智能电网的发展认识到短期电力净负荷预测对综合能源系统(integrated energy system,IES)的重要性。净负荷预测代表用电负荷与安装的可再生能源之间的差异,是能量管理和优化调度的基础。为解决IES波动性大,传统统计模型预测精较差的问题...智能电网的发展认识到短期电力净负荷预测对综合能源系统(integrated energy system,IES)的重要性。净负荷预测代表用电负荷与安装的可再生能源之间的差异,是能量管理和优化调度的基础。为解决IES波动性大,传统统计模型预测精较差的问题,该文提出一种基于时空图卷积网络(spatial temporal graph convolutional networks,STGCN)和Transformer相结合的综合能源系统短期负荷预测模型。首先,利用STGCN作为输入嵌入层对多元输入序列进行编码,填补Transformer中没有充分考虑相关信息的空白。然后,利用Transformer中的自注意机制捕获序列数据的时间依赖性。最后,利用前馈神经网络输出预测负荷值。以浙江省某地区电力数据集为例,与其他4种预测模型相比较平均绝对百分比误差均在5%以内,结果表明该文模型具有较高的预测精度和稳定性。展开更多
In the context of the digital transformation of vocational education,a quality evaluation index system has been constructed.Based on a questionnaire survey conducted among higher vocational colleges and enterprises in...In the context of the digital transformation of vocational education,a quality evaluation index system has been constructed.Based on a questionnaire survey conducted among higher vocational colleges and enterprises in Hainan Province,it has been found that the quality of vocational education generally depends on the talent training program and professional construction at the macro level.At the meso level,the teacher level and teaching environment are critical,while at the micro level,the evaluation of talent training quality cannot be underestimated.Strategies for quality improvement in vocational education are proposed from the perspectives of talent training programs,major construction,teacher development,teaching environment,and talent training quality,all under the lens of digital transformation.展开更多
Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herb...Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herbaceous plants,with notable applications in species such as Arabidopsis(Yin et al.,2024),soybean(Zhang et al.,2024),rice(Zhang et al.,2020),and Chinese cabbage(Li et al.,2021).However,its application in fruit trees is limited.This is primarily due to their long growth cycles and lack of rapid,efficient,and stable transgenic systems,which severely hinders foundational research involving plant genetic transformation(Mei et al.,2024).Furthermore,for subtropical fruit trees,the presence of recalcitrant seeds adds an extra layer of difficulty to genetic transformation(Umarani et al.,2015),as most methods rely on seed germination as a basis for transformation.展开更多
Theβsolidifiedγ-TiAl alloy holds important application value in the aerospace industry,while its com-plex phase compositions and geometric structures pose challenges to its microstructure control during the thermal-...Theβsolidifiedγ-TiAl alloy holds important application value in the aerospace industry,while its com-plex phase compositions and geometric structures pose challenges to its microstructure control during the thermal-mechanical process.The microstructure evolution of Ti-43Al-4Nb-1Mo-0.2B alloy at 1200℃/0.01 s−1 was investigated to clarify the coupling role of dynamic recrystallization(DRX)and phase transformation.The results revealed that the rate of DRX inα2+γlamellar colonies was comparatively slower than that inβo+γmixed structure,instead being accompanied by intense lamellar kinking and rotation.The initiation and development rates of DRX inα2,βo,andγphases decreased sequentially.The asynchronous DRX of the various geometric structures and phase compositions resulted in the un-even deformed microstructure,and the dynamic softening induced by lamellar kinking and rotation was replaced by strengthened DRX as strain increased.Additionally,the blockyα2 phase and the terminals ofα2 lamellae were the preferential DRX sites owing to the abundant activated slip systems.Theα2→βo transformation within lamellar colonies facilitated DRX and fragment ofα2 lamellae,while theα2→γtransformation promoted the decomposition ofα2 lamellae and DRX ofγlamellae.Moreover,the var-iedβo+γmixed structures underwent complicated evolution:(1)Theγ→βo transformation occurred at boundaries of lamellar colonies,followed by simultaneous DRX ofγlamellar terminals and neighboringβo phase;(2)DRX occurred earlier within the band-likeβo phase,with the delayed DRX in enclosedγphase;(3)DRX within theβo synapses and neighboringγphase was accelerated owing to generation of elastic stress field;(4)Dispersedβo particles triggered particle stimulated nucleation(PSN)ofγphase.Eventually,atomic diffusion along crystal defects inβo andγphases caused fracture of band-likeβo phase and formation of massiveβo particles,impeding grain boundary migration and hindering DRXed grain growth ofγphase.展开更多
近年来,全球经济金融环境动荡不安,充满挑战与风险,在此情况下,投资者在金融交易方面的抉择更加复杂,股票交易市场也面临着更大的挑战,传统的计量经济学模型难以充分适应此类变化。本文运用深度学习中的长短期记忆(LSTM)神经网络作为基...近年来,全球经济金融环境动荡不安,充满挑战与风险,在此情况下,投资者在金融交易方面的抉择更加复杂,股票交易市场也面临着更大的挑战,传统的计量经济学模型难以充分适应此类变化。本文运用深度学习中的长短期记忆(LSTM)神经网络作为基本模型对股票数据的收盘价进行预测,选用京粮控股(000505)、东北制药(000597)和中钢国际(000928)三组数据,并在LSTM神经网络中引入Transformer模型。经实验,该模型的预测精度有明显提升,说明Transformer-LSTM网络模型在股票预测领域具有一定的可靠性。In recent years, the global economic and financial environment has been volatile and full of challenges and risks. In this situation, investors’ choices in financial trading have become more complex, and the stock trading market is also facing greater challenges. Traditional econometric models are difficult to fully adapt to such changes. This article uses the Long Short-Term Memory (LSTM) neural network in deep learning as the basic model to predict the closing price of stock data. Three sets of data from Jingliang Holdings (000505), Northeast Pharmaceutical (000597), and Zhonggang International (000928) are selected, and the Transformer model is introduced into the LSTM neural network. Through experiments, the prediction accuracy of the model has been significantly improved, indicating that the Transformer LSTM network model has certain reliability in the field of stock prediction.展开更多
The transformation from multibody models to lumped-parameter models is a crucial aspect of vehicle dynamics research.The velocity transformation method is adopted in this research,and the suspension multibody model is...The transformation from multibody models to lumped-parameter models is a crucial aspect of vehicle dynamics research.The velocity transformation method is adopted in this research,and the suspension multibody model is described using only one degree of freedom.It is found that the equivalent mass of the system is time-dependent during the simulation process,as observed in numerical simulations.Further symbolic calculations are conducted to derive the analytical form of the equivalent mass,and the results show that once the static parameters are determined,the equivalent mass of the suspension system is determined solely by the vertical position of the suspension upright,which reveals the kinematics characteristic of the equivalent mass of the suspension system.It is found that the equivalent mass experiences smaller changes when the suspension is compressed from the middle position,but larger changes when the suspension is extended.Furthermore,by comparing the multibody model,the lumped-parameter model with static mass,and the proposed lumped-parameter model considering the kinematics characteristic of the equivalent unsprung mass,the proposed model produces simulation results that more closely match the original multibody model than the model with static mass.The improvements in accuracy can be up to 20%under certain evaluation metrics.展开更多
This work reveals the significant effects of cobalt(Co)on the microstructure and impact toughness of as-quenched highstrength steels by experimental characterizations and thermo-kinetic analyses.The results show that ...This work reveals the significant effects of cobalt(Co)on the microstructure and impact toughness of as-quenched highstrength steels by experimental characterizations and thermo-kinetic analyses.The results show that the Co-bearing steel exhibits finer blocks and a lower ductile-brittle transition temperature than the steel without Co.Moreover,the Co-bearing steel reveals higher transformation rates at the intermediate stage with bainite volume fraction ranging from around 0.1 to 0.6.The improved impact toughness of the Co-bearing steel results from the higher dense block boundaries dominated by the V1/V2 variant pair.Furthermore,the addition of Co induces a larger transformation driving force and a lower bainite start temperature(BS),thereby contributing to the refinement of blocks and the increase of the V1/V2 variant pair.These findings would be instructive for the composition,microstructure design,and property optimization of high-strength steels.展开更多
文摘In the context of the digital transformation of vocational education,a quality evaluation index system has been constructed.Based on a questionnaire survey conducted among higher vocational colleges and enterprises in Hainan Province,it has been found that the quality of vocational education generally depends on the talent training program and professional construction at the macro level.At the meso level,the teacher level and teaching environment are critical,while at the micro level,the evaluation of talent training quality cannot be underestimated.Strategies for quality improvement in vocational education are proposed from the perspectives of talent training programs,major construction,teacher development,teaching environment,and talent training quality,all under the lens of digital transformation.
基金funded by the Key-Area Research and Development Program of Guangdong Province(Grant No.2022B0202070002)the Guangxi Science and Technology Major Program(Grant No.GuikeAA23023007-2)+1 种基金the Guangdong Province Modern Agricultural Industry Technology System Innovation Team Construction Project(2024CXTD19)Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515010303)。
文摘Agrobacterium tumefaciens-mediated transformation has been widely adopted for plant genetic engineering and the study of gene function(Krenek et al.,2015).This method is prevalent in the genetic transformation of herbaceous plants,with notable applications in species such as Arabidopsis(Yin et al.,2024),soybean(Zhang et al.,2024),rice(Zhang et al.,2020),and Chinese cabbage(Li et al.,2021).However,its application in fruit trees is limited.This is primarily due to their long growth cycles and lack of rapid,efficient,and stable transgenic systems,which severely hinders foundational research involving plant genetic transformation(Mei et al.,2024).Furthermore,for subtropical fruit trees,the presence of recalcitrant seeds adds an extra layer of difficulty to genetic transformation(Umarani et al.,2015),as most methods rely on seed germination as a basis for transformation.
基金financially supported by the National Key Re-search and Development Program of China(No.2021YFB3702604)the National Natural Science Foundation of China(No.52174377)+1 种基金the Chongqing Natural Science Foundation Project(No.CSTB2023NSCQ-MSX0824)This work was also supported by the Shaanxi Materials Analysis&Research Center and the Analytical&Testing Center of NPU.
文摘Theβsolidifiedγ-TiAl alloy holds important application value in the aerospace industry,while its com-plex phase compositions and geometric structures pose challenges to its microstructure control during the thermal-mechanical process.The microstructure evolution of Ti-43Al-4Nb-1Mo-0.2B alloy at 1200℃/0.01 s−1 was investigated to clarify the coupling role of dynamic recrystallization(DRX)and phase transformation.The results revealed that the rate of DRX inα2+γlamellar colonies was comparatively slower than that inβo+γmixed structure,instead being accompanied by intense lamellar kinking and rotation.The initiation and development rates of DRX inα2,βo,andγphases decreased sequentially.The asynchronous DRX of the various geometric structures and phase compositions resulted in the un-even deformed microstructure,and the dynamic softening induced by lamellar kinking and rotation was replaced by strengthened DRX as strain increased.Additionally,the blockyα2 phase and the terminals ofα2 lamellae were the preferential DRX sites owing to the abundant activated slip systems.Theα2→βo transformation within lamellar colonies facilitated DRX and fragment ofα2 lamellae,while theα2→γtransformation promoted the decomposition ofα2 lamellae and DRX ofγlamellae.Moreover,the var-iedβo+γmixed structures underwent complicated evolution:(1)Theγ→βo transformation occurred at boundaries of lamellar colonies,followed by simultaneous DRX ofγlamellar terminals and neighboringβo phase;(2)DRX occurred earlier within the band-likeβo phase,with the delayed DRX in enclosedγphase;(3)DRX within theβo synapses and neighboringγphase was accelerated owing to generation of elastic stress field;(4)Dispersedβo particles triggered particle stimulated nucleation(PSN)ofγphase.Eventually,atomic diffusion along crystal defects inβo andγphases caused fracture of band-likeβo phase and formation of massiveβo particles,impeding grain boundary migration and hindering DRXed grain growth ofγphase.
文摘近年来,全球经济金融环境动荡不安,充满挑战与风险,在此情况下,投资者在金融交易方面的抉择更加复杂,股票交易市场也面临着更大的挑战,传统的计量经济学模型难以充分适应此类变化。本文运用深度学习中的长短期记忆(LSTM)神经网络作为基本模型对股票数据的收盘价进行预测,选用京粮控股(000505)、东北制药(000597)和中钢国际(000928)三组数据,并在LSTM神经网络中引入Transformer模型。经实验,该模型的预测精度有明显提升,说明Transformer-LSTM网络模型在股票预测领域具有一定的可靠性。In recent years, the global economic and financial environment has been volatile and full of challenges and risks. In this situation, investors’ choices in financial trading have become more complex, and the stock trading market is also facing greater challenges. Traditional econometric models are difficult to fully adapt to such changes. This article uses the Long Short-Term Memory (LSTM) neural network in deep learning as the basic model to predict the closing price of stock data. Three sets of data from Jingliang Holdings (000505), Northeast Pharmaceutical (000597), and Zhonggang International (000928) are selected, and the Transformer model is introduced into the LSTM neural network. Through experiments, the prediction accuracy of the model has been significantly improved, indicating that the Transformer LSTM network model has certain reliability in the field of stock prediction.
基金This work was supported by the National Natural Science Foundation of China(Grant No.12272141)The financial support is gratefully acknowledged.
文摘The transformation from multibody models to lumped-parameter models is a crucial aspect of vehicle dynamics research.The velocity transformation method is adopted in this research,and the suspension multibody model is described using only one degree of freedom.It is found that the equivalent mass of the system is time-dependent during the simulation process,as observed in numerical simulations.Further symbolic calculations are conducted to derive the analytical form of the equivalent mass,and the results show that once the static parameters are determined,the equivalent mass of the suspension system is determined solely by the vertical position of the suspension upright,which reveals the kinematics characteristic of the equivalent mass of the suspension system.It is found that the equivalent mass experiences smaller changes when the suspension is compressed from the middle position,but larger changes when the suspension is extended.Furthermore,by comparing the multibody model,the lumped-parameter model with static mass,and the proposed lumped-parameter model considering the kinematics characteristic of the equivalent unsprung mass,the proposed model produces simulation results that more closely match the original multibody model than the model with static mass.The improvements in accuracy can be up to 20%under certain evaluation metrics.
基金supported by the National Natural Science Foundation of China(No.52271089)the financial support from the C hina Postdoctoral Science Foundation(No.2023M732192)。
文摘This work reveals the significant effects of cobalt(Co)on the microstructure and impact toughness of as-quenched highstrength steels by experimental characterizations and thermo-kinetic analyses.The results show that the Co-bearing steel exhibits finer blocks and a lower ductile-brittle transition temperature than the steel without Co.Moreover,the Co-bearing steel reveals higher transformation rates at the intermediate stage with bainite volume fraction ranging from around 0.1 to 0.6.The improved impact toughness of the Co-bearing steel results from the higher dense block boundaries dominated by the V1/V2 variant pair.Furthermore,the addition of Co induces a larger transformation driving force and a lower bainite start temperature(BS),thereby contributing to the refinement of blocks and the increase of the V1/V2 variant pair.These findings would be instructive for the composition,microstructure design,and property optimization of high-strength steels.
