Reconfiguring existing pollutant monitoring stations by increasing the value of the gathered information

The objective of this study is to provide a framework for relocating or reconfiguring existing pollution monitoring station networks by using feature selection and data mining techniques. This methodology enables a partial redesign based on the maximization of the available information that is gathered by the pollution networks by the optimal data mining technique. It also considers requirements of the decision makers, like potential target places, etc.Since this methodology is based on the quality of forecasting, it can also be useful for auditing and forecasting. A case study is included in this paper. In light of the prediction results, a new way to relocate the existing monitoring station is proposed.     

基于聚类的多数据库分类算法的研究与实现

针对多数据库挖掘的预处理,提出了运用聚类的思想来对数据库进行分类。同时,提出了改进的BestClassification算法。通过实验证明这种分类方法具有较好的有效性和正确性。     

网络信息挖掘在电子商务系统中的应用

描述了网络信息挖掘的含义以及与数据挖掘之间的区别,提出了在电子商务应用中采用网络信息挖掘帮助企业实现最大化利润的方法,最后指出了网络信息挖掘未来的研究方向。     

基于多媒体多智能Agents系统的群体决策支持系统集成化设计研究

分析了Ｄeｓａｎｅｔｉｓ＆Ｇａｌｌｕｐｅ群体决策支持系统（Ｇｒｏｕｐ Ｄｅｃｉｓｉｏｎ Ｓｕｐｐｏｒｔ,简称ＧＤＳＳ）初步设计的通用模式,提出了将多媒体技术、智能Ａｇeｎｔs技术、数据仓库技术Ｉｎｔｅｒｎｅｔ／Ｉｎｔｒａｎｅｔ技术等有机地集成于ＧＤＳＳ的集成化设计方案,并就其关键技术功能结构方案设计进行了研究．     

WWW上路径模式发掘的研究

本文从互连网发展的趋势入手,对路径模式发掘进行了研究。先简要介绍数据库发掘的概况及网上数据发掘的特点,后结合关联法和组合概率法,并以算法和实例详细对之进行分析。     

我国露天矿应用半连续开采工艺的现状与前景

介绍了半连续开采工艺在我国露天矿山的应用现状和特点,分析了采用该工艺的必要性,展望了半连续开采工艺的发展趋势,为加速发展我国露天矿山半连续开采工艺而提出几项建议。     

基于数据挖掘的评教系统的设计与实现

为了提高评教数据在教学管理中的利用率,更加有效地为学校的决策服务。本文在研究了数据仓库、OLAP分析、数据挖掘技术的基础上,设计和实现了评教系统,实现了对评教数据的综合分析和深入挖掘。使用该系统后,教学管理部门改变了对评教数据的使用方式,提高了利用率,认识和理解更加深人和全面。     

Deformation effect of lateral roof roadway in close coal seams after repeated mining

This paper analyzed the deformation mechanism in lateral roof roadway of the Ding Wu-3 roadway which was disturbed by repeated mining of close coal seams Wu-8 and Wu-10 in Pingdingshan No. 1 Mine. To determine the strata disturbance scope, the strata displacement angle was used to calculate the protection pillar width. A numerical model was built considering the field geological conditions. In simulation, the mining stress borderline was defined as the contour where the induced stress is 1.5 times of the original stress. Simulation results show the mining stress borderline of the lateral roadway extended 91.7 m outward after repeated mining. Then the original stress increased, deforming the roadway of interest. This deformation agreed with the in situ observations. Moreover, the strata displacement angle changed due to repeated mining. Therefore, reselection of the displacement angle was required to design the protective pillar width. Since a constant strata displacement angle was used in traditional design, the proposed method was beneficial in field cases.     

Stores clustering using a data mining approach for distributing automotive spare-parts to reduce transportation costs

Clustering of retail stores in a distribution network with specific geographical limits plays an important and effective role in distribution and transportation costs reduction. In this paper, the relevant data and information for an established automotive spare-parts distribution and after-sales services company (ISACO) for a 3-year period have been analyzed. With respect to the diversity and lot size of the available information such as stores location, order, goods, transportation vehicles and road and traffic information, three effecting factors with specific weights have been defined for the similarity function: 1. Euclidean distance, 2. Lot size 3. Order concurrency. Based on these three factors, the similarity function has been examined through 5 steps using the Association Rules principles, where the clustering of the stores is performed using k-means algorithm and similar stores are allocated to the clusters. These steps include: 1. Similarity function based on the Euclidean distances, 2. Similarity function based on the order concurrency, 3. Similarity function based on the combination of the order concurrency and lot size, 4. Similarity function based on the combination of these three factors and 5. Improved similarity function. The above mentioned clustering operation for each 5 cases addressed in data mining have been carried out using R software and the improved combinational function has been chosen as the optimal clustering function. Then, trend of each retail store have been analyzed using the improved combinational function and along with determining the priority of the depot center establishment for every cluster, the appropriate distribution policies have been formulated for every cluster. The obtained results of this study indicate a significant cost reduction (32%) in automotive spare-parts distribution and transportation costs.