Abstract
Accurate time series forecasting is crucial across various domains, yet traditional models that rely solely on numerical data often struggle to capture complex patterns in dynamic environments. This work proposes a novel multimodal forecasting framework that integrates visual and numerical data to enhance predictive performance. The framework leverages a FT-Transformer for temporal data processing and a TIMM-based convolutional network for visual data extraction. A hybrid fusion strategy combines these modalities, enabling the model to capture complementary information that improves forecasting accuracy. Empirical evaluations on the M4 dataset demonstrate that the multimodal model consistently outperforms unimodal approaches, achieving up to a 7.0% reduction in Normalized Root Mean Squared Error across multiple forecast horizons. The proposed framework also incorporates an automated training pipeline powered by Optuna, ensuring efficient hyperparameter tuning and scalability across diverse datasets. These results highlight the effectiveness of multimodal integration in advancing time series forecasting performance. © 2026 IEEE.

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Abstract

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Abstract

Abstract
This study aims to map and compare the demand for green skills across four selected African countries by analyzing online job vacancies. Accordingly, the study addresses four research questions: (RQ1) how green skills demand has evolved over time; (RQ2) which sectors exhibit the highest demand for green skills; (RQ3) which occupations are most associated with green skills; and (RQ4) which green competencies are most frequently requested by employers. A Big Data and Labour Market Intelligence approach is employed based on secondary data provided by the online job vacancies (OJV). The results reveal a general upward trend in green skills demand, although with significant cross-country variation. Sectorally, sustainable energy dominates across all countries, followed by more context-specific areas such as agriculture, tourism, and production. At the occupational level, environmental engineers and other technical professions are most strongly associated with green skills. The thematic analysis highlights renewable energy, energy efficiency, and environmental sustainability as the most prominent skill domains, alongside emerging competencies in sustainable mobility, circular economy, and green digital skills. The study contributes to the literature by providing empirical evidence from an underexplored African context and demonstrating the value of online job vacancy data for monitoring labour market transformations.