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Timestamp-Guided Knowledge Distillation for Robust Sensor-Based Time-Series Forecasting. [PDF]
Yan J, Li H, Bai Y, Liu J, Lv H, Bai Y.
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CLM-former for enhancing multi-horizon time series forecasting and load prediction in smart microgrids using a robust transformer-based model. [PDF]
Rahmatinia SM +2 more
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Time series forecasting of infant mortality rate in India using Bayesian ARIMA models. [PDF]
Singh A +3 more
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A novel LLM time series forecasting method based on integer-decimal decomposition. [PDF]
Wang L, Dong K, Zhao X.
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Consistency regularization for few shot multivariate time series forecasting. [PDF]
She Y +5 more
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A multiscale model for multivariate time series forecasting. [PDF]
Naghashi V, Boukadoum M, Diallo AB.
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Forecasting Trends in Time Series
Management Science, 1985Most time series methods assume that any trend will continue unabated, regardless of the forecast lead time. But recent empirical findings suggest that forecast accuracy can be improved by either damping or ignoring altogether trends which have a low probability of persistence.
Everette S. Gardner, Jr., Ed. Mckenzie
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Time Series Forecasting as a Measure
International Journal of Advanced Pervasive and Ubiquitous Computing, 2013In this paper, the time series prediction is as a measure. At the same time, the optimal combination forecast using each method can be defined as the actual impact measurement value of true. Effect of its theoretical estimation has error correlation coefficient values.
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