机译:基于贝叶斯粒子滤波方法的实时概率信道洪水预报模型
Tsinghua Univ, Dept Hydraul Engn, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China;
Pacific Northwest Natl Lab, Joint Global Change Res Inst, 5825 Univ Res Court,Suite 3500, College Pk, MD 20740 USA|Michigan State Univ, Great Lakes Bioenergy Res Ctr, E Lansing, MI 48824 USA;
Tsinghua Univ, Dept Hydraul Engn, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China;
Yellow River Inst Hydraul Res, Zhengzhou 450003, Peoples R China;
Tsinghua Univ, Dept Hydraul Engn, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China;
Tsinghua Univ, Dept Hydraul Engn, State Key Lab Hydrosci & Engn, Beijing 100084, Peoples R China;
China Inst Water Resources & Hydropower Res, Water Environm Dept, Beijing 100038, Peoples R China;
Channel flood forecasting; Probabilistic forecast; Particle filter; Data assimilation; Three Gorges Dam;
机译:使用基于贝叶斯推理的概率指示和高阶粒子过滤框架进行机器健康预测
机译:基于贝叶斯概率模型的协同过滤推荐系统的非负矩阵分解
机译:基于广义概率粒子滤波的实时虹膜跟踪
机译:使用具有适当杂波强度的粒子PHD滤波器的贝叶斯实时交通状态估计方法
机译:基于粒子过滤器的视频跟踪:粒子分配,图形模型和性能评估。
机译:基于微血管测量的基于模型的推断:使用贝叶斯概率方法将实验测量与模型预测相结合
机译:基于用户异常评级行为检测的协同过滤推荐系统强大的贝叶斯概率矩阵分解模型