Popirlan Claudiu Ionut, Tudor Irina-Valentina, Popirlan Cristina
Department of Computer Science, University of Craiova, Craiova, Dolj, Romania.
PeerJ Comput Sci. 2023 Jul 10;9:e1464. doi: 10.7717/peerj-cs.1464. eCollection 2023.
This article analyzes the correlation between energy poverty percentage and unemployment rate for four European countries, Bulgaria, Hungary, Romania and Slovakia, comparing the results with the European average. The time series extracted from the datasets were imported in a hybrid model, namely ARIMA-ARNN, generating predictions for the two variables in order to analyze their interconnectivity. The results obtained from the hybrid model suggest that unemployment rate and energy poverty percentage have comparable tendencies, being strongly correlated. The forecasts suggest that this correlation will be maintained in the future unless appropriate governmental policies are implemented in order to lower the impact of other aspects on energy poverty.
本文分析了保加利亚、匈牙利、罗马尼亚和斯洛伐克这四个欧洲国家的能源贫困率与失业率之间的相关性，并将结果与欧洲平均水平进行比较。从数据集中提取的时间序列被导入到一个混合模型，即自回归积分滑动平均-人工递归神经网络（ARIMA-ARNN）中，对这两个变量进行预测，以分析它们的相互关联性。混合模型得出的结果表明，失业率和能源贫困率具有可比的趋势，且相关性很强。预测表明，除非实施适当的政府政策以降低其他因素对能源贫困的影响，否则这种相关性在未来将持续存在。
