干旱区生态环境知识资源中心(Arid): Evaluation of mine water quality based on the PCA-PSO-BP model

Arid

DOI	10.2166/wcc.2023.604
	Evaluation of mine water quality based on the PCA-PSO-BP model
	Wang, Jiaqi; Huang, Yanli
通讯作者	Wang, JQ ; Huang, YL
来源期刊	JOURNAL OF WATER AND CLIMATE CHANGE
ISSN	2040-2244
EISSN	2408-9354
出版年	2024
卷号	15 期号:2 页码:593-606
英文摘要	To enhance the mining area's overall use of mine water in the arid area of Western China and mitigate the current water scarcity problem, a realistic and scientific assessment of the water quality in the mining area is required. This paper introduces an intelligent optimization algorithm and neural network for mine water quality evaluation and proposes a principal component analysis (PCA)-particle swarm optimization (PSO)-back propagation (BP) mine water quality evaluation model based on PCA, PSO, and BP neural network. First, the model uses PCA to achieve the dimensionality reduction of mine water evaluation indexes, identifies the primary factors affecting mine water quality, then enhances the optimal weights and thresholds of the BP neural network based on the PSO algorithm, takes the principal components of PCA as the input, and takes the results of mine water quality evaluation as the output of the model, and the PCA-PSO-BP evaluation model with nine input layers, nine hidden layers, and one output layer is created. In addition, using the Ningdong Coalfield Shicaocun Mine as an example, using the BP neural network water quality evaluation method as a comparison, the results demonstrate that the PCA-PSO-BP model has accurate mine water quality evaluation results, and the error of the evaluation results of the constructed PCA-PSO-BP model is between +/- 0.02, the prediction accuracy reached 86.8255%, which is much more accurate than the traditional BP neural network. This exemplifies the PSO method's superiority to the BP neural network improvement. In addition to providing a novel theoretical framework for evaluating and predicting water quality in mining areas, this study opens the door to the potential widespread application of cutting-edge neural networks and optimization algorithms in the field of coal mines.
英文关键词	BP neural network mine water quality evaluation particle swarm optimization (PSO) principal component analysis (PCA) PSO-BP model
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001134718000001
WOS关键词	PARTICLE SWARM ; OPTIMIZATION ; INRUSH ; RISK ; NETWORK ; FUSION ; SYSTEM ; INDEX
WOS类目	Water Resources
WOS研究方向	Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404753
推荐引用方式 GB/T 7714	Wang, Jiaqi,Huang, Yanli. Evaluation of mine water quality based on the PCA-PSO-BP model[J],2024,15(2):593-606.
APA	Wang, Jiaqi,&Huang, Yanli.(2024).Evaluation of mine water quality based on the PCA-PSO-BP model.JOURNAL OF WATER AND CLIMATE CHANGE,15(2),593-606.
MLA	Wang, Jiaqi,et al."Evaluation of mine water quality based on the PCA-PSO-BP model".JOURNAL OF WATER AND CLIMATE CHANGE 15.2(2024):593-606.