基于Web-Log Mining的Web文档聚类

速度和效果是聚类算法面临的两大问题.DBSCAN(density based spatial clustering of applications with noise)是典型的基于密度的一种聚类方法,对于大型数据库的聚类实验显示了它在速度上的优越性.提出了一种基于密度的递归聚类算法(recursive density based clustering algorithm,简称RDBC),此算法可以智能地、动态地修改其密度参数.RDBC是基于DBSCAN的一种改进算法,其运算复杂度和DBSCAN相同.通过在Web文档上的聚类实验,结果表明,RDBC不但保留了DBSCAN高速度的优点,而且聚类效果大大优于DBSCAN.

基于Web-Log Mining的N元预测模型

随着Web上用户访问信息的不断增加,特别是Web服务器可提供大量的日志文件,使得有可能对这些大数据集进行知识挖掘,例如,对用户未来的访问进行预测.提出了一种利用服务器日志文件,运用N元(N-gram)预测模型对用户未来可能进行的Web访问请求进行预测.这种模型会选择性地对用户可预测的请求进行预测,从而大大提高了预测精度.实验证明,在自然语言中普遍适用的N元预测模型同样适用于网页预测.同时,采用了一种有效的简化手段,大大压缩了模型的大小,使得5元模型和传统的2元模型大小基本相同,而预测精度提高了1倍.该结果可以广泛地运用到Web上,包括网页的预发送、预取、推荐以及Web上的caching机制.试验是建立在真实的Web日志上的,该算法无论在预测精度上还是在可适用度上都优于以往的算法.

高效的WEB-Log Mining算法

通过对WEB服务器日志文件进行分析,可以发现相似的客户群体、相关WEB页面以及频繁访问路径。这里提出了一种新颖的WEB日志挖掘算法,该算法是以服务器日志文件中的不同会话为聚类对象,通过对不同会话实施空间距离聚类和层次结构比较聚类,最终得到了满意的聚类结果。最后,给出了一个应用实例,实例表明,该方法是有效可行的。

Instability mechanism of mining roadway passing through fault at different angles in kilometre-deep mine and control measures of roof cutting and NPR cables

The angle α between the fault strike and the axial direction of the roadway produces different damage characteristics. In this paper, the research methodology includes theoretical analyses, numerical simulations and field experiments in the context of the Daqiang coal mine located in Shenyang, China. The stability control countermeasure of "pre-splitting cutting roof + NPR anchor cable"(PSCR-NPR) is simultaneously proposed. According to the different deformation characteristics of the roadway, the faults are innovatively classified into three types, with α of type I being 0°-30°, α of type II being 30°-60°, and α of type III being 60°-90°. The full-cycle stress evolution paths during mining roadway traverses across different types of faults are investigated by numerical simulation. Different pinch angles α lead to high stress concentration areas at different locations in the surrounding rock. The non-uniform stress field formed in the shallow surrounding rock is an important reason for the instability of the roadway. The pre-cracked cut top shifted the high stress region to the deep rock mass and formed a low stress region in the shallow rock mass. The high prestressing NPR anchor cable transforms the non-uniform stress field of the shallow surrounding rock into a uniform stress field. PSCR-NPR is applied in the fault-through roadway of Daqiang mine. The low stress area of the surrounding rock was enlarged by 3-7 times, and the cumulative convergence was reduced by 45%-50%. It provides a reference for the stability control of the deep fault-through mining roadway.

InSAR-derived surface deformation characteristics and mining subsidence parameters in mountain coal mines

Mining-induced surface deformation disrupts ecological balance and impedes economic progress.This study employs SBAS-InSAR with 107-view of ascending and descending SAR data from Sentinel-1,spanning February 2017 to September 2020,to monitor surface deformation in the Fa’er Coal Mine,Guizhou Province.Analysis on the surface deformation time series reveals the relationship between underground mining and surface shifts.Considering geological conditions,mining activities,duration,and ranges,the study determines surface movement parameters for the coal mine.It asserts that mining depth significantly influences surface movement parameters in mountainous mining areas.Increasing mining depth elevates the strike movement angle on the deeper side of the burial depth by 22.84°,while decreasing by 7.74°on the shallower side.Uphill movement angles decrease by 4.06°,while downhill movement angles increase by 15.71°.This emphasizes the technology's suitability for local mining design,which lays the groundwork for resource development,disaster prevention,and ecological protection in analogous contexts.

Coordinated Mining Procedures of Open Pit Mines Based on River Management

This paper primarily concerns the effective coordination of the procedures and methods employed in open pit mining operations under the background of river management.The central objective of this study is to identify a viable approach for ensuring rational and efficient development of open pit mineral resources while simultaneously protecting and restoring the ecological environment of the river.This approach should facilitate the realization of a harmonious symbiosis between mining and river management.The intricate mutual influence relationship between river management and open pit mining is first analyzed in depth,which provides a solid foundation for the subsequent coordination strategy development.In light of the aforementioned considerations,a set of coordination procedures for open pit mining based on river management conditions is proposed.These procedures emphasize the integration of river protection into the overall layout of mining at the planning stage.The implementation of scientific mining schemes,accompanied by rigorous control of the scope and depth of mining operations,has proven to be an effective means of reducing the impact of mining activities on river environments.This approach has also facilitated the achievement of a balance and coordination between mining and river management.

Study on the Safety and Prevention Technology of Coal Mining under the River in Xingyuan Coal Mine

Coal mining-induced surface subsidence poses significant ecological and infrastructural challenges, necessitating a comprehensive study to ensure safe mining practices, particularly in underwater conditions. This project aims to address the extensive impact of coal mining on the environment, infrastructure, and overall safety, focusing on the Shigong River area above the working face. The study employs qualitative and quantitative analyses, along with on-site engineering measurements, to gather data on crucial parameters such as coal seam characteristics, roof rock lithology, thickness, water resistance, and structural damage degree. The research encompasses a multidisciplinary approach, involving mining, geology, hydrogeology, geophysical exploration, rock mechanics, mine surveying, and computational mathematics. The importance of effective safety measures and prevention techniques is emphasized, laying the foundation for research focused on the Xingyun coal mine. The brief concludes by highlighting the potential economic and social benefits of this project and its contribution to valuable experience for future subsea coal mining.

Mechanism,prevention,and control of mining-induced dynamic disasters in underground metal mines in China:Challenges and solutions

Metal mineral resources play an indispensable role in the development of the national economy.Dynamic disasters in underground metal mines seriously threaten mining safety,which are major scientific and technological problems to be solved urgently.In this article,the occurrence status and grand challenges of some typical dynamic disasters involving roof falling,spalling,collapse,large deformation,rockburst,surface subsidence,and water inrush in metal mines in China are systematically presented,the characteristics of mining-induced dynamic disasters are analyzed,the examples of dynamic disasters occurring in some metal mines in China are summarized,the occurrence mechanism,monitoring and early warning methods,and prevention and control techniques of these disasters are highlighted,and some new opinions,suggestions,and solutions are proposed simultaneously.Moreover,some shortcomings in current disaster research are pointed out,and the direction of efforts to improve the prevention and control level of dynamic disasters in China’s metal mines in the future is prospected.The integration of forward-looking key innovative theories and technologies in the abovementioned aspects will greatly enhance the cognitive level of disaster prevention and mitigation in China’s metal mining industry and achieve a significant shift from passive disaster relief to active disaster prevention.

Progress and prospects of mining with backfill in metal mines in China

Mining is the foundation of modern industrial development.In the context of the“carbon peaking and carbon neutrality”era,countries have put forward the development strategy of“adhering to the harmonious coexistence of humans and nature.”The ongoing progress and improvement of filling mining technology have provided significant advantages,such as“green mining,safe,efficient,and low-carbon emission,”which is crucial to the comprehensive utilization of mining solid waste,environmental protection,and safety of re-mining.This review paper describes the development history of metal mine filling mining in China and the characteristics of each stage.The excitation mechanism and current research status of producing cementitious materials from blast furnace slag and other industrial wastes are then presented,and the concept of developing cementitious materials for backfill based on the whole solid waste is proposed.The advances in the mechanical characteristics of cemented backfill are elaborated on four typical levels:static mechanics,dynamic mechanics,mechanical influencing factors,and multi-scale mechanics.The working/rheological characteristics of the filling slurry are presented,given the importance of the filling materials conveying process.Finally,the future perspectives of mining with backfill are discussed based on the features of modern filling concepts to provide the necessary theoretical research value for filling mining.

Stability control measures for roof cutting and NPR supporting of mining roadways in fault areas of kilometre-deep coal mine

The study focuses on the stability control measures for mining roadways in fault zones of deep mines,using Daqiang Coal Mine as a case study.The control system under consideration,referred to as"pre-splitting cutting roof+NPR anchor cable"(PSCR-NPR),is subjected to scrutiny through theoretical analysis,numerical modelling,and field trials.Furthermore,a comprehensive analysis is undertaken to evaluate the stability control mechanism of this particular technology.The study provides evidence that the utilization of deep-hole directional energy-concentrated blasting facilitates the attainment of directional roof cutting in roadways.The aforementioned procedure leads to the formation of a uniform structural surface on the roof of the roadway and causes modifications in the surrounding geological formation.The examination of the lateral abutment pressure and shear stress distribution,both prior to and subsequent to roof cutting,indicates that the implementation of pre-splitting techniques leads to a noteworthy reduction in pressure.The proposition of incorporating the safety factor Q for roof cutting height is suggested as a method to augment comprehension of the pressure relief phenomenon in the field of engineering.The analysis of numerical simulation has indicated that the optimal pressure relief effect of a mining roadway in a fault area is attained when the value of Q is 1.8.The NPR anchor cable exhibits noteworthy characteristics,including a high level of prestress,continuous resistance,and substantial deformation.After the excavation of the roadway,a notable reduction in radial stress occurs,leading to the reinstatement of the three-phase stress state in the surrounding rock.This restoration is attributed to the substantial prestress exerted on the radial stress.The termination point of the NPR anchor cable is strategically positioned within a stable rock formation,allowing for the utilization of the mechanical characteristics of the deep stable rock mass.This positioning serves to improve the load-bearing capacity of the surrounding rock.The mining roadway within the fault region of Daqiang Coal Mine is outfitted with the PSCR-NPR technology.The drop in shear stress experienced by the rock surrounding the roadway is estimated to be around 30%,whilst the low-stress region of the mining roadway extends by a factor of approximately 5.5.The magnitude of surface displacement convergence experiences a decrease of approximately 45%-50%.The study’s findings provide useful insights regarding the stable of mining roadway in characterized by fault zones.

Ground fissure development regularity and formation mechanism of shallow buried coal seam mining with Karst landform in Jiaozi coal mine: a case study

A comprehensive study was undertaken at Jiaozi coal mine to investigate the development regularity of ground fissures in shallow buried coal seam mining with Karst landform,shedding light on the development type,geographical distribution,dynamic development process,and failure mechanism of these ground fissures by employing field monitoring,numerical simulation,and theoretical analysis.The findings demonstrate that ground fissure development has an obvious feature of subregion,and its geographical distribution is significantly affected by topography.Tensile type,open type,and stepped type are three different categories of ground fissure.Ground fissures emerge dynamically as the panel advances,and they typically develop with a distance of less than periodic weighting step distance in advance of panel advancing position.Ground fissures present the dynamic development feature,temporary fissure has the ability of self-healing.The dynamic development process of ground fissure with closed-distance coal seam repeated mining is expounded,and the development scale is a dynamic development stage of“closure→expansion→stabilized”on the basis of the original development scale.From the perspective of topsoil deformation,the computation model considering two points movement vectors towards two directions of the gob and the ground surface is established,the development criterion considering the critical deformation value of topsoil is obtained.The mechanical model of hinged structure of inclined body is proposed to clarify the ground fissure development,and the interaction between slope activity and ground fissure development is expounded.These research results fulfill the gap of ground fissures about development regularity and formation mechanism,and can contribute to ground fissure prevention and treatment with Karst landform.

Sustainable Mining in the Era of Artificial Intelligence

The mining sector historically drove the global economy but at the expense of severe environmental and health repercussions,posing sustainability challenges[1]-[3].Recent advancements on artificial intelligence(AI)are revolutionizing mining through robotic and data-driven innovations[4]-[7].While AI offers mining industry advantages,it is crucial to acknowledge the potential risks associated with its widespread use.Over-reliance on AI may lead to a loss of human control over mining operations in the future,resulting in unpredictable consequences.

Spatiotemporal deformation characteristics of Outang landslide and identification of triggering factors using data mining

Since the impoundment of Three Gorges Reservoir(TGR)in 2003,numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall.One case is the Outang landslide,a large-scale and active landslide,on the south bank of the Yangtze River.The latest monitoring data and site investigations available are analyzed to establish spatial and temporal landslide deformation characteristics.Data mining technology,including the two-step clustering and Apriori algorithm,is then used to identify the dominant triggers of landslide movement.In the data mining process,the two-step clustering method clusters the candidate triggers and displacement rate into several groups,and the Apriori algorithm generates correlation criteria for the cause-and-effect.The analysis considers multiple locations of the landslide and incorporates two types of time scales:longterm deformation on a monthly basis and short-term deformation on a daily basis.This analysis shows that the deformations of the Outang landslide are driven by both rainfall and reservoir water while its deformation varies spatiotemporally mainly due to the difference in local responses to hydrological factors.The data mining results reveal different dominant triggering factors depending on the monitoring frequency:the monthly and bi-monthly cumulative rainfall control the monthly deformation,and the 10-d cumulative rainfall and the 5-d cumulative drop of water level in the reservoir dominate the daily deformation of the landslide.It is concluded that the spatiotemporal deformation pattern and data mining rules associated with precipitation and reservoir water level have the potential to be broadly implemented for improving landslide prevention and control in the dam reservoirs and other landslideprone areas.

The influence of inter-band rock on rib spalling in longwall panel with large mining height

In order to improve rib stability,failure criteria and instability mode of a thick coal seam with inter-band rock layer are analysed in this study.A three-dimensional mechanical model is established for the rib by considering the rock layer.A safety factor is defined foy the rib,and it is observed that the safety factor exhibits a positive correlation with the thickness and strength of the inter-band rock.A calculation method for determining critical parameters of the rock layer is presented to ensure the rib stability.It is revealed that incomplete propagation of the fracture at the hard rock constitutes a fundamental prerequisite for ensuring the rib stability.The influence of the position of the inter-band rock in the coal seam on failure mechanism of the rib was thoroughly investigated by developing a series of physical models for the rib at the face area.The best position for the inter-band rock in the coal seam is at a height of 1.5 m away from the roof line,which tends to provide a good stability state for the rib.For different inter-band rock positions,two ways of controlling rib by increasing supports stiffness and flexible grouting reinforcement are proposed.

Artificial ground freezing of underground mines in cold regions using thermosyphons with air insulation

Current practice of underground artificial ground freezing(AGF)typically involves huge refrigeration systems of large economic and environmental costs.In this study,a novel AGF technique is proposed deploying available cold wind in cold regions.This is achieved by a static heat transfer device called thermosyphon equipped with an air insulation layer.A refrigeration unit can be optionally integrated to meet additional cooling requirements.The introduction of air insulation isolates the thermosyphon from ground zones where freezing is not needed,resulting in:(1)steering the cooling resources(cold wind or refrigeration)towards zones of interest;and(2)minimizing refrigeration load.This design is demonstrated using well-validated mathematical models from our previous work based on two-phase enthalpy method of the ground coupled with a thermal resistance network for the thermosyphon.Two Canadian mines are considered:the Cigar Lake Mine and the Giant Mine.The results show that our proposed design can speed the freezing time by 30%at the Giant Mine and by two months at the Cigar Lake Mine.Further,a cooling load of 2.4 GWh can be saved at the Cigar Lake Mine.Overall,this study provides mining practitioners with sustainable solutions of underground AGF.

A Quarterly High RFM Mining Algorithm for Big Data Management

In today’s highly competitive retail industry,offline stores face increasing pressure on profitability.They hope to improve their ability in shelf management with the help of big data technology.For this,on-shelf availability is an essential indicator of shelf data management and closely relates to customer purchase behavior.RFM(recency,frequency,andmonetary)patternmining is a powerful tool to evaluate the value of customer behavior.However,the existing RFM patternmining algorithms do not consider the quarterly nature of goods,resulting in unreasonable shelf availability and difficulty in profit-making.To solve this problem,we propose a quarterly RFM mining algorithmfor On-shelf products named OS-RFM.Our algorithmmines the high recency,high frequency,and high monetary patterns and considers the period of the on-shelf goods in quarterly units.We conducted experiments using two real datasets for numerical and graphical analysis to prove the algorithm’s effectiveness.Compared with the state-of-the-art RFM mining algorithm,our algorithm can identify more patterns and performs well in terms of precision,recall,and F1-score,with the recall rate nearing 100%.Also,the novel algorithm operates with significantly shorter running times and more stable memory usage than existing mining algorithms.Additionally,we analyze the sales trends of products in different quarters and seasonal variations.The analysis assists businesses in maintaining reasonable on-shelf availability and achieving greater profitability.

Preface:Heavy metal(loid)s at mining&metallurgical sites:Fate,risk and remediation

The contamination of heavy metal(loid)s at mining&metallurgical sites has been a major environmental challenge worldwide[1].Typically,large amounts of metal(loid)s-bearing wastes are generated at these sites,such as smelting slag,combustion residues,mine tailings,wastewater,and exhaust gas[2].Due to their high mobility in the environment,the released heavy metal(loid)s can easily enter the soil and water environment,posing long-term and widespread threats to ecological and human health[3].

Using deep neural networks coupled with principal component analysis for ore production forecasting at open-pit mines

Ore production is usually affected by multiple influencing inputs at open-pit mines.Nevertheless,the complex nonlinear relationships between these inputs and ore production remain unclear.This becomes even more challenging when training data(e.g.truck haulage information and weather conditions)are massive.In machine learning(ML)algorithms,deep neural network(DNN)is a superior method for processing nonlinear and massive data by adjusting the amount of neurons and hidden layers.This study adopted DNN to forecast ore production using truck haulage information and weather conditions at open-pit mines as training data.Before the prediction models were built,principal component analysis(PCA)was employed to reduce the data dimensionality and eliminate the multicollinearity among highly correlated input variables.To verify the superiority of DNN,three ANNs containing only one hidden layer and six traditional ML models were established as benchmark models.The DNN model with multiple hidden layers performed better than the ANN models with a single hidden layer.The DNN model outperformed the extensively applied benchmark models in predicting ore production.This can provide engineers and researchers with an accurate method to forecast ore production,which helps make sound budgetary decisions and mine planning at open-pit mines.

Using X Social Networks (formerly Twitter) and web news mining to predict the measles outbreak

Measles,an infectious disease caused by the measles virus,remains a significant public health concern worldwide due to its highly contagious nature and potential for severe complications[1].In addition to symptoms such as high fever,cough,Koplik spots,and rash,measles can lead to serious complications including pneumonia and myocarditis,particularly in vulnerable populations such as young children[1,2].

Integrated biomarker response to assess toxic impacts of iron and manganese on deep-sea mussel Gigantidas platifrons under a deep-sea mining activity scenario

Deep-sea mining activities can potentially release metals,which pose a toxicological threat to deep-sea ecosystems.Nevertheless,due to the remoteness and inaccessibility of the deep-sea biosphere,there is insufficient knowledge about the impact of metal exposure on its inhabitants.In this study,deep-sea mussel Gigantidas platifrons,a commonly used deep-sea toxicology model organism,was exposed to manganese(100,1000μg/L)or iron(500,5000μg/L)for 7 d,respectively.Manganese and iron were chosen for their high levels of occurrence within deep-sea deposits.Metal accumulation and a battery of biochemical biomarkers related to antioxidative stress in superoxide dismutase(SOD),catalase(CAT),malondialdehyde(MDA);immune function in alkaline phosphatase(AKP),acid phosphatase(ACP);and energy metabolism in pyruvate kinase(PK)and hexokinase(HK)were assessed in mussel gills.Results showed that deep-sea mussel G.platifrons exhibited a high capacity to accumulate Mn/Fe.In addition,most tested biochemical parameters were altered by metal exposure,demonstrating that metals could induce oxidative stress,suppress the immune system,and affect energy metabolism of deep-sea mussels.The integrated biomarker response(IBR)approach indicated that the exposure to Mn/Fe had a negative impact on deep-sea mussels,and Mn demonstrated a more harmful impact on deep-sea mussels than Fe.Additionally,SOD and CAT biomarkers had the greatest impact on IBR values in Mn treatments,while ACP and HK were most influential for the low-and high-dose Fe groups,respectively.This study represents the first application of the IBR approach to evaluate the toxicity of metals on deep-sea fauna and serves as a crucial framework for risk assessment of deep-sea mining-associated metal exposure.