16 hours ago · Abstract. This study analyzes the application of machine learning (ML) and deep learning (DL) models to forecast hourly national energy consumption.

16 hours ago · This study proposes a time-series forecasting methodology to predict the scale and structural trends of South Korea's doctorate-level S&T workforce. Based on ...

1 day ago · The objective of this study is to construct a time-series analysis model that can comprehend sales and profits/losses while forecasting future values. To ...

3 days ago · In this paper, we introduce a novel approach called Optimal Starting Point Time Series Forecast (OSP-TSP) to capture the intrinsic characteristics of time ...

6 days ago · We present a method for predicting hyperchaotic time series using a complex network-based forecasting model. We first construct a network from a given time ...

3 days ago · In this paper we present a forecasting method for time series using copula-based models for multivariate time series.

15 hours ago · Abstract- This study analyzes the application of machine learning (ML) and deep learning (DL) models to forecast hourly national energy consumption.

7 days ago · Multivariate Time Series (MTS) forecasting is a fundamental task with numerous real-world applications, such as transportation, climate, and epidemiology.

7 days ago · This study presents an improved data-centric approach to short-term water demand forecasting using univariate time series from water reservoir levels.

6 days ago · In this paper, we first demonstrate that, for the time series forecasting (TSF) task, the previously overlooked decoder-only autoregressive Transformer model ...