Application of projection pursuit regression model for blasting vibration velocity peak prediction

• Autorzy: Shi Jianjun , An Huaming , Wei Xin

Identyfikatory

DOI

10.24425/ace.2021.137190

• Języki publikacji: EN

Abstrakty

EN

Based on Projection Pursuit Regression Theory (PPRT), a projection pursuit regression model has been established for forecasting the peak value of blasting vibration velocity. The model is then used to predict the peak value of blasting vibration velocity in a tunnel excavation blasting in Beijing. In order to train and test the model, 15 sets of measured samples from the tunnel project are used as the input data. It is found that predicting results by projection pursuit regression model on the basis of the input data is much more reasonable than that predicted by the traditional Sodaovsk algorithm and modified Sodaovsk formula. The results show that the average predicting error of the projection pursuit regression model is 6.36%, which is closer to the measured values. Thus, the projection pursuit prediction model is a practical and reasonable tool for forecasting the peak value of blasting vibration velocity.

Słowa kluczowe

EN

blasting vibration; vibration velocity; prediction; projection pursuit; regression model; shallow tunnel; genetic algorithm

PL

wibracje wybuchowe; przewidywanie; prędkość drgań; model regresji; pościg projekcji; płytki tunel; algorytm genetyczny

• Wydawca: Komitet Inżynierii Lądowej i Wodnej PAN ; Politechnika Warszawska, Wydział Inżynierii Lądowej
• Czasopismo: Archives of Civil Engineering
• Rocznik: 2021
• Tom: Vol. 67, nr 2
• Strony: 653--673
• Opis fizyczny: Bibliogr. 29 poz., il., tab.

Twórcy

autor

Shi Jianjun

• Beijing Key Laboratory of Urban Underground Space Engineering, School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing, China

autor

An Huaming

• Kunming University of Science and Technology, Faculty of Public Security and Emergency Management, Kunming, China

• https://orcid.org/0000-0003-2254-2276

autor

Wei Xin

• University of Science and Technology Beijing, School of Civil and Resource Engineering, Beijing, China (student)

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