基于主成分分析和PSO-ELM算法的排土场稳定性预测模型

doi:10.11872/j.issn.1005-2518.2021.05.168

Abstract

Abstract:

Aiming at the stability analysis of dump slope，a PCA-PSO-ELM dump slope stability prediction model is proposed in this paper，which uses principal component analysis method to reduce data redundancy and particle swarm optimization algorithm to optimize the weight threshold of extreme learning machine. Eight prediction indexes of dump stability were determined in this model，including soil cohesion，internal friction angle，dump slope angle，foundation bearing capacity，seismic intensity，rainfall and snowfall conditions，dumping technology and random mining and digging conditions.According to 100 groups of corresponding dump data，training time，RMSE value and determination coefficient R² were used to evaluate and compare the validity of prediction results of PCA-PSO-ELM model，BP neural network model，ELM model and PSO-ELM model.The research results show that as the input variable to train and test the PSO-ELM network model，the dump stability sample data processed by PCA dimensionality reduction，made predicted value very close to the real value.The prediction accuracy and efficiency are not only higher than the ELM algorithm，but also far better than the traditional BP neural network algorithm.Compared with the PSO-ELM model without PCA treatment，the PSO-ELM model optimized by PCA method can significantly shorten the calculation time on the basis of little difference in efficiency，which proves that the method has certain practical value.

Key words: dump sites’ safety, stability evaluation, extreme learning machine, principal component analysis, artificial neutral network, particle swarm algorithm

CLC Number:

Feng GAO,Xiaodong WU,Keping ZHOU. Prediction Model of Soil Dump Stability Based on Principal Component Analysis and PSO-ELM Algorithm[J].Gold Science and Technology, 2021, 29(5): 658-668.

Figures/Tables 10

Fig.1

Fig.2

Fig.3

Table 1

Table 2

Loading matrix of principal component factor"

影响因素	主成分
影响因素	$X 1$	$X 2$
黏聚力	0.155	0.202
内摩擦角	0.159	0.127
边坡角度	0.126	0.575
地基承载力	0.152	-0.358
地震烈度	0.151	0.390
降雨和降雪条件	0.151	-0.373
排土工艺	0.157	-0.113
乱采乱挖	0.147	-0.367

Table 2

Fig.4

Fig.5

Fig.6

Table 3

Fig.7

References 0

	Bishop A W，1955.The use of the slip circle in the stability analysis of slopes［J］.Geotechnique，5（1）：7-17.
	Cao Lanzhu，Wang Zhen，Wang Dong，al et，2017.Numerical simulation of stability during dumping of soft soil dump site［J］.Journal of Disaster Prevention and Mitigation Engineering，37（5）：776-781.
	Castano A，Fernandez-Navarre F，Hervas-Martinez C，2013.PCA-ELM：A robust and pruned extreme learning machine approach based on principal component analysis［J］.Neural Processing Letters，37（3）：377-392.
	Chen Peng，Chen Pengfei，2010.Slope stability analysis of open-pit mine dump［J］.Journal of Liaoning Technical University（Natural Science Edition），29（6）：1028-1031.
	Cho S E，2009.Probabilistic stability analyses of slopes using the ANN-based response surface［J］.Computers & Geotechnics，36（5）：787-797.
	Gordan B，Armaghani D J，Hajihassani M，al et，2016.Prediction of seismic slope stability through combination of particle swarm optimization and neural network［J］.Engineering with Computers，32（1）：85-97.
	He Tingting，Shang Yuequan，Qing Lü，al et，2013.Support vector machine method for slope reliability analysis［J］.Rock and Soil Mechanics，34（11）：3269-3276.
	Hong W P，Song Y S，Lim S G，2005.Stability evaluation of the cut slope using artificial neural network model［J］.Journal of the Korean Society of Civil Engineers，25（4C）：15-21.
	Janbu N，1975.Slope stability computations：In embankment-dam engineering.Textbook.Eds.R.C.Hirschfeld and S.J.Poulos.John Wiley and Sons Inc.Pub.NY，1973，40P［J］.International Journal of Rock Mechanics and Mining sciences & Geomechanics Abstracts，12（4）：67.
	Jolliffe I T，Cadima J，2016.Principal component analysis：A review and recent developments［J］.Philosophical Transactions of the Royal Society Mathematical Physical & Engineering Sciences，374（2065）：20150202.
	Kang F，Li J J，2016.Artificial bee colony algorithm optimized support vector regression for system reliability analysis of slopes［J］.Journal of Computing in Civil Engineering，30（3）：04015040.
	Li Wei，2014.Slope stability analysis and treatment technology of open-pit coal mine dump site［J］.Coal Science and Technology，42（10）：37-40，5.
	Liu D J，Han L S，Hu J，al et，2015.DCPSO-BP model of slope stability research［C］ //International Conference on Mechanics，Building Material and Civil Engineering.Pennsylvania：DEStech Publication. Inc.
	Liu Z B，Shao J F，Xu W Y，al et，2014.An extreme learning machine approach for slope stability evaluation and prediction［J］.Natural Hazards，73（2）：787-804.
	Lu H J，Du B J，Liu J Y，al et，2017.A kernel extreme learning machine algorithm based on improved particle swam optimization［J］.Memetic Computing，9（2）：121-128.
	Luan Tingting，2015.Research and Application of Early Warning Method of Open-pit Mine Dump Landslide［D］.Beijing：University of Science and Technology Beijing.
	Morgenstern N R，Price V E，1967.A numerical method for solving the equations of stability of general slip surfaces［J］.The Computer Journal，9（4）：388-393.
	Shao Liangshan，Ma Han，Wen Tingxin，2015.Prediction of slope stability based on RF-ELM model［J］.China Safety Science and Technology，11（3）：93-98.
	Shi L，Yang Y L，Lü J H，2015.PCA-PSO-BP neural network application in IDS［C］// International Power，Electronics & Materials Engineering Conference.Paris：Atlantis Press，145-150.DOI：https：//doi.org/10.2991/ipemec-15.2015.29. doi: https：//doi.org/10.2991/ipemec-15.2015.29
	Spencer E，1967.A method of analysis of the stability of embankments assuming parallel inter-slice forces［J］.Geotechnique，17（1）：11-26.
	Su Guoshao，Zhao Wei，Peng Lifeng，al et，2014.Gaussian dynamic response surface method for slope failure probability estimation［J］.Rock and Soil Mechanics，35（12）：3592-3601.
	Su Yonghua，Luo Zhengdong，Zhang Panfeng，al et，2013.Active search method of slope stability reliability based on Kriging［J］.Chinese Journal of Geotechnical Engineering，35（10）：1863-1869.
	Su Yonghua，Yang Hongbo，2012.Slope stability reliability algorithm based on proxy model［J］.Chinese Journal of Applied Mechanics，29（6）：705-710，776.
	Tan Xiaohui，Hu Xiaojun，Chu Chengfu，al et，2011.Fuzzy response surface method and its application in the reliability analysis of slope stability［J］.Journal of University of Science and Technology of China，41（3）：233-237，243.
	Wang Biaolong，Meng Fanli，Zeng Chao，al et，2019.Landslide reliability evaluation method of PSO-BP neural network based on natural selection strategy［J］.China & Foreign Highway，39（3）：1-9.
	Wang Yu，Wang Chunlei，Wang Can，al et，2011.Research and application of vector projection response surface for slope reliability evaluation［J］.Chinese Journal of Geotechnical Engineering，33（9）：1434-1439.
	Wen Tingxin，Zhu Jing，2018.Slope stability prediction based on SAPSO-ELM［J］.Journal of Safety and Environment，18（6）：2146-2150.
	Xue X H，2016.Prediction of slope stability based on hybrid PSO and LSSVM［J］.Journal of Computing in Civil Engineering，31（1）：04016041.
	Yi P，Wei K T，Kong X，al et，2015.Cumulative PSO-Kriging model for slope reliability analysis［J］.Probabilistic Engineering Mechanics，39：39-45.
	Zhai Wenlong，Zhou Hanmin，2015.Application of simplified bishop method and co-thrust method to stability calculation of high step dumping site［J］.Modern Mining，31（8）：168-170.
	Zhang Lijun，Mu Chuanwei，He Fangwei，2015.Stability analysis of dump site slope based on strength reduction finite element method［J］.Modern Mining，31（8）：159-160.
	Zhang Qiwei，Ma Shuzhi，Jia Hongbiao，2015.Comparative analysis of FLAC 3D method and rigid body limit equilibrium method for stability evaluation of mine dumps［J］.Mining Research and Development，35（6）：45-48.
	曹兰柱，王珍，王东，等，2017.软弱基底排土场堆载过程中稳定性数值模拟［J］.防灾减灾工程学报，37（5）：776-781.
	陈鹏，陈鹏飞，2010.露天矿排土场边坡稳定性分析［J］.辽宁工程技术大学学报（自然科学版），29（6）：1028-1031.
	翟文龙，周汉民，2015.简化Bishop法和余推力法在高台阶排土场稳定性计算中的应用［J］.现代矿业，31（8）：168-170.
	何婷婷，尚岳全，吕庆，等，2013.边坡可靠度分析的支持向量机法［J］.岩土力学，34（11）：3269-3276.
	李伟，2014.露天煤矿排土场边坡稳定性分析与治理技术［J］.煤炭科学技术，42（10）：37-40，5.
	栾婷婷，2015.露天矿排土场滑坡预警方法的研究及应用［D］.北京：北京科技大学.
	邵良杉，马寒，温廷新，2015.基于RF-ELM模型的边坡稳定性预测研究［J］.中国安全生产科学技术，11（3）：93-98.
	苏国韶，赵伟，彭立锋，等，2014.边坡失效概率估计的高斯过程动态响应面法［J］.岩土力学，35（12）：3592-3601.
	苏永华，罗正东，张盼凤，等，2013.基于Kriging的边坡稳定可靠度主动搜索法［J］.岩土工程学报，35（10）：1863-1869.
	苏永华，杨红波，2012.基于代理模型的边坡稳定可靠度算法［J］.应用力学学报，29（6）：705-710，776.
	谭晓慧，胡晓军，储诚富，等，2011.模糊响应面法及其在边坡稳定可靠度分析中的应用［J］.中国科学技术大学学报，41（3）：233-237，243.
	王彪龙，孟凡利，曾超，等，2019.基于自然选择策略的PSO-BP神经网络的滑坡可靠性评价方法［J］.中外公路，39（3）：1-9.
	王宇，王春磊，汪灿，等，2011.边坡可靠性评价的向量投影响应面研究及应用［J］.岩土工程学报，33（9）：1434-1439.
	温廷新，朱静，2018.基于SAPSO-ELM的边坡稳定性预测［J］.安全与环境学报，18（6）：2146-2150.
	张利军，母传伟，何方维，2015.基于强度折减有限元法的排土场边坡稳定性分析［J］.现代矿业，31（8）：159-160.
	张其唯，马淑芝，贾洪彪，2015.矿山排土场稳定性评价的FLAC 3D方法和刚体极限平衡法对比分析［J］.矿业研究与开发，35（6）：45-48.

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成分	初始特征值			提取平方和载入
成分	合计	方差百分比	累计贡献率/％	合计	方差百分比	累计贡献率/％
1	5.552	69.406	69.406	5.552	69.406	69.406
2	1.049	13.110	82.516	1.049	13.110	82.516
3	0.414	5.179	87.695
4	0.320	3.998	91.693
5	0.220	2.751	94.444
6	0.172	2.151	96.595
7	0.150	1.875	98.470
8	0.122	1.530	100.000

样本编号	真实值	预测值
样本编号	真实值	BPNN	ELM	PSO-ELM	PCA-PSO-ELM
91	5（V）	5.5443	4.6699	5.0936	5.0850
92	3（III）	3.4779	3.1714	3.0214	3.0184
93	1（I）	1.8100	1.1842	0.9521	0.9028
94	4（IV）	4.9611	3.8648	3.8699	3.8195
95	1（I）	1.1654	1.4305	1.0935	1.0040
96	4（IV）	3.6122	3.9996	4.0544	3.9933
97	5（V）	5.6236	4.9438	4.9937	5.0779
98	1（I）	0.8102	0.7896	0.9994	0.9721
99	3（III）	3.9471	3.3157	3.0690	3.0034
100	5（V）	4.9532	4.7209	4.8955	4.9943
RMSE 值时间/s		0.6005	0.2451	0.0747	0.0752
RMSE 值时间/s		0.3533	0.1765	26.9467	12.9354

Prediction Model of Soil Dump Stability Based on Principal Component Analysis and PSO-ELM Algorithm

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