Rockburst Prediction Model Based on Entropy Weight Integrated with Grey Relational BP Neural Network

被引：24

作者：

Zheng, Yuchao ^{[1
]}

Zhong, Heng ^{[1
]}

Fang, Yong ^{[1
]}

Zhang, Wensheng ^{[1
]}

Liu, Kai ^{[1
]}

Fang, Jing ^{[1
]}

机构：

[1] Southwest Jiaotong Univ, Sch Civil Engn, Key Lab Transportat Tunnel Engn, Minist Educ, Chengdu, Sichuan, Peoples R China

来源：

ADVANCES IN CIVIL ENGINEERING | 2019年 / 2019卷

基金：

中国国家自然科学基金;

关键词：

HIGHWAY TUNNEL; ROCK; ACCIDENTS;

D O I：

10.1155/2019/3453614

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

A rockburst prediction model of the entropy weight grey relational backpropagation (BP) neural network is developed. The model needs to select the evaluation factors according to the engineering practice and establish the sample library. The entropy weight method is used to calculate the objective weight of the characteristic factors, and the similarity between the samples is calculated by the combination of grey relational theory and the entropy method. The training sample of the BP neural network is selected by threshold determination. Finally, we use the trained neural network to estimate the rockburst intensity grade of samples to be tested. This model is applied to the rockburst prediction of Qamchiq tunnel project, and the prediction results are in good agreement with the actual conditions of the subsequent construction, thus verifying the feasibility and effectiveness of the model in the rockburst prediction.

引用

页数：8

共 50 条

[31] The contrastive study of prediction of women's heptathlon performance based on grey theory and BP neural network prediction model
[J]. Hou, Zhongren, 1600, Trade Science Inc, 126,Prasheel Park,Sanjay Raj Farm House,Nr. Saurashtra Unive, Rajkot, Gujarat, 360 005, India (10):
[32] Prediction method of rockburst intensity grade based on SOFM neural network model
Yang, Xiaobin
Pei, Yanyu
Cheng, Hongming
Hou, Xin
Lv, Jiaqi
[J]. Yanshilixue Yu Gongcheng Xuebao/Chinese Journal of Rock Mechanics and Engineering, 2021, 40 : 2708 - 2715
[33] Failure prediction based on combined model of grey neural network
基于灰色神经网络组合模型的故障预测
[J]. Su, Chun (suchun@seu.edu.cn), 1600, Chinese Institute of Electronics (42): : 238 - 244
[34] The Coal Demand Prediction Based on the Grey Neural Network Model
Wu, Wanjing
Wang, Xifu
[J]. LISS 2014, 2015, : 1337 - 1343
[35] Prediction of Water Consumption Using NARX Neural Network Based on Grey Relational Analysis
Zhang, Wanjuan
Bai, Yun
[J]. 2018 INTERNATIONAL CONFERENCE ON SENSING, DIAGNOSTICS, PROGNOSTICS, AND CONTROL (SDPC), 2018, : 471 - 475
[36] Prediction and Evaluation of Rockburst Based on Depth Neural Network
Zhang, Jin
Wang, Mengxue
Xi, Chuanhao
[J]. ADVANCES IN CIVIL ENGINEERING, 2021, 2021
[37] Research on forecasting model of artificial neural network based on grey relational analysis
Su Bo
Liu Lu
Yang Fang-ting
[J]. PROCEEDINGS OF 2006 CHINESE CONTROL AND DECISION CONFERENCE, 2006, : 121 - 125
[38] Research on tax prediction model based on BP neural network
Zhang, SQ
Wei, YY
[J]. Proceedings of the 2005 International Conference on Management Science and Engineering, 2005, : 448 - 452
[39] The performance prediction model of NMOSFET based on BP neural network
Fu, Liang
Wang, Feng
[J]. THIRD INTERNATIONAL CONFERENCE ON SENSORS AND INFORMATION TECHNOLOGY, ICSI 2023, 2023, 12699
[40] Research on tax prediction model based on BP neural network
Zhang, Shaoqiu
Hu, Yueming
[J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2006, 13 : 330 - 333

← 1 2 3 4 5 →