Purpose: Traffic volume in empty container depots has been highly volatile due to external factors. Forecasting the expected container truck traffic along with having a dynamic module to foresee the future workload plays a critical role in improving the work efficiency. This paper studies the...

The proliferation of business data and on-demand computing have propelled the use of artificial intelligence methods in quantitative forecasting. Machine learning has a prominent role in solving clustering and classification problems as well as dimensionality reduction. Nevertheless, traditional...

Purpose: This paper aims to give an overview about the current state of research in the field of machine learning methods in demand planning. A cross-industry analysis for current machine learning approaches within the field of demand planning provides a decision-making support for the...

This paper focus on measuring the performance of algortimic trading in now-casting of stock returns using machine learning technics. For this task, (1) nine commonly used trend indicators to capture the behavior of the stock and a binary variable to signal positive/negative returs are used as...