Forecasting, Volume 7, Issue 2

Financial fraud detection is a critical application area within the broader domains of cybersecurity and intelligent financial analytics. With the growing volume and complexity of digital transactions, the traditional rule-based and shallow learning...

In recent years, the prominence of probabilistic forecasting has risen among numerous research fields (finance, meteorology, banking, etc.). Best practices on using such forecasts are, however, neither well explained nor well understood. The question...

Flooding is the most frequent natural hazard that accompanies hardships for millions of civilians and substantial economic losses. In Sri Lanka, fluvial floods cause the highest damage to lives and properties. Ratnapura, which is in the Kalu River Ba...

This study addresses the challenge of predicting the airtightness of stratospheric airship envelopes, a critical factor influencing flight performance. Traditional ground-based airtightness tests often rely on limited resources and empirical formulas...

Wind data are often cyclostationary due to cyclic variations, non-constant variance resulting from fluctuating weather conditions, and structural breaks due to transient behaviour (due to wind gusts and turbulence), resulting in unreliable wind power...

This study introduces a novel forecasting framework that identifies and predicts recurrently emerging structural patterns in stock trends using rising visibility graphs (RVGs) and the Weisfeiler–Lehman (WL) subtree kernel. The proposed method,...

In this work, we present a novel approach for predicting short-term electrical energy consumption. Most energy consumption methods work well for their case study datasets. The proposed method utilizes a cloud computing platform that allows for integr...

Water temperature is a fundamental parameter influencing a range of biotic and abiotic processes occurring within various components of the hydrosphere. This study presents a multi-step, data-driven predictive modeling framework to estimate water tem...

Natural gas consumption in Europe has undergone substantial changes in recent years, driven by geopolitical tensions, economic dynamics, and the continent’s ongoing transition towards cleaner energy sources. Furthermore, as noted in the Interna...

This article describes a robust Gaussian Prior process state space modeling (GPSSM) approach to assess the impact of an intervention in a time series. Numerous applications can benefit from this approach. Examples include: (1) time series could be th...