Safety risk assessment of green building construction based on BP neural network optimized by genetic algorithm

Xiaofei Zhang; Yueming Wang

doi:10.1117/12.3004689

9 October 2023 Safety risk assessment of green building construction based on BP neural network optimized by genetic algorithm

Xiaofei Zhang, Yueming Wang

Author Affiliations +

Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 127910K (2023) https://doi.org/10.1117/12.3004689
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China

Abstract

This study examines the assessment of construction safety risks in green building risk management. By comprehensively considering all factors that affect the safety of green building construction, an evaluation index system is established. The AHP method is used to weigh each index, expert scoring determines the risk level of each project index, and the weighted summation results in the expected output value. In addition, the genetic algorithm (GA) is introduced to optimize the BP neural network, and an evaluation model based on AHP and GA-BP neural network is established that can be used to predict and evaluate construction safety risks. The results show that this method can effectively predict the safety risk of green building construction and provide valuable guidance for the safety management of green building construction.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaofei Zhang and Yueming Wang "Safety risk assessment of green building construction based on BP neural network optimized by genetic algorithm", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 127910K (9 October 2023); https://doi.org/10.1117/12.3004689

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