To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game mod...To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game model of gov-ernment,commercial banks,and automobile enterprises;introduced a dynamic reward and punishment mechanism;and analyzed the development process of the three parties’strategic behavior under the static and dynamic reward and punish-ment mechanism.Vensim PLE was used for numerical simulation analysis.Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism.A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations.Under the dynamic reward and punishment mechan-ism,an increase in the initial probabilities of the three parties can promote the system stability,and the government can im-plement effective supervision by adjusting the upper limit of the reward and punishment intensity.Finally,the implementa-tion of green credit by commercial banks plays a significant role in promoting the green development of automobile enter-prises.展开更多
针对论文引用预测方法在特征稀疏时性能下降的问题,提出了基于异构特征融合的方法,可同时利用定长特征、引文网络特征和引文时序特征,有效提升了引用预测方法的精度。本文针对论文引用预测任务定义了引文属性网络,对3类异构特征进行建模...针对论文引用预测方法在特征稀疏时性能下降的问题,提出了基于异构特征融合的方法,可同时利用定长特征、引文网络特征和引文时序特征,有效提升了引用预测方法的精度。本文针对论文引用预测任务定义了引文属性网络,对3类异构特征进行建模;提出了面向异构特征融合的论文引用预测方法,使用图神经网络处理定长特征和引文网络特征,使用循环神经网络处理引文时序特征,基于多头注意力机制对提取到的异构特征进行融合并预测被引次数。在大规模真实数据集上的实验表明,本文方法可以有效利用多种异构特征并缓解数据稀疏问题,均方根误差(Root mean squatr error,RMSE)比最好的基准方法降低了0.31。展开更多
基金supported by the National Natural Science Foundation of China(71973001).
文摘To explore the green development of automobile enterprises and promote the achievement of the“dual carbon”target,based on the bounded rationality assumptions,this study constructed a tripartite evolutionary game model of gov-ernment,commercial banks,and automobile enterprises;introduced a dynamic reward and punishment mechanism;and analyzed the development process of the three parties’strategic behavior under the static and dynamic reward and punish-ment mechanism.Vensim PLE was used for numerical simulation analysis.Our results indicate that the system could not reach a stable state under the static reward and punishment mechanism.A dynamic reward and punishment mechanism can effectively improve the system stability and better fit real situations.Under the dynamic reward and punishment mechan-ism,an increase in the initial probabilities of the three parties can promote the system stability,and the government can im-plement effective supervision by adjusting the upper limit of the reward and punishment intensity.Finally,the implementa-tion of green credit by commercial banks plays a significant role in promoting the green development of automobile enter-prises.
文摘针对论文引用预测方法在特征稀疏时性能下降的问题,提出了基于异构特征融合的方法,可同时利用定长特征、引文网络特征和引文时序特征,有效提升了引用预测方法的精度。本文针对论文引用预测任务定义了引文属性网络,对3类异构特征进行建模;提出了面向异构特征融合的论文引用预测方法,使用图神经网络处理定长特征和引文网络特征,使用循环神经网络处理引文时序特征,基于多头注意力机制对提取到的异构特征进行融合并预测被引次数。在大规模真实数据集上的实验表明,本文方法可以有效利用多种异构特征并缓解数据稀疏问题,均方根误差(Root mean squatr error,RMSE)比最好的基准方法降低了0.31。
