我国煤矿开采新技术探讨

我国煤矿开采技术在“十一五”期间取得了重大进展.论文介绍了绿色开采、充填开采、无煤柱开采、离层注浆减沉、特厚煤层大采高综放开采成套技术、大倾角综采、煤与瓦斯共采等技术的应用实践情况.     

放顶煤技术在残煤开采中的应用

放顶煤技术是适用于煤层较厚、煤质松散的煤层开采的-种方法.残煤开采是将过去已开采区留下的煤柱、不可采的煤柱.再进行复采.本文就放顶煤技术在残煤开采中遇到的有关问题做一般性分析,仅供参考.     

薄煤层开采技术

我国薄煤层资源丰富,但采出率低.论文介绍了薄煤层资源现状及薄煤层开采技术现状,详细介绍了我国近年来薄煤层开采技术取得的新进展.     

不规则边角工作面仰角开采方法与快速调采技术

本文主要阐述了矿井不规则边角工作面开采的技术路线,主要内容,仰采开采挫术方法和快速调采等技术问题.     

浅论煤矿开采的技术分析

本文主要分析了当前煤矿地下开采技术,并展开了优化巷道布置、减少矸石排放的开采技术、采场围岩控制技术,煤炭地下气化技术.     

简析一次采全高采煤工艺

随着采矿技术的不断发展,如何进一步提高资源采出率成为煤矿企业实现可持续发展必需解决的技术难题.实践证明,大采高综采是提高工作面开采强度,减少资源损失的有效途径.     

浅谈煤矿残煤的开采

针时煤矿残采布巷、工作面初次来压、采场支护方式、工程质量、残采单放、大倾角单放开采、开采前史料查找等问题以煤矿安全、生产、效益为目标,从实践中摸索研究、合理可行、适合安全生产的方法和途径.     

煤矿残煤开采研究

针对煤矿残采布巷、工作面初次来压、秉场支护方式、工程质量、残采单放、大倾角单放开采、开采前史料查找等问题以煤矿安全、生产、效益为目标.从实践中摸索研究、合理可行、适合安全生产的方法和途径.     

谈矿井安全开采技术问题

本文主要阐述了高产高效炮采工作面长度、工作面开采的实用技术、新型支护用品的改进与使用、瓦斯综合治理技术等矿井安全开采的技术问题。     

综采技术在珲春矿区推广应用

吉煤集团珲春矿业公司运用锚网索联合支护技术,大倾角伪下回采技术,液压支架快速回撤技术,多种形状工作面调整技术和"采准合一"劳动组织法,成功解决了复杂地质构造条件下应用综采枝术出现的主要问题.目前,公司综采程度达到百分之百,单产水平居吉林省中厚煤层开采的前列.     

Data mining in business services

Data mining applies traditional statistical tools as well as artificial intelligence algorithms to the analysis of large datasets. Data mining has proven very effective in many fields, including business. This paper reviews applications of data mining relevant to the service industry, and demonstrates primary business functions and data mining methods. Typical industry data mining process is described, analytic tools are reviewed, and major software tools noted.     

煤矿开采新技术分析

小煤矿开采工艺落后,安全条件差,资源同收率低.国家实施关闭小煤矿,淘汰落后的生产技术和生产设备,提高平均单井规模的技术政策,开发小型煤矿机械化、半机械化开采技术和装备,改进小煤矿的采煤方法和开采工艺,提高采煤工作面的单产和工效,有着积极意义.文章结合国内、外采煤方法的改革发展,分析我国乡镇煤矿开采技术的条件,总结了我国乡镇小煤矿开采适用的采矿新技术.     

Data mining: proprietary rights, people and proposals

This article focuses on the issue of data mining as it relates to the consumer and to the issue of whether the consumer's private information has any proprietary status. A brief review of data mining is provided as a background for a better understanding of the purposes and uses of data mining. Also examined are several issues of the ethics of data mining, including a review of stakeholders, who they are and which may be most seriously affected by unethical data mining practices. Several suggestions for the improvement of data mining as it relates to the consumer are further presented: suggestions that would allow for data mining that would be beneficial to both the business community and the consumer.     

Knowledge-intensive service activities in the success of the Australian mining industry

No other industry in Australia has achieved a greater significance in economic development terms as mining. The mineral industries have built a national infrastructure throughout Australia for more than a century and Australia's minerals boom has produced generations of mining technology services (MTS) companies. This paper discusses the role of MTS firms in the transformation of the mining industry into the knowledge economy. Results from a study of Australian MTS and mining firms suggest that innovation results from the interaction of these firms through knowledge-intensive service activities.     

企业电子商务中客户知识挖掘模型研究

本文从语义的视角构建了面向传统企业电子商务业务的客户知识挖掘模型,实现了在异构、分布式客户数据源语义集成的基础上实施客户知识挖掘过程,推动知识挖掘方法和技术智能化进程,提高客户知识挖掘模式产生的质量。     

User preference mining based on fine-grained sentiment analysis

User preference mining is an application of data mining that attracts increasing attention. Although most of the existing user preference mining methods achieved significant performance improvement, the sentiment tendencies of users were seldom considered. This paper proposes fine-grained sentiment analysis for preference mining. The powerful feature representation capabilities of deep neural networks have significantly improved the performance of fine-grained sentiment analysis. But two main challenges remain when using deep neural network models: incomplete user feature extraction and insufficient interaction. In response, a pre-training language model is employed to encode user features to fully explore potential interests of users, a linguistic knowledge model is introduced to assist the encoding, a multi-scale convolution neural network is adopted to capture text features at different scales and fully utilize the text information, and the fine-grained sentiment analysis task is modeled as a sequence labeling problem to explore the sentiment polarity of user evaluation. Experiments on a user review data set are used to verify the new approach. Experimental results of precision, recall rate and F1-value show that the proposed approach performs better, and is more effective than baseline models. For example, the F1-value is increased by 4.27% compared to the best performing baseline model. Findings have important implications for research and practice.     

Managing occupational health and safety in the mining industry

The mining industry is a high health risk occupation. Companies should implement occupational health and safety management (OHSM) rules and regulations. These companies face a rapidly booming mining sector and need the help of OHSM to achieve business goals. Being aware of the influential factors on the OHSM is needed to reduce work-related fatalities and increase the company's efficiency. Few studies identifying the influential factors on the implementation of OHSM in the mining industry are available. This study provides a general overview of OHSM and investigates the relationship between five factors influencing the implementation of occupational health and safety management among currently operational mining companies. The results show that the correlation of the five domains varies. Using factor loading to examine the most influential factor to the least influential factors, the order is shown as follows: act and regulation, stakeholder pressure, investment, integrated OHSM and organizational culture. In addition, lack of adequate investment from the government was reported by the majority of the OHS specialists. This finding is noteworthy in that there was an OHS specialist agreement that their companies do not spend at least 1% of their production and service cost to implement OHSM requirements.     

Multinational mining enterprises and artisanal small-scale miners: From confrontation to cooperation

In many developing countries, multinational enterprises (MNEs) in mining operate alongside fast-growing communities of informal artisanal, small-scale miners. This has led to direct conflict and competition for mineral resources. This paper introduces the Salience and Institutional Analysis and Design framework as a means to analyze the MNE strategies used to address informal miners across different governance levels in the gold mining sector of Ghana and discusses the implications of these strategies for sustainability. We identify the emergence of a cooperative strategy with informal miners as a sustainable alternative to the political strategy of reliance on the state to protect tenure.     

基于谱聚类的用户关联关系挖掘

为了从用户地理空间分布数据中挖掘用户间关联关系,提出了一种基于谱聚类的关联关系挖掘算法。首先定义了关联度,用以衡量用户之间空间分布的相似性,基于关联度构造相似矩阵,再利用谱聚类方法对用户进行聚类分析,聚类结果表征了用户的关联关系。采用Silhouette指标和聚类准确率来衡量用户关系挖掘质量,同时与传统的K-Means方法进行了比较,通过真实数据集实验,结果表明该算法在实验数据集上能达到90%以上的聚类准确率,证明方法有效、可行。     

Developing the profiles of supermarket customers through data mining

To stay competitive, supermarkets need to develop a viable customer retention strategy. Since a key to the successful development of such a strategy rests with customer relationship management, supermarkets should identify the most profitable ways to build and maintain a loyal customer relationship. In an effort to help supermarkets understand their customers' shopping/patronage behaviour and the ways to retain valued customers, we propose data mining techniques. Using the examples of franchised supermarkets in the south-eastern United States, this paper illustrates the usefulness of the proposed data mining techniques for examining customer grocery shopping behaviour and developing the profiles of loyal patrons.