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灰色优化模型gom
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     An intensive research on the way of predicting the relaxation of autofrettaged residual stresses based on the Gray System Theory has been launched. The limitations and improvements of applying the Grey Prediction GM(1,1) model are analyzed. According to the characteristic of the relaxation of autofrettaged residual stresses,the Grey Optimal Model(GOM) of its regularity under the circulated inner pressure is established.
     深入研究了基于灰色系统理论的自增强残余应力松弛的预测方法,剖析了灰色预测GM(1,1)模型应用的局限性及其改进方法,根据自增强残余应力松弛的特点,建立内压循环下自增强残余应力松弛规律的灰色优化模型(GOM).
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     优化;
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     证券组合的灰色优化
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     The Optimization of Grey Model GM (1,1)
     灰色模型GM(1,1)优化
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An intensive research on the way of predicting the relaxation of autofrettaged residual stresses based on the Gray System Theory has been launched.The limitations and improvements of applying the Grey Prediction GM(1,1) model are analyzed.According to the characteristic of the relaxation of autofrettaged residual stresses,the Grey Optimal Model(GOM) of its regularity under the circulated inner pressure is established.The predicted value of GOM is compared with that of GM(1,1) model as well as that of the experimental...

An intensive research on the way of predicting the relaxation of autofrettaged residual stresses based on the Gray System Theory has been launched.The limitations and improvements of applying the Grey Prediction GM(1,1) model are analyzed.According to the characteristic of the relaxation of autofrettaged residual stresses,the Grey Optimal Model(GOM) of its regularity under the circulated inner pressure is established.The predicted value of GOM is compared with that of GM(1,1) model as well as that of the experimental curve-fitting equation.The results show that the GOM has much higher precision and less errors and the predicted result accords with the experiment data basically.So the GOM can be used as the predicting model of the regularity of the relaxation of autofrettaged residual stresses.

深入研究了基于灰色系统理论的自增强残余应力松弛的预测方法,剖析了灰色预测GM(1,1)模型应用的局限性及其改进方法,根据自增强残余应力松弛的特点,建立内压循环下自增强残余应力松弛规律的灰色优化模型(GOM).并将模型预测值与GM(1,1)模型和试验拟合曲线方程预测值相比较,结果表明:该模型精度较高,预测误差较小,预测结果与试验数据基本吻合,可作为自增强残余应力松弛规律的预测模型.

 
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