论文标题
机器学习模型投射乌克兰危机的影响
Machine learning model to project the impact of Ukraine crisis
论文作者
论文摘要
俄罗斯对乌克兰的袭击于2022年2月24日星期四占据了金融市场和地缘政治危机的增加。在本文中，我们选择了一些主要的经济指数，例如黄金，石油（WTI），NDAQ和已知货币，这些货币涉及这场危机，并试图找到这场战争对他们的定量效应。为了量化战争效应，我们使用相关特征以及这些经济指数之间的关系，创建数据集，并将预测结果与真实数据进行比较。为了研究战争效果，我们使用机器学习线性回归。我们进行经验实验，并在这些经济指数数据集上执行，以评估和预测这一战争及其对主要经济学指数的影响。
Russia's attack on Ukraine on Thursday 24 February 2022 hitched financial markets and the increased geopolitical crisis. In this paper, we select some main economic indexes, such as Gold, Oil (WTI), NDAQ, and known currency which are involved in this crisis and try to find the quantitative effect of this war on them. To quantify the war effect, we use the correlation feature and the relationships between these economic indices, create datasets, and compare the results of forecasts with real data. To study war effects, we use Machine Learning Linear Regression. We carry on empirical experiments and perform on these economic indices datasets to evaluate and predict this war tolls and its effects on main economics indexes.
