Discrimination of mine inrush water source based on PCA -CRHJ model
Aiming at problems of traditional discriminant model of mine inrush water source, such as poor nonlinear ability, poor model stability and low discrimination accuracy, PCA -CRHJ discriminant model of mine inrush water source is constructed based on principal component analysis (PCA) method and cycle...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Department of Industry and Mine Automation
2020-11-01
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| Series: | Gong-kuang zidonghua |
| Subjects: | |
| Online Access: | http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671 -251x.2020040089 |
| _version_ | 1819124132845977600 |
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| author | QIU Xingguo WANG Ruizhi ZHANG Weiguo ZHANG Zhaozhao ZHANG Jing |
| author_facet | QIU Xingguo WANG Ruizhi ZHANG Weiguo ZHANG Zhaozhao ZHANG Jing |
| author_sort | QIU Xingguo |
| collection | DOAJ |
| description | Aiming at problems of traditional discriminant model of mine inrush water source, such as poor nonlinear ability, poor model stability and low discrimination accuracy, PCA -CRHJ discriminant model of mine inrush water source is constructed based on principal component analysis (PCA) method and cycle reservoir with hierarchical jumps (CRHJ). PCA is introduced to reduce dimension of multivariate time water inrush sequence and extract key features, the water inrush data is reconstructed to obtain principal component water inrush series, and the CRHJ model is trained by reconstructed sequence. The model completed by the training is applied to water inrush source discrimination in Zhangji Coal Mine and Xinzhuangzi Coal Mine for validity verfication. The results show that: ① By comparing with CRHJ、cycle reservoir with regular jumps (CRJ) and echo state network (ESN) models, the results show that PCA -CRHJ model has the best actual discriminant effect and the accuracy can reach 100%. ② The PCA -CRHJ model has five main types of parameters, namely, reserve pool size, input connection weight, one -way connection weight, hierarchical two -way jump weight and jump step size, the sensitivity analysis of these five types of parameters shows that the input weight parameters have the greatest impact on the model discrimination accuracy. When three kinds of weight parameters obtain the optimal value and remain unchanged, the reserve pool size has the greatest impact on the model error, while the jump step size has less effect. |
| first_indexed | 2024-12-22T07:19:23Z |
| format | Article |
| id | doaj.art-9e04f30ab7034515a611cce03ce5bdb5 |
| institution | Directory Open Access Journal |
| issn | 1671-251X |
| language | zho |
| last_indexed | 2024-12-22T07:19:23Z |
| publishDate | 2020-11-01 |
| publisher | Editorial Department of Industry and Mine Automation |
| record_format | Article |
| series | Gong-kuang zidonghua |
| spelling | doaj.art-9e04f30ab7034515a611cce03ce5bdb52022-12-21T18:34:20ZzhoEditorial Department of Industry and Mine AutomationGong-kuang zidonghua1671-251X2020-11-014611657110.13272/j.issn.1671 -251x.2020040089Discrimination of mine inrush water source based on PCA -CRHJ modelQIU XingguoWANG RuizhiZHANG WeiguoZHANG ZhaozhaoZHANG JingAiming at problems of traditional discriminant model of mine inrush water source, such as poor nonlinear ability, poor model stability and low discrimination accuracy, PCA -CRHJ discriminant model of mine inrush water source is constructed based on principal component analysis (PCA) method and cycle reservoir with hierarchical jumps (CRHJ). PCA is introduced to reduce dimension of multivariate time water inrush sequence and extract key features, the water inrush data is reconstructed to obtain principal component water inrush series, and the CRHJ model is trained by reconstructed sequence. The model completed by the training is applied to water inrush source discrimination in Zhangji Coal Mine and Xinzhuangzi Coal Mine for validity verfication. The results show that: ① By comparing with CRHJ、cycle reservoir with regular jumps (CRJ) and echo state network (ESN) models, the results show that PCA -CRHJ model has the best actual discriminant effect and the accuracy can reach 100%. ② The PCA -CRHJ model has five main types of parameters, namely, reserve pool size, input connection weight, one -way connection weight, hierarchical two -way jump weight and jump step size, the sensitivity analysis of these five types of parameters shows that the input weight parameters have the greatest impact on the model discrimination accuracy. When three kinds of weight parameters obtain the optimal value and remain unchanged, the reserve pool size has the greatest impact on the model error, while the jump step size has less effect.http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671 -251x.2020040089mine water inrushdiscrimination of water inrush sourcecycle reservoir with hierarchical jumpsprincipal component analysismultivariate time series |
| spellingShingle | QIU Xingguo WANG Ruizhi ZHANG Weiguo ZHANG Zhaozhao ZHANG Jing Discrimination of mine inrush water source based on PCA -CRHJ model Gong-kuang zidonghua mine water inrush discrimination of water inrush source cycle reservoir with hierarchical jumps principal component analysis multivariate time series |
| title | Discrimination of mine inrush water source based on PCA -CRHJ model |
| title_full | Discrimination of mine inrush water source based on PCA -CRHJ model |
| title_fullStr | Discrimination of mine inrush water source based on PCA -CRHJ model |
| title_full_unstemmed | Discrimination of mine inrush water source based on PCA -CRHJ model |
| title_short | Discrimination of mine inrush water source based on PCA -CRHJ model |
| title_sort | discrimination of mine inrush water source based on pca crhj model |
| topic | mine water inrush discrimination of water inrush source cycle reservoir with hierarchical jumps principal component analysis multivariate time series |
| url | http://www.gkzdh.cn/article/doi/10.13272/j.issn.1671 -251x.2020040089 |
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