High quality grids generation and numerical simulation of the flow field around wing-body configuration

Li, Zhan-ke; Wu, Meng

doi:10.1109/csae.2011.5953243

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2023

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“…The development of blasting technology ushered in a climax again with the concept of "Fine Blasting" [1][2] . Although the demolition efficiency of traditional blasting technology has been guaranteed, it is particularly passive in terms of safety protection.…”

Section: Introductionmentioning

confidence: 99%

Prediction of thickness of blasting scatter water belt based on GA-BP and PSO-BP

Liu,

Cai,

Liu

et al. 2023

Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023)

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In this paper, a method for predictive analysis is proposed based on BP neural network optimized by genetic algorithm and BP neural network optimized based on particle swarm algorithm. By optimizing the initial weight and threshold of the neural network by the algorithm, showing the error between the predicted value and the real value, and comparing the mean squared error of the three, the MSE of the GA-BP prediction model is reduced by 56.53% compared with the BP neural network prediction model. The MSE of the PSO-BP network predictive model was reduced by 50.00%. The results show that this method can accurately predict the thickness of the blasting protective water belt, which provides a new and reliable method for the study of controlling blasting flying objects.

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Section: Introductionmentioning

confidence: 99%