论文标题
部分可观测时空混沌系统的无模型预测
Temperature and Mental Health: Evidence from Helpline Calls
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
This paper studies the short-term effects of ambient temperature on mental health using data on nearly half a million helpline calls in Germany. Leveraging location-based routing of helpline calls and random day-to-day weather fluctuations, I find a negative effect of temperature extremes on mental health as revealed by an increase in the demand for telephone counseling services. On days with an average temperature above 25°C (77°F) and below 0°C (32°F), call volume is 3.4 and 5.1 percent higher, respectively, than on mid-temperature days. Mechanism analysis reveals pronounced adverse effects of cold temperatures on social and psychological well-being and of hot temperatures on psychological well-being and violence. More broadly, the findings of this work contribute to our understanding of how changing climatic conditions will affect population mental health and associated social costs in the near future.
