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《Mining Research and Development》 2007-02
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An Intelligent Ant Colony Neural Network Model for the Dynamic Constitutive Relationship of Rock under High Strain Rate

Chen Chaojun,Guo Lianjun,Fei Aiping (School of Civil and Transportation Engineering,Anshan University of Science and Technology,Anshan,Liaoning 114044,China)  
To solve the disadvantages of ant colony algorithm including slow searching speed and low precision in optimizing weights of neural network,a novel hybrid ant colony neural network is proposed,in which gradient descent method is set as a kind of optimization operator,and based on the results of compression test under high strain-rate,a intelligent ant colony model on the constitutive relationship of granite under high strain-rate induce by dynamic load is constructed.The simulation results of the intelligent model are very close to the test results, this shows that the constructed model is valuable for studying on the dynamic mechanic properties of rocks.
【Fund】: 辽宁省自然科学基金资助项目(20032146)
【CateGory Index】: TU452
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