Transformation of semantic knowledge into simulation-based decision support

Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, in-depth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model. This knowledge-intensity leads to long development times of respective projects, which contradicts the need for timely decision support. Since more and more companies use industrial knowledge graphs and ontologies to foster their knowledge management, this paper proposes a framework on how to efficiently derive a simulation model from such semantic knowledge bases. As part of the approach, a novel Simulation Ontology provides a standardized meta-model for hybrid simulations. Its instantiation enables the user to come up with a fully parameterized formal simulation model. Newly developed Mapping Rules facilitate this process by providing guidance on how to turn knowledge from existing ontologies, which describe the system to be simulated, into instances of the Simulation Ontology. The framework is completed by a parsing procedure for an automated transformation of this conceptual model into an executable one. This novel modeling approach makes model development more efficient by reducing its complexity. It is validated in a use case implementation from semiconductor manufacturing, where cross-domain knowledge was required in order to model and simulate the impacts of the COVID-19 pandemic on a global supply chain network.     

Entropy/cross entropy-based group decision making under intuitionistic fuzzy environment

We study the group decision making problem under intuitionistic fuzzy environment. Based on entropy and cross entropy, we give two methods to determine the optimal weights of attributes, and develop two pairs of entropy and cross entropy measures for intuitionistic fuzzy values. Then, we discuss the properties of these measures and the relations between them and the existing ones. Furthermore, we introduce three new aggregation operators, which treat the membership and non-membership information fairly, to aggregate intuitionistic fuzzy information. Finally, several practical examples are presented to illustrate the developed methods.     

Soft computing approach to fault diagnosis of centrifugal pump

Fault detection and isolation in rotating machinery is very important from an industrial viewpoint as it can help in maintenance activities and significantly reduce the down-time of the machine, resulting in major cost savings. Traditional methods have been found to be not very accurate. Soft computing based methods are now being increasingly employed for the purpose. The proposed method is based on a genetic programming technique which is known as gene expression programming (GEP). GEP is somewhat a new member of the genetic programming family. The main objective of this paper is to compare the classification accuracy of the proposed evolutionary computing based method with other pattern classification approaches such as support vector machine (SVM), Wavelet-GEP, and proximal support vector machine (PSVM). For this purpose, six states viz., normal, bearing fault, impeller fault, seal fault, impeller and bearing fault together, cavitation are simulated on centrifugal pump. Decision tree algorithm is used to select the features. The results obtained using GEP is compared with the performance of Wavelet-GEP, support vector machine (SVM) and proximal support vector machine (PSVM) based classifiers. It is observed that both GEP and SVM equally outperform the other two classifiers (PSVM and Wavelet-GEP) considered in the present study.     

Sensitivity analysis for simulation-based decision making: Application to a hospital emergency service design

An increasing concern of decision makers when dealing with system design is preparation for a wide range of potentially uncertain operating conditions. This paper provides a novel multiobjective approach for simulation-driven decision making that accounts for not only the conventional average system performance indices, but also (i) upper-tail, or extreme, values of these indices, and (ii) measures of their sensitivity to uncertainty in model parameters. The proposed approach is applied to a hospital emergency department service design case study wherein different design alternatives are compared using total time-in-system performance metric under multiple uncertain operating conditions.     

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.     

数据挖掘在电子商务中的应用研究

本文主要介绍数据挖掘在电子商务中的应用,文章从数据挖掘的定义、数据挖掘的常用方法出发,阐述了数据挖掘在海量信息中提取有效信息的作用,特别是数据挖掘与电子商务的结合可以给人们生活带来便利,给企业带来新的利润空间以及为企业提供决策支持。常用的数据挖掘技术主要包括支持向量机、朴素贝叶斯、聚类、决策树、神经网络和关联规则等,最后介绍了数据挖掘在电子商务的4个主要应用方面,说明了数据挖掘存在的必要性。     

高校餐饮服务信息化综合解决方案

高校餐饮服务相比较于社会化餐饮服务具有其独特特性,在购买原材料完全遵循市场规则而销售定价不能完全市场化的限制下,还要面对窗口自选以及餐厅点餐两种销售模式并存的影响,以及伴随着扩招带来了多校区、多食堂、多窗口的状况,如何通过信息化手段提高其工作流程和效率,成为当前迫切需要。文中提出一种符合实际工作需要的信息化解决方案,对整个高校餐饮服务过程中所涉及的人、物、财进行综合管理,并形成决策,以最大化信息系统的效用,真正做到开源节流。     

近终型金属铸造模具制造工艺设计分析与应用

近终型制模技术，可以缩短制模周期、降低生产成本。本文介绍近终型技术在制模工艺实际中的应用概况。并举出实例，指出近终型制模技术可以提高生产效率，快捷地制造出各种复杂的零件/金属模具，该技术有着广阔的应用前景。     

超低硫X65管线钢中非金属夹杂物研究

对本钢超低硫X65管线钢中夹杂物的研究结果表明,LF精炼初期,钢中夹杂物主要是球形、多边形和大量簇状的Al2O3夹杂物,99.1%的夹杂物尺寸小于20μm。微合金化后,部分Al2O3夹杂物中出现TiO、SiO2、MnS等成分。钙处理后,夹杂物的平均直径达到8.58μm,大量夹杂物为含有微量MgO、SiO2或MnS等的2~50μm的球形mCaO.nAl2O3,部分为Al2O3、MnS、CaS或CaS-MnS。铸坯中夹杂物数量最少且尺寸最小,96.9%的夹杂物尺寸小于10μm,未发现大于50μm的夹杂物,平均直径为3.71μm。铸坯中大部分为球形的以mCaO.nAl2O3为主要成分的复合夹杂物,还有少量的Al2O3、MnS和CaS夹杂物等。     

逻辑表达式图的实现及其在集成电路故障 可测性中的应用

数字电路的可靠性有着至关重要的影响,测试是其重要保证,测试向量的自动生成(ATPG)在数字电路的测试中占有重要地位;逻辑表达式图(Boolean Expression Diagrams,BED)是用于逻辑函数与逻辑电路表达与运算一种数据结构,能够将逻辑电路在线性空间复杂度内表达,是二元判决图(Binary Decision Diagrams, BDD)在概念上的推广且保留着BDD的许多有用的性质。讨论了BED的性质与实现方法,并将BED用于逻辑电路呆滞型故障测试向量的自动生成中,基于BED的测试算法直接将原电路与故障电路做异或运算后用BED表达再化简或判断其可满足性,算法能充分使用逻辑代数的化简规则和利用电路与故障电路的相似性。实验结果表明,基于BED的测试方法具有较低的复杂度。