This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution pric...This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.展开更多
在大地形三维多分辨率显示中,针对裂缝消除问题提出了一种基于LOD(Level of Detail)控制和裂缝可视性的改进算法。证明在四叉树网格可视距离/尺寸比>3时,必然满足限制四叉树约束;基于裂缝的可见性,在预处理阶段通过区分地形上升裂缝...在大地形三维多分辨率显示中,针对裂缝消除问题提出了一种基于LOD(Level of Detail)控制和裂缝可视性的改进算法。证明在四叉树网格可视距离/尺寸比>3时,必然满足限制四叉树约束;基于裂缝的可见性,在预处理阶段通过区分地形上升裂缝和地形下降裂缝,为后者添加与裂缝大小一致的几何图形来生成裂缝消除补丁;在实时渲染过程中,既不需要通过CPU计算来控制网格的层次差,也不需要通过CPU来识别相邻网格层次差和消除裂缝。实验测试表明:该算法简单有效,附加网格数据比裙边算法减少约75%,且完全能够避免地形裂缝的显示。展开更多
基于激励与约束的博弈机制式表述方法,根据科学与工程计算网格(science and engineering computinggrid,SECGrid)应用特点,对网格计算资源负载与计算性能下降的相关问题进行了分析,将实际应用中影响计算资源使用性能的因素与双方经济效...基于激励与约束的博弈机制式表述方法,根据科学与工程计算网格(science and engineering computinggrid,SECGrid)应用特点,对网格计算资源负载与计算性能下降的相关问题进行了分析,将实际应用中影响计算资源使用性能的因素与双方经济效益目标,由定性转化为定量,构建合理效益函数,指导计算网格资源分配.将影响网格资源分配的各种因素划分、归类为相应的激励与约束策略和行动,并对其进行动态调整,引导和协调资源主体调节自身行为,充分共享更多的有效资源,使双方效益趋于最大.展开更多
基金the National Key Research and Development Program of China(Grant No.2020YFB1707804)the 2018 Key Projects of Philosophy and Social Sciences Research(Grant No.18JZD032)Natural Science Foundation of Hebei Province(Grant No.G2020403008).
文摘This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine(DRBM)optimized by the Lion algorithm(LA).Firstly,two factors including transmission and distribution price reform(TDPR)and 5G station construction were comprehensively incorporated into the consideration of influencing factors,and the fuzzy threshold method was used to screen out critical influencing factors.Then,the LA was used to optimize the parameters of the DRBM model to improve the model’s prediction accuracy,and the model was trained with the selected influencing factors and investment.Finally,the LA-DRBM model was used to predict the investment of a power grid enterprise,and the final prediction result was obtained by modifying the initial result with the modifying factors.The LA-DRBMmodel compensates for the deficiency of the singlemodel,and greatly improves the investment prediction accuracy of the power grid.In this study,a power grid enterprise was taken as an example to carry out an empirical analysis to prove the validity of the model,and a comparison with the RBM,support vector machine(SVM),back propagation neural network(BPNN),and regression model was conducted to verify the superiority of the model.The conclusion indicates that the proposed model has a strong generalization ability and good robustness,is able to abstract the combination of low-level features into high-level features,and can improve the efficiency of the model’s calculations for investment prediction of power grid enterprises.
文摘在大地形三维多分辨率显示中,针对裂缝消除问题提出了一种基于LOD(Level of Detail)控制和裂缝可视性的改进算法。证明在四叉树网格可视距离/尺寸比>3时,必然满足限制四叉树约束;基于裂缝的可见性,在预处理阶段通过区分地形上升裂缝和地形下降裂缝,为后者添加与裂缝大小一致的几何图形来生成裂缝消除补丁;在实时渲染过程中,既不需要通过CPU计算来控制网格的层次差,也不需要通过CPU来识别相邻网格层次差和消除裂缝。实验测试表明:该算法简单有效,附加网格数据比裙边算法减少约75%,且完全能够避免地形裂缝的显示。
文摘基于激励与约束的博弈机制式表述方法,根据科学与工程计算网格(science and engineering computinggrid,SECGrid)应用特点,对网格计算资源负载与计算性能下降的相关问题进行了分析,将实际应用中影响计算资源使用性能的因素与双方经济效益目标,由定性转化为定量,构建合理效益函数,指导计算网格资源分配.将影响网格资源分配的各种因素划分、归类为相应的激励与约束策略和行动,并对其进行动态调整,引导和协调资源主体调节自身行为,充分共享更多的有效资源,使双方效益趋于最大.
