Articles Open Access
Interpretable Machine Learning Approaches for Fault Diagnosis and Predictive Maintenance in EV Powertrains
Independent Researcher, Canada
Junior Research Assistant, Rhineburg Institute of Applied Sciences, Germany
Abstract
Cape Verde, an archipelago in the Central Atlantic, is confronted with opportunities and challenges associated with the development of business and tourism sectors, including the root and tuber value chains. This phenomenon is associated with climate change that increasingly dictates new business opportunities and new risk factors to be addressed in the world of tourism. This study identified risk scales associated with climate change along the entire root and tuber value chain in the country. In addition to these factors, 85 positive and negative risk factors were identified, classified and described. A set of thematic maps was built, presenting the risk levels and their factors in Cape Verde and in each of the six islands that make up the country. The research indicated that drought and desertification are the most critical climate risks on the islands. The lower development of the root and tuber tourism value chain in Cape Verde offers new opportunities for businesses and tourism. The analysis of the initialized risk factors in the root and tuber value chain provides the foundation for implementing a climate risk management plan, which seeks to minimize, decrease and/or mitigate the consequences for tourism due to the effects of climate change.
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Publication Information
| Journal | International Research Journal of Innovative Engineering |
|---|---|
| Volume | 10 |
| Number | 4 |
| Pages | 19310-19327 |
| Published | 2026-07-13 |
| Issue | Vol. 10 No. 4 (2026): International Research Journal of Innovative Engineering (IRJIE) |
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4. Annapareddy, V. N. (2025). The Intersection of Big Data, Cybersecurity, and ERP Systems: A Deep Learning Perspective. Journal of Artificial Intelligence and Big Data Disciplines, 2(1), 45-53. Pipeline Optimization for Risk Prediction in Cloud-Native Workers’ Compensation Platforms. In 2026 IEEE International Conference for Convergence in Computing Technology (I3CTCON) (pp. 1-6). IEEE.
5. Chabokpour, J., Kalisetty, S., Malempati, M., Challa, K., Mandala, V., Kumar, B., & Azamathulla, H. M. (2025). Integrating Hydrological and Hydraulic Approaches for Adaptive Environmental Flow Management: A Multi-Method Approach for Adaptive River Management in Semi-Arid Regions. Water, 17(7), 926.
6. Singireddy, S., Pandiri, L., Motamary, S., Kummari, D. N., Somu, B., & Lakkarasu, P. (2025, August). Blockchain-Powered Claims Validation for Enhancing Trust in Health and Auto Insurance Ecosystems. In International Conference on Artificial Intelligence: Theory and Applications (pp. 26-38). Cham: Springer Nature Switzerland.
7. Manikandan, K., Pamisetty, V., Challa, S. R., Komaragiri, V. B., Challa, K., & Chava, K. (2025). Scalability and efficiency in distributed big data architectures: a comparative study. Metallurgical and Materials Engineering, 31(3), 40-49.
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11. Challa, K., Challa, S. R., Pamisetty, A., Kaulwar, P. K., & Koppolu, H. K. R. (2025, December). Transforming Payments: The Role of AI and Big Data in Fraud Alerts, Credit Monitoring, and Secure Transactions. In 2025 IEEE International Conference on Communication Networks and Computing (CNC) (pp. 1406-1414). IEEE..
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