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Weekly Hotel Occupancy Forecasting of a Tourism Destination
2018
Sustainability
The accurate forecasting of tourism demand is complicated by the dynamic tourism marketplace and its intricate causal relationships with economic factors. In order to enhance forecasting accuracy, we present a modified ensemble empirical mode decomposition (EEMD)–autoregressive integrated moving average (ARIMA) model, which dissects a time series into three intrinsic model functions (IMFs): high-frequency fluctuation, low-frequency fluctuation, and a trend; these three signals were then modeled
doi:10.3390/su10124351
fatcat:ekbrnhsywnc65kkwtzs6ii665q