The paper will probe into the conference system of educative cooperation between China and ASEAN,proposing concretely the thinking of senior meeting system,exhibition system and presidents’ joint conference system.
Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
The Mg−Al composite rods of aluminum core-reinforced magnesium alloy were prepared by the extrusion−shear(ES)process,and the microstructure,deformation mechanism,and mechanical properties of the Mg−Al composite rods w...The Mg−Al composite rods of aluminum core-reinforced magnesium alloy were prepared by the extrusion−shear(ES)process,and the microstructure,deformation mechanism,and mechanical properties of the Mg−Al composite rods were investigated at different extrusion temperatures and shear stresses.The experimental results show that the proportion of dynamic recrystallization(DRX)and texture for Al and Mg alloys are controlled by the combination of temperature and shear stress.The texture type of the Al alloys exhibits slight variations at different temperatures.With the increase of temperature,the DRX behavior of Mg alloy shifts from discontinuous DRX(DDRX),continuous DRX(CDRX),and twin-induced DRX(TDRX)dominant to CDRX,the dislocation density in Mg alloy grains decreases significantly,and the average value of Schmid factor(SF)of the basalslip system increases.In particular,partial grains exhibit a distinct dominant slip system at 390℃.The hardness and thickness of the bonding layer,as well as the yield strength and elongation of the Mg alloy,reach their maximum at 360℃as a result of the intricate influence of the combined temperature and shear stress.展开更多
文摘The paper will probe into the conference system of educative cooperation between China and ASEAN,proposing concretely the thinking of senior meeting system,exhibition system and presidents’ joint conference system.
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
基金supported by the general project of the National Natural Science Foundation of China(No.52071042)Chongqing Natural Science Foundation Project,China(Nos.CSTB2023NSCQ-MSX0079,cstc2021ycjh-bgzxm0148)Graduate Student Innovation Program of Chongqing University of Technology,China(No.gzlcx20232008).
文摘The Mg−Al composite rods of aluminum core-reinforced magnesium alloy were prepared by the extrusion−shear(ES)process,and the microstructure,deformation mechanism,and mechanical properties of the Mg−Al composite rods were investigated at different extrusion temperatures and shear stresses.The experimental results show that the proportion of dynamic recrystallization(DRX)and texture for Al and Mg alloys are controlled by the combination of temperature and shear stress.The texture type of the Al alloys exhibits slight variations at different temperatures.With the increase of temperature,the DRX behavior of Mg alloy shifts from discontinuous DRX(DDRX),continuous DRX(CDRX),and twin-induced DRX(TDRX)dominant to CDRX,the dislocation density in Mg alloy grains decreases significantly,and the average value of Schmid factor(SF)of the basalslip system increases.In particular,partial grains exhibit a distinct dominant slip system at 390℃.The hardness and thickness of the bonding layer,as well as the yield strength and elongation of the Mg alloy,reach their maximum at 360℃as a result of the intricate influence of the combined temperature and shear stress.
