A confidence-weighted exponential moving average was introduced to improve the robustness and interpretability of UAV-based speed estimation under complex observation conditions. This update adds ...

Predictive models turn historical data into reliable forecasts that support accurate planning across industries. Different modeling types solve different problems, from forecasting numbers to ...

Demand forecasting is a critical component of supply chain management and business operations. While traditional demand forecasting methods are geared towards continuous and stable demand patterns, ...

Three models for yearly time series predictions were built: autoregressive integrated moving average (ARIMA), simple exponential smoothing (SES), and Holt's double expansional smoothing (HDES) models.

Supply chain management usually faces problems such as high empty rate of transportation, unreasonable inventory management, and large material consumption caused by inaccurate market demand forecasts ...

The era of modern financial data modeling seeks machine learning techniques which are suitable for noisy and non-stationary big data. We demonstrate how a general class of exponential smoothed ...