Researchers Develop AI-Powered Algorithm for Precise Fire Temperature Prediction

Researchers at Southeast University in Nanjing, China have developed a novel fusion fire temperature prognosis algorithm that combines wavelet neural networks and whale optimization algorithms. This algorithm has been shown to provide accurate and real-time temperature field predictions in large-space building fires, surpassing traditional wavelet neural networks. The research was supported by the National Program on Key R & D Project of China and has been peer-reviewed.

Key Takeaways:

• The researchers developed a fusion fire temperature prognosis algorithm that integrates wavelet neural networks and whale optimization algorithms to provide accurate and real-time temperature field predictions in large-space building fires.
• The algorithm has been shown to be more efficient and effective than traditional wavelet neural networks, offering real-time adaptive learning through sensor data without dependence on pre-existing training datasets.
• The research includes two application instances of future temperature field predictions in a large underground parking fire and a large subway station fire, which validated the algorithm's efficacy.
• The algorithm was developed to facilitate real firefighting applications and has been shown to be a valuable tool for achieving rapid temperature prognosis in large-space building fires.
• The research was supported by the National Program on Key R & D Project of China and has been peer-reviewed by the Journal of Cleaner Production.

Statistics:

• The algorithm was tested in two application instances, including a large underground parking fire and a large subway station fire.
• The research concluded that the algorithm is efficacious and surpasses traditional wavelet neural networks in terms of accuracy and efficiency.
• The algorithm provides real-time temperature field predictions, allowing for more effective firefighting strategies.
• The research was supported by the National Program on Key R & D Project of China, with a grant amount not specified in the source material.

Sources:

• NewsRx. Findings from Southeast University Broaden Understanding of Environment and Sustainability Research (Wavelet Neural Network and Whale Optimization Fusion Fire Temperature Prognosis In Large-space Buildings). Ecology, Environment & Conservation. July 11, 2025; p 156.
• Wavelet Neural Network and Whale Optimization Fusion Fire Temperature Prognosis In Large-space Buildings. Journal of Cleaner Production, 2025;513.
• Journal of Cleaner Production. "Wavelet Neural Network and Whale Optimization Fusion Fire Temperature Prognosis In Large-space Buildings."
• Southeast University. China Pakistan Belt & Rd Joint Lab Smart Disaster, Nanjing 210096, People's Republic of China.