为尽可能地提高大气加权平均温度的估计精度,利用神经网络所建立的大气加权平均温度模型,却未顾及大气加权平均温度的长期变化趋势。因此,本文利用全球气候第五代再分析数据集和大气逐层数据,考虑大气加权平均温度的年际变化,基于多层...为尽可能地提高大气加权平均温度的估计精度,利用神经网络所建立的大气加权平均温度模型,却未顾及大气加权平均温度的长期变化趋势。因此,本文利用全球气候第五代再分析数据集和大气逐层数据,考虑大气加权平均温度的年际变化,基于多层感知器建立了湟水流域大气加权平均温度模型,并使用探空数据与已有的六种模型进行了比较验证分析。结果表明:本模型的年均偏差和均方根误差分别为–0.01 K、2.71 K;均方根误差相比于Bevis式、双因子、多因子、全球气压温度3(global pressure and temperature 3,GPT3)、改进的GPT3模型、谢劭峰等(2022)方法分别减小了32%、23%、15%、14%、7%、5%。验证了引入年际变化因子可进一步提高神经网络模型的精度,建立了目前湟水流域精度相对最优的大气加权平均温度模型。展开更多
As the main food source for humans, the global movement of the three major grains significantly impacts human survival and development. To investigate the evolution of the world cereal trade network and its developmen...As the main food source for humans, the global movement of the three major grains significantly impacts human survival and development. To investigate the evolution of the world cereal trade network and its development trend, a weighted directed dynamic multiplexed network was established using historical data on cereal trade, cereal import dependency ratio, and arable land per capita. Inspired by the MLP framework, we redefined the weight determination method for computing layer weights and edge weights of the target layer, modified the CN, RA, AA, and PA indicators, and proposed the node similarity indicator for weighted directed networks. The AUC metric, which measures the accuracy of the algorithm, has also been improved in order to finally obtain the link prediction results for the grain trading network. The prediction results were processed, such as web-based presentation and community partition. It was found that the number of generalized trade agreements does not have a decisive impact on inter-country cereal trade. The former large grain exporters continue to play an important role in this trade network. In the future, the world trade in cereals will develop in the direction of more frequent intercontinental trade and gradually weaken the intracontinental cereal trade.展开更多
文摘为尽可能地提高大气加权平均温度的估计精度,利用神经网络所建立的大气加权平均温度模型,却未顾及大气加权平均温度的长期变化趋势。因此,本文利用全球气候第五代再分析数据集和大气逐层数据,考虑大气加权平均温度的年际变化,基于多层感知器建立了湟水流域大气加权平均温度模型,并使用探空数据与已有的六种模型进行了比较验证分析。结果表明:本模型的年均偏差和均方根误差分别为–0.01 K、2.71 K;均方根误差相比于Bevis式、双因子、多因子、全球气压温度3(global pressure and temperature 3,GPT3)、改进的GPT3模型、谢劭峰等(2022)方法分别减小了32%、23%、15%、14%、7%、5%。验证了引入年际变化因子可进一步提高神经网络模型的精度,建立了目前湟水流域精度相对最优的大气加权平均温度模型。
文摘As the main food source for humans, the global movement of the three major grains significantly impacts human survival and development. To investigate the evolution of the world cereal trade network and its development trend, a weighted directed dynamic multiplexed network was established using historical data on cereal trade, cereal import dependency ratio, and arable land per capita. Inspired by the MLP framework, we redefined the weight determination method for computing layer weights and edge weights of the target layer, modified the CN, RA, AA, and PA indicators, and proposed the node similarity indicator for weighted directed networks. The AUC metric, which measures the accuracy of the algorithm, has also been improved in order to finally obtain the link prediction results for the grain trading network. The prediction results were processed, such as web-based presentation and community partition. It was found that the number of generalized trade agreements does not have a decisive impact on inter-country cereal trade. The former large grain exporters continue to play an important role in this trade network. In the future, the world trade in cereals will develop in the direction of more frequent intercontinental trade and gradually weaken the intracontinental cereal trade.
