Risk Management Innovations through Neural Network Integration in Automated Boiler Combustion Systems

Authors

DOI:

https://doi.org/10.31181/jscda31202565

Keywords:

Neural networks , Risk management, Automatic boilers, Combustion optimization

Abstract

In the early decades of the twenty-first century, the application of artificial intelligence has been expanding across all sectors of society, including industrial energy systems. This paper emphasizes the significance of integrating artificial neural networks into boilers with automatic firing, as part of a research project currently in its fifth year of experimental validation. The implementation of neural networks in such systems has demonstrated promising results in the domain of risk management, particularly through the prediction of system malfunctions and their proactive elimination via software interventions. The application of AI-based solutions in boiler control not only contributes to the reduction of environmental impact but also enhances operational safety by preventing accidents that may endanger human health and cause material losses. 

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References

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Published

2025-07-19

Issue

Vol. 3 No. 1 (2025): Journal of Soft Computing and Decision Analytics

Section

Articles

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Copyright (c) 2025 Stefan Popovic, Sonja Djukic Popovic, Nebojsa Denic, Dejan Djukic, Jelena Stojanovic (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Popovic, S., Djukic Popovic, S., Denic, N., Djukic, D., & Stojanovic, J. (2025). Risk Management Innovations through Neural Network Integration in Automated Boiler Combustion Systems. Journal of Soft Computing and Decision Analytics, 3(1), 129-135. https://doi.org/10.31181/jscda31202565