机译:地球同步电子通量的人工神经网络预测模型:取决于卫星位置和粒子能量
Department of Astronomy and Space Science, Chungbuk National University, Cheongju, South Korea, Korea Astronomy and Space Science Institute, and Department of Astronomy and Space Science, Korea University of Science and Technology, Daejeon, South Korea;
Department of Astronomy and Space Science, Chungbuk National University, Cheongju, South Korea;
Division of Science Education, College of Education, Daegu University, Gyeongsan, Gyeongbuk, South Korea;
Korea Astronomy and Space Science Institute, and Department of Astronomy and Space Science, Korea University of Science and Technology, Daejeon, South Korea;
Korean Space Weather Center, National Radio Research Agency, Jeju, South Korea;
Predictive models; Neural networks; Satellites; Autoregressive processes; Magnetic separation; Satellite broadcasting; Meteorology;
机译:数据分类的回归和人工神经网络模型用于建筑能耗预测
机译:使用人工神经网络,高光谱卫星数据和现场光谱法预测建模与土壤碳含量的映射
机译:基于人工神经网络的纳米二氧化硅纤维增强自密实混凝土能量吸收能力预测
机译:利用人工神经网络(ANN)预测高能粒子淋浴的一次能量和堆芯位置
机译:磁层规范模型,Garrett模型和地球同步电子通量卫星数据的比较。
机译:利用卫星测量的相对湿度预测油棕人工林中的平面螳螂种群:回归和人工神经网络模型的比较评估
机译:地球同步电子通量的人工神经网络预测模型:依赖卫星位置和颗粒能量