scholarly journals Predicting the Water-Conducting Fracture Zone (WCFZ) Height Using an MPGA-SVR Approach

2020 ◽  
Vol 12 (5) ◽  
pp. 1809
Author(s):  
Changfang Guo ◽  
Zhen Yang ◽  
Shen Li ◽  
Jinfu Lou
Keyword(s):  
Genetic Algorithm ◽  
Fracture Zone ◽  
Mine Water ◽  
Mean Squared Error ◽  
Water Inrush ◽  
Correlation Coefficients ◽  
Mining Area ◽  
Support Vector ◽  
Accuracy And Stability ◽  
Overburden Strata

Mine water that inrushes from coal-roof strata has always posed a substantial threat to mining activities every year. Therefore, an accurate prediction of the water-conducting fracture zone (WCFZ) height in the mining overburden strata is of great significance for the prevention and control of mine water accidents. The support vector regression (SVR) is proposed to predict the height of the WCFZ based on the mining depth, hard rock proportional coefficient, mining thickness and length of the working face. Simultaneously, the multi-population genetic algorithm (MPGA) is employed to search for the optimal SVR parameters. The MPGA-SVR model is trained and tested with a total of 69 collected data samples, and it is also applied to a field test. The accuracy and stability of the model were measured by the mean squared error and correlation coefficients. The obtained results show that the MPGA-SVR model achieves a higher accuracy and stability than the traditional empirical formula and genetic algorithm (GA)-SVR model. In terms of the process for optimizing the SVR parameters, the MPGA can find the optimal parameters more quickly and accurately, and it can effectively overcome the problem of premature and slow convergence of the genetic algorithm (GA). The proposed model improves the prediction accuracy and stability, which will help to avoid accidents caused by the inrush of water inrush in mining overburden strata and protect the ecological environment of the mining area.

scholarly journals Hydrogeochemical Evolution and Control Mechanism of Underground Multiaquifer System in Coal Mine Area

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Qiding Ju ◽  
Yu Liu ◽  
Youbiao Hu ◽  
Yuquan Wang ◽  
Qimeng Liu ◽  
...  
Keyword(s):  
Cation Exchange ◽  
Mine Water ◽  
Control Mechanism ◽  
Water Inrush ◽  
Pyrite Oxidation ◽  
Mining Area ◽  
Carbonate Dissolution ◽  
Mining Activities ◽  
Hydrogeochemical Evolution ◽  
And Control

Mining activities interfere into the natural groundwater chemical environment, which may lead to hydrogeochemical changes of aquifers and mine water inrush disasters. The study of hydrogeochemical evolution processes of underground aquifers is helpful to the prevention and control of mine water inrush. The results show that the study area is mainly impacted by four hydrogeochemical processes: dissolution, cation exchange, desulfurization and reduction, and pyrite oxidation. The Cenozoic aquifers are dominated by carbonate dissolution and desulfurization. The Permian aquifers are impacted mainly by cation exchange and sulfate dissolution, followed by pyrite oxidation. The Carboniferous aquifers are mainly impacted by dissolving sulfate, followed by pyrite oxidation and cation exchange. The hydrogeochemical evolution of the aquifers was controlled by mining activities and tectonic changes, and a certain regularity in space. For the Cenozoic aquifers, sulfate dissolution and cation exchange increase from west to east, and desulfurization weakens. For the Permian aquifers, cation exchange and sulfate dissolution are stronger near synclines and faults, pyrite oxidation is enhanced, and desulfurization decreases from the middle to the east of the mining area. For the Carboniferous aquifers, there is a higher dissolution of rock salt, pyrite oxidation, and cation exchange from west to east, and the desulfurization effect weakens.

Water-Inrush Mechanism while Fault Zone Secondary Activated in Mining

2012 ◽  
Vol 524-527 ◽  
pp. 799-802
Author(s):  
Shi Guo Sun ◽  
Shao Jie Feng ◽  
Jia Hao Lei
Keyword(s):  
Fault Zone ◽  
Fracture Zone ◽  
Rock Fracture ◽  
Water Inrush ◽  
Mining Area ◽  
Water Conductivity ◽  
Sublevel Caving ◽  
Discontinuous Deformation ◽  
Height Increase ◽  
The Impact

As many different size faults in the fully-mechanized sublevel caving mining area overlying rock, undermine the continuity of rock deformation, and the occurrence of different conditions, the impact properties vary widely. This paper studies the impact of faults on the water inrush with specific examples of project, obtained the discontinuous deformation on both sides of fault zone induce the fault zone secondary activate and result in it’s water transmitting ability dramatic increase; with the mining geometry increases, the water flowing-fracture zone height increase and lead to the water conductivity channel of faults connect with rock fracture zone, so as to constitute water inrush channel and likely to cause water inrush accident, so to explore the influence of fault for underground work safety has important theoretical significance and application value.

Discrimination of Mine Water Bursting Source Based on Fuzzy System

2012 ◽  
Vol 182-183 ◽  
pp. 644-648
Author(s):  
Wei Feng Yang ◽  
Ding Yi Shen ◽  
Yu Bing Ji ◽  
Yi Wang
Keyword(s):  
Coal Mine ◽  
Mine Water ◽  
Fuzzy System ◽  
Comprehensive Evaluation ◽  
Water Inrush ◽  
Fuzzy Comprehensive Evaluation ◽  
Mining Area ◽  
Shanxi Province ◽  
Estimation Model ◽  
Water Bursting

Through applying the background values of aquifer derived from fuzzy clustering analysis, a fuzzy comprehensive estimation model was developed for quick recognition of mine water inrush. Based on the hydrological-chemical analysis data of water samples which water bursting sources were known in Liliu mining area, Shanxi province, this paper presented that the hydrological-chemical characters of different aquifer was different, and established a sort of fuzzy comprehensive evaluation models of discriminating coal mine water bursting sources in Liliu mining area. Applied to a production mine, the correct rate of water bursting source judged results by various methods was more than 70%. With the dispersion method and the method extracted from stepwise discrimination analysis to determine the membership degree and Model 3 the type determined by various factors, the correct rate of water bursting source with comprehensive evaluation of combination of two methods was higher respectively 94.5% and 93.3%. The fuzzy system can efficiently and accurately discriminate the resource of water inrush for an unknown sample, and provide the decision basis for the safety production of the coal mine.

scholarly journals Integration of Genetic Algorithm and Support Vector Machine to Predict Rail Track Degradation

2019 ◽  
Vol 259 ◽  
pp. 02007 ◽  
Author(s):  
Amir Falamarzi ◽  
Sara Moridpour ◽  
Majidreza Nazem ◽  
Reyhaneh Hesami
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Preventive Maintenance ◽  
Mean Squared Error ◽  
Study Data ◽  
Transport Infrastructure ◽  
Coefficient Of Determination ◽  
Ride Quality ◽  
Support Vector ◽  
Svm Model

Gradual deviation in track gauge of tram systems resulted from tram traffic is unavoidable. Tram gauge deviation is considered as an important parameter in poor ride quality and the risk of train derailment. In order to decrease the potential problems associated with excessive gauge deviation, implementation of preventive maintenance activities is inevitable. Preventive maintenance operation is a key factor in development of sustainable rail transport infrastructure. Track degradation prediction modelling is the basic prerequisite for developing efficient preventive maintenance strategies of a tram system. In this study, the data sets of Melbourne tram network is used and straight rail tracks sections are examined. Two model types including plain Support Vector Machine (SVM) and SVM optimised by Genetic Algorithm (GA- SVM) have been applied to the case study data. Two assessment indexes including Mean Squared Error (MSE) and the coefficient of determination (R2) are employed to evaluate the performance of the proposed models. Based on the results, GA-SVM model produces more accurate outcomes than plain SVM model.

scholarly journals Piper-PCA-Fisher Recognition Model of Water Inrush Source: A Case Study of the Jiaozuo Mining Area

Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Pinghua Huang ◽  
Xinyi Wang
Keyword(s):  
Water Sample ◽  
Water Samples ◽  
Mine Water ◽  
Water Inrush ◽  
Water Source ◽  
Mining Area ◽  
Information Quantity ◽  
Recognition Model ◽  
Piper Trilinear Diagram ◽  
Discrimination Rate

Source discrimination of mine water plays an important role in guiding mine water prevention in mine water management. To accurately determine water inrush source from a mine in the Jiaozuo mining area, a Piper trilinear diagram based on hydrochemical experimental data of stratified underground water in the area was utilized to determine typical water samples. Additionally, principal component analysis (PCA) was used for dimensionality reduction of conventional hydrochemical variables, after which mutually independent variables were extracted. The Piper-PCA-Fisher water inrush source recognition model was established by combining the Piper trilinear diagram and Fisher discrimination theory. Screened typical samples were used to conduct back-discriminate verification of the model. Results showed that 28 typical water samples in different aquifers were determined through the Piper trilinear diagram as a water sample set for training. Before PCA was carried out, the first five factors covered 98.92% of the information quantity of the original data and could effectively represent the data information of the original samples. During the one-by-one rediscrimination process of 28 groups of training samples using the Piper-PCA-Fisher water inrush source model, 100% correct discrimination rate was achieved. During the prediction and discrimination process of 13 samples, one water sample was misdiscriminated; hence, the correct prediscrimination rate was 92.3%. Compared with the traditional Fisher water source recognition model, the Piper-PCA-Fisher water source recognition model established in this study had higher accuracy in both rediscrimination and prediscrimination processes. Thus it had a strong ability to discriminate water inrush sources.

scholarly journals Height prediction of water-flowing fracture zone with a genetic-algorithm support-vector-machine method

2020 ◽  
Vol 7 (4) ◽  
pp. 740-751
Author(s):  
Enke Hou ◽  
Qiang Wen ◽  
Zhenni Ye ◽  
Wei Chen ◽  
Jiangbo Wei
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Prediction Model ◽  
Mining Area ◽  
Support Vector ◽  
Burial Depth ◽  
Machine Method ◽  
Working Face ◽  
Face Length ◽  
Coal Seam Thickness

AbstractPrediction of the height of a water-flowing fracture zone (WFFZ) is the foundation for evaluating water bursting conditions on roof coal. By taking the Binchang mining area as the study area and conducting an in-depth study of the influence of coal seam thickness, burial depth, working face length, and roof category on the height of a WFFZ, we proposed that the proportion of hard rock in different roof ranges should be used to characterise the influence of roof category on WFFZ height. Based on data of WFFZ height and its influence index obtained from field observations, a prediction model is established for WFFZ height using a combination of a genetic algorithm and a support-vector machine. The reliability and superiority of the prediction model were verified by a comparative study and an engineering application. The results show that the main factors affecting WFFZ height in the study area are coal seam thickness, burial depth, working face length, and roof category. Compared with multiple-linear-regression and back-propagation neural-network approaches, the height-prediction model of the WFFZ based on a genetic-algorithm support-vector-machine method has higher training and prediction accuracy and is more suitable for WFFZ prediction in the mining area.

Mining Design Optimization Research on the Northern Section of 8 Coal Seam in West No.1 Mining Area in Pansan Mine

2013 ◽  
Vol 634-638 ◽  
pp. 3394-3403
Author(s):  
Hua Wang ◽  
Chang Cai Fang ◽  
Yi Guo Shu ◽  
Li Xin Yang ◽  
De Fu Jiang ◽  
...  
Keyword(s):  
Coal Seam ◽  
Design Optimization ◽  
Mine Water ◽  
Water Inrush ◽  
Mining Area ◽  
Mine Area ◽  
Rock Pillar ◽  
Working Face ◽  
Coal Rock ◽  
Mining Design

Water in Lower Aquifer of Quaternary is one of the mine water inrush sources during working faces being mining in the Northern Section of 8 Coal Seam in West No.1 Mining Area. Water flowing fractured zone, F1 fault, F22-a fault and F48 fault are main water-conducting channels in mining. According to the analysis of geology and hydrographical geology of the mine area, and combined with “Water Prevention Regulation of Coal Mines” and “Regulations of pillar leaving and coal mining under building, water, railway and mail shaft and tunnel”, stope layout was optimized, i.e. the minimum waterproof coal(rock) pillar between working face and Lower Aquifer Quaternary is 70 meter, the waterproof coal(rock) pillar between working face and F1 fault, F22-a fault, F48 fault is 70~95 meter, 70~75 meter, 80~90 meter respectively. Each shallow waterproof coal (rock) pillar of fault is narrow at the top and tends to increasingly widen at the bottom.

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