A new time invariant fuzzy time series forecasting method based on particle swarm optimization

In the analysis of time invariant fuzzy time series, fuzzy logic group relationships tables have been generally preferred for determination of fuzzy logic relationships. The reason of this is that it is not need to perform complex matrix operations when these tables are used. On the other hand, when fuzzy logic group relationships tables are exploited, membership values of fuzzy sets are ignored. Thus, in defiance of fuzzy set theory, fuzzy sets’ elements with the highest membership value are only considered. This situation causes information loss and decrease in the explanation power of the model. To deal with these problems, a novel time invariant fuzzy time series forecasting approach is proposed in this study. In the proposed method, membership values in the fuzzy relationship matrix are computed by using particle swarm optimization technique. The method suggested in this study is the first method proposed in the literature in which particle swarm optimization algorithm is used to determine fuzzy relations. In addition, in order to increase forecasting accuracy and make the proposed approach more systematic, the fuzzy c-means clustering method is used for fuzzification of time series in the proposed method. The proposed method is applied to well-known time series to show the forecasting performance of the method. These time series are also analyzed by using some other forecasting methods available in the literature. Then, the results obtained from the proposed method are compared to those produced by the other methods. It is observed that the proposed method gives the most accurate forecasts.     

基于数据挖掘的复杂装备维修辅助决策研究

文章通过某装备维修信息框架分析,维修数据预处理,然后以维修记录为例,挖掘出了维修件之间关联规则,并采用决策树分类方法对维修件进行了分类,这些规则和分类结果可以为维修计划制定、器材采购、视情维修等方面提供决策依据。     

Distributed match-making

In many distributed computing environments, processes are concurrently executed by nodes in a store- and-forward communication network. Distributed control issues as diverse as name server, mutual exclusion, and replicated data management involve making matches between such processes. We propose a formal problem called distributed match-making as the generic paradigm. Algorithms for distributed match-making are developed and the complexity is investigated in terms of messages and in terms of storage needed. Lower bounds on the complexity of distributed match-making are established. Optimal algorithms, or nearly optimal algorithms, are given for particular network topologies.The work of the second author was supported in part by the Office of Naval Research under Contract N00014-85-K-0168, by the Office of Army Research under Contract DAAG29-84-K-0058, by the National Science Foundation under Grant DCR-83-02391, and by the Defence Advanced Research Projects Agency (DARPA) under Contract N00014-83-K-0125. Current address of both authors: CWI, Kruislaan 413, 1098 SJ Amsterdam, The Netherlands.     

曝光数据流优化问题的蒙特卡罗算法

集成工艺中控制图形发生器产生掩模图形的数据流文件的数据排列顺序优化,是一个其结点数可达数千个之多的大规模旅行商问题(从镜头架的位置,即每个矩形的矩心为结点),常规算法早已不适用。本文采用多阶段蒙特卡罗算法并加以改进,补充了“分层优化模式”,邻接结点的预合并和在各个阶段末提取共同子路径并删去相关结点等一系列逐步缩小问题规模的措施,形成了一个实用的优化算法。相应的软件已成功地应用于薄膜磁头的数据流文件的优化。     

An experimental study of the thermodynamic properties of 1,1-difluoroethane

Experimental vapor pressures andP--T data of an important alternative refrigerant, 1, 1-difluoroethane (HFC-152a), have been measured by means of a constant-volume method coupled with expansion procedures. SixtyP--T data were measured along eight isochores in a range of temperaturesT from 330 to 440 K, at pressuresP from 1.6 to 9.3 MPa, and at densities from 51 to 811 kg·m^–3. Forty-six vapor pressures were also measured at temperatures from 320 K to the critical temperature. The uncertainties of the temperature and pressure measurements are within ±7mK and ±2kPa, respectively, while the uncertainty of the density values is within ±0.1%. The purity of the sample used is 99.9 wt%. On the basis of the measurements along each isochore, five saturation points were determined and the critical pressure was determined by correlating the vapor-pressure measurements. The second and third virial coefficients for temperatures from 360 to 440 K have also been determined.     

A Further Comparison of Splitting Rules for Decision-Tree Induction

One approach to learning classification rules from examples is to build decision trees. A review and comparison paper by Mingers (Mingers, 1989) looked at the first stage of tree building, which uses a splitting rule to grow trees with a greedy recursive partitioning algorithm. That paper considered a number of different measures and experimentally examined their behavior on four domains. The main conclusion was that a random splitting rule does not significantly decrease classificational accuracy. This note suggests an alternative experimental method and presents additional results on further domains. Our results indicate that random splitting leads to increased error. These results are at variance with those presented by Mingers.     

Rapid software integration using structured methods

In this paper we discuss an approach to organizing the integration of 110,000 lines of C, SQL, Assembler, and microcode distributed over a network of 36 processors of four types so that it could be accomplished in six months. The software runs on a test system architecture consisting of a LAN-based workstation group and a set of VME-based embedded processors. By using structured methodology, parallelism in the integration process was achieved. The necessary stub tools were identified and developed before integration began. The principles followed and experiences of integrating the system are discussed.     

针对肌肉功能障碍患者的数据库研究与开发

建立标准数据库是临床研究病情变化的重要手段,建立适用于肌肉功能障碍患者的标准数据库模板更具有重要临床意义。本研究针对临床上所采集的具有肌肉功能障碍患者的肌力、肌电数据,通过ODBC连接方式,引入了统一建模语言(UML),使用VC++开发工具,设计和完成了Access数据库,以对获取到的大量的肌力、肌电数据进行管理和使用。数据库有效存储并管理肌力、肌电数据,同时能减少数据占有空间和数据冗余,它更好地满足了医院康复科的需求。     

偏最小二乘回归在气温预测中的研究与应用

气温的预测要考虑多重气象因子,然而各气象因子间的多重相关性导致普通的多元回归模型失真,预测精度降低。为了解决以上问题,本研究采用偏最小二乘回归(Partial Least Squares Regression,简称PLS)建模,根据实际建模需要对算法进行改进。为了验证该模型,本研究以成都市10月份气温场为预报场,并结合成都市13个自动站气温数据,提取预报所需主要因子,进行PLS回归建模。实验表明该模型有较好的预测能力。     

基于MapXtreme的数字校园房管系统的开发

校园规模在不断地扩大,校园房屋管理规划部门对日益更新和迅速增加的建筑物房屋信息的管理与维护愈感困难,而现有的系统对空间数据与属性数据没有很好集成,更不利于图文信息的相互查询、检索和更新等。针对如上现实问题,应用MapInfo平台中的WebGIS技术,即MapXtreme技术,以及UML统一建模技术和SQL Server数据库等技术,成功地实现了数字校园房屋管理系统设计与开发,解决了房管部门面临的查询搜索更新校园建筑房屋信息时效率低下、管理与维护困难等实际问题。