Based on the decline in exploitation of coal resources, steep coal seam mining and mining face tensions continue to explore the feasibility analysis of steeply inclined faces in the gob. One of the key factors in util...Based on the decline in exploitation of coal resources, steep coal seam mining and mining face tensions continue to explore the feasibility analysis of steeply inclined faces in the gob. One of the key factors in utilizing the technology of gob-side entry retaining in steep coal seams is to safely and effectively prevent caving rock blocks from rushing into the gob-side entry by sliding downwards along levels. Using theoretical analysis and field methods, we numerically simulated the mining process on a fully-mechanized face in a steep coal seam. The stress and deformation process of roof strata has been analyzed, and the difficulty of utilizing the technology is considered and combined with practice in a steep working face in Lvshuidong mine. The feasibility of utilizing the technology of gob-side entry retaining in a steep coal seam has been recognised. We propose that roadways along the left lane offshoot body use a speciallymade reinforced steel dense net to build a dense rock face at the lower head. The results show that the lane offshoot branch creates effective roof control, safe conditions for roadway construction workers, and practical application of steeply inclined gob.展开更多
In underground mining by sublevel caving method, the deformation and damage of the surface induced by subsidence are the major challenging issues. The dynamic and soft backflling body increases the safety risks in the...In underground mining by sublevel caving method, the deformation and damage of the surface induced by subsidence are the major challenging issues. The dynamic and soft backflling body increases the safety risks in the subsiding area. In this paper, taking Zhangfushan iron mine as an example, the ore body and the general layout are focused on the safety of backflling of mined-out area. Then, we use the ANSYS software to construct a three-dimensional(3D) model for the mining area in the Zhangfushan iron mine. According to the simulation results of the initial mining stages, the ore body is stoped step by step as suggested in the design. The stability of the backflling is back analyzed based on the monitored displacements, considering the stress distribution to optimize the stoping sequence. The simulations show that a reasonable stoping sequence can minimize the concentration of high compressive stress and ensure the safety of stoping of the ore body.展开更多
Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results conta...Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.展开更多
The purpose of this research was to develop a new approach in determination of overhaul and maintenance cost of loading equipment in surface mining. Two statistical models including univariate exponential regression (...The purpose of this research was to develop a new approach in determination of overhaul and maintenance cost of loading equipment in surface mining. Two statistical models including univariate exponential regression (UER) and multivariate linear regression (MLR) were used in this study. Loading equipment parameters such as bucket capacity, machine weight, engine power, boom length, digging depth, and dumping height were considered as variables. The results obtained by models and mean absolute error rate indicate that these models can be applied as the useful tool in determination of overhaul and maintenance cost of loading equipment. The results of this study can be used by the decision-makers for the specific surface mining operations.展开更多
Based on the conclusions of domestic and foreign research, we have analyzed the collapse-fall characteristics of overlying strata and the mechanism of aquifer-protective mining in shallow coal seam working faces at th...Based on the conclusions of domestic and foreign research, we have analyzed the collapse-fall characteristics of overlying strata and the mechanism of aquifer-protective mining in shallow coal seam working faces at the Shendong Mine. We have selected the height of the water-conducting fracture zone in overlying strata as a composite index and established the applicable conditions of aquifer-protective mining in shallow coal seams with a multi-factor synthetic-index classification method. From our calculations and analyses of variance, we used factors such as the overlying strata strength, mining disturbing factors and rock integrity as related factors of the composite index. We have classified the applicable conditions of aquifer-protective mining in shallow coal seams into seven types by comparing the result of the height of water-conducting fractured zones of long-wall and short-wall working faces with the thickness of the bedrock, the thickness of the weathered zone and the size of safety coal-rock pillars. As a result, we propose the preliminary classification system of aquifer-protective mining in shallow coal seams. It can provide a theoretical guidance for safe applications of aquifer-protective mining technology in shallow coal seams under similar conditions.展开更多
Data mining has been proven as a reliable technique to analyze road accidents and provide productive results. Most of the road accident data analysis use data mining techniques, focusing on identifying factors that af...Data mining has been proven as a reliable technique to analyze road accidents and provide productive results. Most of the road accident data analysis use data mining techniques, focusing on identifying factors that affect the severity of an accident. However, any damage resulting from road accidents is always unacceptable in terms of health, property damage and other economic factors. Sometimes, it is found that road accident occurrences are more frequent at certain specific locations. The analysis of these locations can help in identifying certain road accident features that make a road accident to occur frequently in these locations. Association rule mining is one of the popular data mining techniques that identify the correlation in various attributes of road accident. In this paper, we first applied k-means algorithm to group the accident locations into three categories, high-frequency, moderate-frequency and low-frequency accident locations. k-means algorithm takes accident frequency count as a parameter to cluster the locations. Then we used association rule mining to characterize these locations. The rules revealed different factors associated with road accidents at different locations with varying accident frequencies. Theassociation rules for high-frequency accident location disclosed that intersections on highways are more dangerous for every type of accidents. High-frequency accident locations mostly involved two-wheeler accidents at hilly regions. In moderate-frequency accident locations, colonies near local roads and intersection on highway roads are found dangerous for pedestrian hit accidents. Low-frequency accident locations are scattered throughout the district and the most of the accidents at these locations were not critical. Although the data set was limited to some selected attributes, our approach extracted some useful hidden information from the data which can be utilized to take some preventive efforts in these locations.展开更多
Identifying composite crosscutting concerns（CCs） is a research task and challenge of aspect mining.In this paper,we propose a scatter-based graph clustering approach to identify composite CCs.Inspired by the state-o...Identifying composite crosscutting concerns（CCs） is a research task and challenge of aspect mining.In this paper,we propose a scatter-based graph clustering approach to identify composite CCs.Inspired by the state-of-the-art link analysis tech-niques,we propose a two-state model to approximate how CCs tangle with core modules.According to this model,we obtain scatter and centralization scores for each program element.Espe-cially,the scatter scores are adopted to select CC seeds.Further-more,to identify composite CCs,we adopt a novel similarity measurement and develop an undirected graph clustering to group these seeds.Finally,we compare it with the previous work and illustrate its effectiveness in identifying composite CCs.展开更多
Engineering and research teams often develop new products and technologies by referring to inventions described in patent databases. Efficient patent analysis builds R＆D knowledge, reduces new product development tim...Engineering and research teams often develop new products and technologies by referring to inventions described in patent databases. Efficient patent analysis builds R＆D knowledge, reduces new product development time, increases market success, and reduces potential patent infringement. Thus, it is beneficial to automatically and systematically extract information from patent documents in order to improve knowledge sharing and collaboration among R＆D team members. In this research, patents are summarized using a combined ontology based and TF-IDF concept clustering approach. The ontology captures the general knowledge and core meaning of patents in a given domain. Then, the proposed methodology extracts, clusters, and integrates the content of a patent to derive a summary and a cluster tree diagram of key terms. Patents from the International Patent Classification （IPC） codes B25C, B25D, B25F （categories for power hand tools） and B24B, C09G and H011 （categories for chemical mechanical polishing） are used as case studies to evaluate the compression ratio, retention ratio, and classification accuracy of the summarization results. The evaluation uses statistics to represent the summary generation and its compression ratio, the ontology based keyword extraction retention ratio, and the summary classification accuracy. The results show that the ontology based approach yields about the same compression ratio as previous non-ontology based research but yields on average an 11% improvement for the retention ratio and a 14% improvement for classification accuracy.展开更多
文摘Based on the decline in exploitation of coal resources, steep coal seam mining and mining face tensions continue to explore the feasibility analysis of steeply inclined faces in the gob. One of the key factors in utilizing the technology of gob-side entry retaining in steep coal seams is to safely and effectively prevent caving rock blocks from rushing into the gob-side entry by sliding downwards along levels. Using theoretical analysis and field methods, we numerically simulated the mining process on a fully-mechanized face in a steep coal seam. The stress and deformation process of roof strata has been analyzed, and the difficulty of utilizing the technology is considered and combined with practice in a steep working face in Lvshuidong mine. The feasibility of utilizing the technology of gob-side entry retaining in a steep coal seam has been recognised. We propose that roadways along the left lane offshoot body use a speciallymade reinforced steel dense net to build a dense rock face at the lower head. The results show that the lane offshoot branch creates effective roof control, safe conditions for roadway construction workers, and practical application of steeply inclined gob.
文摘In underground mining by sublevel caving method, the deformation and damage of the surface induced by subsidence are the major challenging issues. The dynamic and soft backflling body increases the safety risks in the subsiding area. In this paper, taking Zhangfushan iron mine as an example, the ore body and the general layout are focused on the safety of backflling of mined-out area. Then, we use the ANSYS software to construct a three-dimensional(3D) model for the mining area in the Zhangfushan iron mine. According to the simulation results of the initial mining stages, the ore body is stoped step by step as suggested in the design. The stability of the backflling is back analyzed based on the monitored displacements, considering the stress distribution to optimize the stoping sequence. The simulations show that a reasonable stoping sequence can minimize the concentration of high compressive stress and ensure the safety of stoping of the ore body.
基金Under the auspices of Special Fund of Ministry of Land and Resources of China in Public Interest(No.201511001)
文摘Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.
文摘The purpose of this research was to develop a new approach in determination of overhaul and maintenance cost of loading equipment in surface mining. Two statistical models including univariate exponential regression (UER) and multivariate linear regression (MLR) were used in this study. Loading equipment parameters such as bucket capacity, machine weight, engine power, boom length, digging depth, and dumping height were considered as variables. The results obtained by models and mean absolute error rate indicate that these models can be applied as the useful tool in determination of overhaul and maintenance cost of loading equipment. The results of this study can be used by the decision-makers for the specific surface mining operations.
基金Financial support for this work, provided by the research fund of the North China Institute of Science and Technology (No.A09002)the National Natural Science Foundation of China (No.50834005)the National Basic Research Program of China (No.2007CB209402)
文摘Based on the conclusions of domestic and foreign research, we have analyzed the collapse-fall characteristics of overlying strata and the mechanism of aquifer-protective mining in shallow coal seam working faces at the Shendong Mine. We have selected the height of the water-conducting fracture zone in overlying strata as a composite index and established the applicable conditions of aquifer-protective mining in shallow coal seams with a multi-factor synthetic-index classification method. From our calculations and analyses of variance, we used factors such as the overlying strata strength, mining disturbing factors and rock integrity as related factors of the composite index. We have classified the applicable conditions of aquifer-protective mining in shallow coal seams into seven types by comparing the result of the height of water-conducting fractured zones of long-wall and short-wall working faces with the thickness of the bedrock, the thickness of the weathered zone and the size of safety coal-rock pillars. As a result, we propose the preliminary classification system of aquifer-protective mining in shallow coal seams. It can provide a theoretical guidance for safe applications of aquifer-protective mining technology in shallow coal seams under similar conditions.
文摘Data mining has been proven as a reliable technique to analyze road accidents and provide productive results. Most of the road accident data analysis use data mining techniques, focusing on identifying factors that affect the severity of an accident. However, any damage resulting from road accidents is always unacceptable in terms of health, property damage and other economic factors. Sometimes, it is found that road accident occurrences are more frequent at certain specific locations. The analysis of these locations can help in identifying certain road accident features that make a road accident to occur frequently in these locations. Association rule mining is one of the popular data mining techniques that identify the correlation in various attributes of road accident. In this paper, we first applied k-means algorithm to group the accident locations into three categories, high-frequency, moderate-frequency and low-frequency accident locations. k-means algorithm takes accident frequency count as a parameter to cluster the locations. Then we used association rule mining to characterize these locations. The rules revealed different factors associated with road accidents at different locations with varying accident frequencies. Theassociation rules for high-frequency accident location disclosed that intersections on highways are more dangerous for every type of accidents. High-frequency accident locations mostly involved two-wheeler accidents at hilly regions. In moderate-frequency accident locations, colonies near local roads and intersection on highway roads are found dangerous for pedestrian hit accidents. Low-frequency accident locations are scattered throughout the district and the most of the accidents at these locations were not critical. Although the data set was limited to some selected attributes, our approach extracted some useful hidden information from the data which can be utilized to take some preventive efforts in these locations.
基金Supported by the National Pre-research Project (513150601)
文摘Identifying composite crosscutting concerns（CCs） is a research task and challenge of aspect mining.In this paper,we propose a scatter-based graph clustering approach to identify composite CCs.Inspired by the state-of-the-art link analysis tech-niques,we propose a two-state model to approximate how CCs tangle with core modules.According to this model,we obtain scatter and centralization scores for each program element.Espe-cially,the scatter scores are adopted to select CC seeds.Further-more,to identify composite CCs,we adopt a novel similarity measurement and develop an undirected graph clustering to group these seeds.Finally,we compare it with the previous work and illustrate its effectiveness in identifying composite CCs.
基金supported by National Science Council research grants
文摘Engineering and research teams often develop new products and technologies by referring to inventions described in patent databases. Efficient patent analysis builds R＆D knowledge, reduces new product development time, increases market success, and reduces potential patent infringement. Thus, it is beneficial to automatically and systematically extract information from patent documents in order to improve knowledge sharing and collaboration among R＆D team members. In this research, patents are summarized using a combined ontology based and TF-IDF concept clustering approach. The ontology captures the general knowledge and core meaning of patents in a given domain. Then, the proposed methodology extracts, clusters, and integrates the content of a patent to derive a summary and a cluster tree diagram of key terms. Patents from the International Patent Classification （IPC） codes B25C, B25D, B25F （categories for power hand tools） and B24B, C09G and H011 （categories for chemical mechanical polishing） are used as case studies to evaluate the compression ratio, retention ratio, and classification accuracy of the summarization results. The evaluation uses statistics to represent the summary generation and its compression ratio, the ontology based keyword extraction retention ratio, and the summary classification accuracy. The results show that the ontology based approach yields about the same compression ratio as previous non-ontology based research but yields on average an 11% improvement for the retention ratio and a 14% improvement for classification accuracy.
