such as data coming from a single unit (i.e., univariate time series) and having observations that are regularly spaced are frequently linked to time series. Furthermore, time series can be generated from multiple units (multivariate time series) and can accommodate variations in overtime ...
Purpose of this paper is to model the data FTT paddy crops using autoregressive integrated moving average method (ARJMA) and multivariate adaptive regression splines time series (TS_MARS). Having acqu ired two models, it wi ll be compared to a better modei. Comparison of models based on the...
Voyant, C.; Muselli, M.; Paoli, C.; Nivet, M.-L. Optimization of an artificial neural network dedicated to the multivariate forecasting of daily global radiation.Energy2011,36, 348–359. [Google Scholar] [CrossRef] Ramedani, Z.; Omid, M.; Keyhani, A.; Shamshirband, S.; Khoshnevisan...
000 cases nationally. This recent escalation of the Monkeypox outbreak has become a severe and urgent worldwide public health concern. We aimed to develop an efficient forecasting tool that allows health experts to implement effective prevention policies for Monkeypox and shed light on the case ...