Quantile Fourier regressions for decision making under uncertainty
针对具有周期性的马尔可夫决策过程，提出分位数傅里叶回归方法，同时捕捉过程取值和序列依赖结构的周期变化，并通过水电调度和风电并网两个数值例子展示其应用。
Abstract We consider Markov decision processes arising from a Markov model of an underlying natural phenomenon. Such phenomena are usually periodic (e.g. annual) in time, and so the Markov processes modelling them must be time-inhomogeneous, with cyclostationary rather than stationary behaviour. We describe a technique for constructing such processes that allows for periodic variations both in the values taken by the process and in the serial dependence structure. We include two illustrative numerical examples: a hydropower scheduling problem and a model of offshore wind power integration.