Timely and accurate wheat yield forecasts using Unmanned Aircraft Vehicles (UAV) are crucial for crop management decisions, food security, and ensuring the sustainability of agriculture worldwide. While traditional machine learning algorithms have already been used in crop yield modelling,...

This article investigates the macroeconomic and labor market conditions that shape the adoption of artificial intelligence (AI) technologies among large firms in Europe. Based on panel data econometrics and supervised machine learning techniques, we estimate how public health spending, access to...

Exhaustive hyperparameter search techniques such as grid search and random search are widely used in predictive analytics but become computationally expensive and often suboptimal in high-dimensional or nonlinear settings. This challenge is particularly clear in tuning Cycle Reservoir with Jumps...

Predicting delivery delays is crucial for companies, especially in times of increasing global uncertainty and vulnerable supply chains. Machine learning (ML) offers significant potential to improve the forecast performance and quality of delivery delay prediction. Although various prediction...

In today's dynamic technological environment, the integration of IoT into Supply Chain Management Systems (SCMS) has significantly enhanced functionality, visibility, and decision-making. However, integrating Industrial-IoT (IIoT) with Supply Chain Networks (SCN) is an equally significant...