新疆三塘湖盆地侏罗系煤有机地球化学特征

有机地球化学和有机岩石学研究结果表明，新疆三塘湖盆地侏罗系煤中富集孢子体和角质体（３．０％～６．０％，全岩体积百分比），对煤中氯仿沥青“Ａ”组成中较高的总烃馏分（３０％～５０％）和饱芳比（０．６～３．０）产生了影响。煤的聚集环境是影响煤的显微组分组成及生油特性的关键因素。三塘湖盆地侏罗系煤属于“晚生晚排”叠加有“早生早排”类型的烃源岩。     

露天矿场有规则安全小平台开采方法

文中提出了在高阶段不分层开采的露天矿场采用“有规则安全小平台开采方法”。开采坡度能够得到控制，有效地控制了采石场经常发生的塌方事故，能提高产量，降低生产成本，安全性好，且技术简单，易于推广。     

锚网支护在综采工作面开切眼中的应用

介绍了平煤集团一矿在戊8— 310 40综合机械化采煤工作面开切眼实施煤巷锚网支护的基本情况。总结了经验 ,为同类条件下的锚网支护设计提供了依据。     

A Search for Hidden Relationships: Data Mining with Genetic Algorithms

This paper presents an algorithm that permits the search for dependencies among sets of data (univariate or multivariate time-series, or cross-sectional observations). The procedure is modeled after genetic theories and Darwinian concepts, such as natural selection and survival of the fittest. It permits the discovery of equations of the data-generating process in symbolic form. The genetic algorithm that is described here uses parts of equations as building blocks to breed ever better formulas. Apart from furnishing a deeper understanding of the dynamics of a process, the method also permits global predictions and forecasts. The algorithm is successfully tested with artificial and with economic time-series and also with cross-sectional data on the performance and salaries of NBA players during the 94–95 season.     

松软矿体有底柱高分段崩落法的改进方案

锦屏磷矿对其东山采区松软矿体所使用的分段崩落法做了集中快速采准施工、增加分段高度、实行水平或上向扇形深孔连续崩矿等改进,简化了采场结构,矿石损失率由原来的63％下降到改进后的20.34％,贫化率由23.92％下降到15.10％。     

Computational complexity of queries based on itemsets

We investigate determining the exact bounds of the frequencies of conjunctions based on frequent sets. Our scenario is an important special case of some general probabilistic logic problems that are known to be intractable. We show that despite the limitations our problems are also intractable, namely, we show that checking whether the maximal consistent frequency of a query is larger than a given threshold is NP-complete and that evaluating the Maximum Entropy estimate of a query is PP-hard. We also prove that checking consistency is NP-complete.     

Apparent versus true density for the volume-to-weight transformation in coal blends

This work reviews the procedures involved in the conversion of the petrographic characterization data of blended coals into weight percentages of the single coals in the blends, the selection of the most suitable parameter for describing the density of the coals being critical. First, the fundamentals of the volume-to-weight transformation of the petrographic data were developed by means of mathematical formulae. This part of the procedure highlighted the need to use a density value adapted to the resolving power of the optical microscope. It was found that mercury penetration at 5 MPa, as determined by mercury porosimetry, was best suited for this purpose. A literature survey of published coal density data revealed that the use of correlations between coal density and rank was not an accurate enough procedure to deal with the relatively low corrections involved in the transformation of petrographic data. In the end, three binary blends were prepared from six carefully selected coals and polished particulate blocks of these blends were petrographically analysed to determine their compositions on a volume per cent basis. The best fit of these volume percentages with the weight percentages used in the formulation of the blends was found for a density correction based on mercury penetration at 5 MPa, in agreement with the empirical analysis.     

山西煤焦流通市场化改革建议

本文分析了山西在推进煤炭流通市场化过程中面临的机遇及现行体制弊端,提出建立更加适合市场经济的煤焦流通体制的若干建议。     

Non-redundant data clustering

Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice, this discovery process should avoid redundancies with existing knowledge about class structures or groupings, and reveal novel, previously unknown aspects of the data. In order to deal with this problem, we present an extension of the information bottleneck framework, called coordinated conditional information bottleneck, which takes negative relevance information into account by maximizing a conditional mutual information score subject to constraints. Algorithmically, one can apply an alternating optimization scheme that can be used in conjunction with different types of numeric and non-numeric attributes. We discuss extensions of the technique to the tasks of semi-supervised classification and enumeration of successive non-redundant clusterings. We present experimental results for applications in text mining and computer vision.