholds were...
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