A Simple Constraint-Based Algorithm for Efficiently Mining Observational Databases for Causal Relationships

This paper presents a simple, efficient computer-based method for discovering causal relationships from databases that contain observational data. Observational data is passively observed, as contrasted with experimental data. Most of the databases available for data mining are observational. There is great potential for mining such databases to discover causal relationships. We illustrate how observational data can constrain the causal relationships among measured variables, sometimes to the point that we can conclude that one variable is causing another variable. The presentation here is based on a constraint-based approach to causal discovery. A primary purpose of this paper is to present the constraint-based causal discovery method in the simplest possible fashion in order to (1) readily convey the basic ideas that underlie more complex constraint-based causal discovery techniques, and (2) permit interested readers to rapidly program and apply the method to their own databases, as a start toward using more elaborate causal discovery algorithms.     

广义杠杆规则及其在配方计算中的应用

作者将相图中的一维杠杆规则推广至多元配料系统而成为广义杠杆规则，并利用这一规则对配方计算中解的可行域问题进行了深入的讨论，给出了几何解释及工艺诠释，对配方设计有一定的指导作用。     

我国钨业“四矿”问题及其对策思考

简要回顾了我国钨矿业悠久的历史、资源的优势、技术的进步和卓越的贡献 ;20世纪80年代中期以后 ,逐步陷入困境 ,举步维艰的主要表现 ;以及在解决“四矿”(矿业、矿山、矿工、矿城)问题中的艰苦经历。指出应在“四矿”问题讨论中做更多、更深的对策思考 ,并对钨业的“四矿”问题加以重点研究。     

复杂开采条件矿体三强回采作业技术应用

本文针对金翅岭金矿矿体开采条件极其复杂的情况，在采矿方法试验中，率先在岩金矿山采用了三强作业技术，既保证了安全回采，又取是了较好的技术经济指标。     

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。     

模糊Petri网及知识表示

在建造专家系统中虽然有很多种知识表示方法，但都有不尽人意的地方，本文试图用一种新的方法－Ｐｅｔｒｉ网模型来表示知识。本文给出了Ｆｕｚｚｚｙ Ｐｅｔｒｉ网和广义Ｆｕｚｚｙ Ｐｅｔｒｉ网两种模型，并给出了相应的推理算法，一旦专家知识用Ｐｅｔｒｉ网表示后，根据Ｐｅｔｒｉ网固有的特性，我们就能处理专家系统中并行推理、无回溯推理，反向推理等问题。     

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％。     

基于Patel-Teja状态方程的统一粘度模型(Ⅱ)应用于油气藏流体粘度的预测

基于(I)报根据pVT和Tμp图形的相似性和Patel-Teja状态方程建立的预测纯流体气、液相粘度的统一模型,通过引入常规的状态方程参数的混合规则,将其应用于二元轻烃混合物共计1894个数据点及模拟天然气高压粘度的预测,平均相对误差分别为13.78%和16.75%;应用于油藏原油和天然气高压粘度的预测,结果优于现有的有关油气藏流体粘度模型.