1 day ago · This paper focuses on projecting complicated stock market price dynamics, weather data variations, and hourly traffic occupancy rates.

3 days ago · Abstract. The accurate forecasting of financial time series remains a significant challenge due to the stochastic nature of the underlying data.

5 days 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 ...

6 days ago · In this paper, we introduce Compositional Time Series Reasoning, a new task of handling intricate multistep reasoning tasks from time series data. Specifically, ...

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

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

6 days ago · This study investigates the forecasting accuracy of human experts versus large language models (LLMs) in the retail sector, particularly during standard and ...

6 days ago · In time series forecasting, time series with high variance tends to mask inherent patterns or trends in the data, making prediction more difficult. Previous ...

5 days ago · In this paper, as an application of fuzzy time series in educational research, the forecast of the enrollments of the University of Alabama is carried out.

6 days ago · The work presented in this article constitutes a contribution to modeling and forecasting the demand in a food company, by using time series approach.