基于Web的工程索赔决策支持系统的研究

针对我国工程索赔经验少、索赔专家稀缺的实际情况，提出了一种基于Web的工程索赔决策支持系统，首先综合了数据仓库，联机分析处理，数据挖掘技术于一体的综合决策支持系统，给出了数据仓库、模型库和知识库的具体设计，最后对系统的实现作了简要的介绍，该系统的应用旨在建立一个功能强大的在线工程索赔支持平台，共享索赔专家丰富的知识和经验，帮助承包商完成复杂的索赔工作。     

提高炮采工作面块煤率的爆破技术

通过小规模爆破试验，用线性回归方法对块煤进行筛分分析，指出影响炮采工作面块煤率的因素是炸药性能、装药结构、爆破参数、起爆顺序、时间间隔等。     

陆相断陷盆地层序地层与成藏单元类比分析——以济阳坳陷为例

陆相断陷盆地不同级别的层序地层是不同层次构造运动形式的物质体现，也以不同的方式对应着不同类型的石油地质要素。盆地不同级别成藏单元成因划分的基础是不同层次的成藏要素类型及其作用，通过不同级别层序地层、地质要素及其作用内在联系的分析，认为不同级别的层序地层单元与成藏单元之间可以建立起成因类比关系，一级层序、二级层序、三级层序分别以不同的方式对应于含油气盆地、含油气系统或复式油气聚集带、成藏组合体．从而更加深入地反映陆相断陷位地等时成因地层格架与成藏单元结构间的内在成因联系。     

垦西油田东营组高分辨率层序地层与沉积微相研究——以K71断块区为例

以高分辨率层序地层学和传统沉积学理论为指导,通过岩心观察和测井相分析,在基准面旋回的识别与划分基础上,建立垦西油田东营组地层的高分辨率等时地层格架,并进行了基准面旋回对比,进而应用油藏描述技术中的沉积微相分析方法,遵循从点(标准井测井沉积微相分析)到线(全区多井对比)的基本原则,对垦西油田K71断块区东营组储层的沉积微相类型及特征进行了详细研究.研究认为,东营组为湖泊-三角洲沉积相,而且可以细分为三角洲平原沉积亚相、三角洲前缘沉积亚相及前三角洲沉积亚相,每种亚相都具有特定的沉积微相构成及特征,这些特征的识别对基准面对比及其储层物性的预测都具有重要意义.     

A genetic algorithm for the optimisation of assembly sequences

This paper describes a Genetic Algorithm (GA) designed to optimise the Assembly Sequence Planning Problem (ASPP), an extremely diverse, large scale and highly constrained combinatorial problem. The modelling of the ASPP problem, which has to be able to encode any industrial-size product with realistic constraints, and the GA have been designed to accommodate any type of assembly plan and component. A number of specific modelling issues necessary for understanding the manner in which the algorithm works and how it relates to real-life problems, are succinctly presented, as they have to be taken into account/adapted/solved prior to Solving and Optimising (S/O) the problem. The GA has a classical structure but modified genetic operators, to avoid the combinatorial explosion. It works only with feasible assembly sequences and has the ability to search the entire solution space of full-scale, unabridged problems of industrial size. A case study illustrates the application of the proposed GA for a 25-components product.     

A clustering method to distribute a database on a grid

Clusters and grids of workstations provide available resources for data mining processes. To exploit these resources, new distributed algorithms are necessary, particularly concerning the way to distribute data and to use this partition. We present a clustering algorithm dubbed Progressive Clustering that provides an “intelligent” distribution of data on grids. The usefulness of this algorithm is shown for several distributed datamining tasks.     

Nonlinear suboptimal filtration of pseudorandom sequences

The critical importance of studies of alternative methods of representation and processing of signals constructed from pseudorandom sequences of maximal period is demonstrated. For the first time, it is proposed that a multidimensional nonlinear finite-difference representation of an arbitrary pseudorandom sequence be employed. A suboptimal algorithm for nonlinear discrete Kalman filtration of a pseudorandom sequence is obtained. A numerical example of filtration of a sequence formed on the basis of a given recurrence rule is considered and its efficiency is demonstrated.     

An efficient algorithm for mining frequent inter-transaction patterns

In this paper, we propose an efficient method for mining all frequent inter-transaction patterns. The method consists of two phases. First, we devise two data structures: a dat-list, which stores the item information used to find frequent inter-transaction patterns; and an ITP-tree, which stores the discovered frequent inter-transaction patterns. In the second phase, we apply an algorithm, called ITP-Miner (Inter-Transaction Patterns Miner), to mine all frequent inter-transaction patterns. By using the ITP-tree, the algorithm requires only one database scan and can localize joining, pruning, and support counting to a small number of dat-lists. The experiment results show that the ITP-Miner algorithm outperforms the FITI (First Intra Then Inter) algorithm by one order of magnitude.     

Geotechnical study for optimizing the slope design of a deep open-pit mine,India

The study was undertaken to determine the optimal overall slope angle of a lead–zinc mine, which could extend down to a depth of 170 m. Detailed geotechnical investigations were conducted, including geotechnical mapping of existing benches to establish the geometrical and mechanical properties of the discontinuities, the drilling of eight boreholes and the establishment of the physico-mechanical properties of the intact rock. Based on these data, limit equilibrium and numerical simulation techniques were applied to assess the stability of the slopes and determine an optimal slope angle. It was concluded that the overall foot-wall and hanging-wall slopes should be 42 and 48° respectively.      

Development of materials database system for cae system of heat treatment based on data mining technology

Computer simulation for materials processing needs of materials. In order to employ the accumulated large data on a huge database containing a great deal of various physical properties materials heat treatment in the past years, it is significant to develop an intelligent database system. Based on the data mining technology for data analysis, an intelligent database web tool system of computer simulation for heat treatment process named as IndBASEweb-HT was built up. The architecture and the arithmetic of this system as well as its application were introduced.