No matter where he is and what he does,Dr. Shen always considers himself as a devoted researcher,and holds tough mind that he will go further along the medicine innovation, heading for the health and happiness of huma...No matter where he is and what he does,Dr. Shen always considers himself as a devoted researcher,and holds tough mind that he will go further along the medicine innovation, heading for the health and happiness of human being.展开更多
The hot compression tests of 7Mo super austenitic stainless(SASS)were conducted to obtain flow curves at the temperature of 1000-1200℃and strain rate of 0.001 s^(-1)to 1 s^(-1).To predict the non-linear hot deformati...The hot compression tests of 7Mo super austenitic stainless(SASS)were conducted to obtain flow curves at the temperature of 1000-1200℃and strain rate of 0.001 s^(-1)to 1 s^(-1).To predict the non-linear hot deformation behaviors of the steel,back propagation-artificial neural network(BP-ANN)with 16×8×8 hidden layer neurons was proposed.The predictability of the ANN model is evaluated according to the distribution of mean absolute error(MAE)and relative error.The relative error of 85%data for the BP-ANN model is among±5%while only 42.5%data predicted by the Arrhenius constitutive equation is in this range.Especially,at high strain rate and low temperature,the MAE of the ANN model is 2.49%,which has decreases for 18.78%,compared with conventional Arrhenius constitutive equation.展开更多
A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductiv...A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.展开更多
A novel method for spectral characterization of scanner was proposed in this paper, which combined the principal component analysis （PCA） and back propagation （BP） artificial neural network （ANN）. The natural co...A novel method for spectral characterization of scanner was proposed in this paper, which combined the principal component analysis （PCA） and back propagation （BP） artificial neural network （ANN）. The natural color system （NCS） color patches were adopted as the color targets. The accuracy of this method was evaluated by spectral root mean square （SRMS） error and the CIEDE2000 color difference specification. The experimental results showed that six principal components were appropriate and the spectral characterization accuracy was outstanding when a 3-20-6 BP net structure was used to estimate the scalars from the scanner red/green/blue （RGB） signals.展开更多
Based on the population and economic data of the Wumeng Mountain Area from 2000 to 2020,this study explored the imbalanced spatiotemporal patterns of population and economy in the area using methods such as the geogra...Based on the population and economic data of the Wumeng Mountain Area from 2000 to 2020,this study explored the imbalanced spatiotemporal patterns of population and economy in the area using methods such as the geographic concentration,gravity model,imbalance index,and inconsistency index.The study also analyzed the influencing factors using geodetectors and spatiotemporal geographically weighted regression models.The results show four key aspects of this phenomenon.(1)The spatial distributions of the population and economic geographic concentrations deviate from their ideal distributions.The population distribution shows a spatial pattern of being higher in the northeast and lower in the southwest,while the economic distribution shows a spatial pattern of being higher in the south and lower in the north.(2)The population and economic gravity centers have shifted toward the northeast and south relative to the geometric center of the mountain area,respectively,and the economic center has shifted more than the population center.(3)The degree of imbalance between the population and economic distributions is decreasing,but regional development disparities still exist.The region with inconsistent spatial distributions between population and economy remains stable,showing a"north high,south low"pattern,with an increase in the number of counties dominated by the economy and reductions in the numbers of counties in other categories.(4)Economic power,social consumption level,industrial structure,urban development level,government regulation capacity,and health care infrastructure are the main factors affecting the inconsistent distributions of population and economy in Wumeng Mountain Area,and the effects of these factors are reflected in the promotion of economic development.展开更多
文摘No matter where he is and what he does,Dr. Shen always considers himself as a devoted researcher,and holds tough mind that he will go further along the medicine innovation, heading for the health and happiness of human being.
文摘The hot compression tests of 7Mo super austenitic stainless(SASS)were conducted to obtain flow curves at the temperature of 1000-1200℃and strain rate of 0.001 s^(-1)to 1 s^(-1).To predict the non-linear hot deformation behaviors of the steel,back propagation-artificial neural network(BP-ANN)with 16×8×8 hidden layer neurons was proposed.The predictability of the ANN model is evaluated according to the distribution of mean absolute error(MAE)and relative error.The relative error of 85%data for the BP-ANN model is among±5%while only 42.5%data predicted by the Arrhenius constitutive equation is in this range.Especially,at high strain rate and low temperature,the MAE of the ANN model is 2.49%,which has decreases for 18.78%,compared with conventional Arrhenius constitutive equation.
基金supported by the Fundamental Research Funds for the Central Universities (No.3122020072)the Multi-investment Project of Tianjin Applied Basic Research(No.23JCQNJC00250)。
文摘A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.
文摘A novel method for spectral characterization of scanner was proposed in this paper, which combined the principal component analysis （PCA） and back propagation （BP） artificial neural network （ANN）. The natural color system （NCS） color patches were adopted as the color targets. The accuracy of this method was evaluated by spectral root mean square （SRMS） error and the CIEDE2000 color difference specification. The experimental results showed that six principal components were appropriate and the spectral characterization accuracy was outstanding when a 3-20-6 BP net structure was used to estimate the scalars from the scanner red/green/blue （RGB） signals.
基金The National Natural Science Foundation Project(41261039).
文摘Based on the population and economic data of the Wumeng Mountain Area from 2000 to 2020,this study explored the imbalanced spatiotemporal patterns of population and economy in the area using methods such as the geographic concentration,gravity model,imbalance index,and inconsistency index.The study also analyzed the influencing factors using geodetectors and spatiotemporal geographically weighted regression models.The results show four key aspects of this phenomenon.(1)The spatial distributions of the population and economic geographic concentrations deviate from their ideal distributions.The population distribution shows a spatial pattern of being higher in the northeast and lower in the southwest,while the economic distribution shows a spatial pattern of being higher in the south and lower in the north.(2)The population and economic gravity centers have shifted toward the northeast and south relative to the geometric center of the mountain area,respectively,and the economic center has shifted more than the population center.(3)The degree of imbalance between the population and economic distributions is decreasing,but regional development disparities still exist.The region with inconsistent spatial distributions between population and economy remains stable,showing a"north high,south low"pattern,with an increase in the number of counties dominated by the economy and reductions in the numbers of counties in other categories.(4)Economic power,social consumption level,industrial structure,urban development level,government regulation capacity,and health care infrastructure are the main factors affecting the inconsistent distributions of population and economy in Wumeng Mountain Area,and the effects of these factors are reflected in the promotion of economic development.
