Detecting, Assessing and Monitoring Relevant Topics in Virtual Information Environments

The ability to assess the relevance of topics and related sources in information-rich environments is a key to success when scanning business environments. This paper introduces a hybrid system to support managerial information gathering. The system is made up of three components: (1) a hierarchical hyperbolic SOM for structuring the information environment and visualizing the intensity of news activity with respect to identified topics, (2) a spreading activation network for the selection of the most relevant information sources with respect to an already existing knowledge infrastructure, and (3) measures of interestingness for association rules as well as statistical testing facilitates the monitoring of already identified topics. Embedding the system by a framework describing three modes of human information seeking behavior endorses an active organization, exploration and selection of information that matches the needs of decision makers in all stages of the information gathering process. By applying our system in the domain of the hotel industry we demonstrate how typical information gathering tasks are supported. Moreover, we present an empirical study investigating the effectiveness and efficiency of the visualization framework of our system.     

Application of intelligent data management in resource allocation for effective operation of manufacturing systems

Resource allocation has been a critical issue in manufacturing. This paper presents an intelligent data management induced resource allocation system (RAS) which aims at providing effective and timely decision making for resource allocation. This sophisticated system is comprised of product materials, people, information, control and supporting function for the effectiveness in production. The said system incorporates a Database Management System (DBMS) and fuzzy logic to analyze data for intelligent decision making, and Radio Frequency Identification (RFID) for result verification. Numerical data from diverse sources are managed in the DBMS and used for resource allocation determination by using fuzzy logic. The output, representing the essential resources level for production, is then verified with reference to the resource utilization status captured by RFID. The effectiveness of the developed system is verified with a case study carried out in a Hong Kong-based garment manufacturing company. Results show that data gathering before resource allocation determination is more efficient with the use of developed system where the resource allocation decision parameters in the centralize database are effectively determined by using fuzzy logic. Decision makers such as production managers are allowed to determine resource allocation in a standardized approach in a more efficient way. The system also incorporates RFID with Artificial Intelligence techniques for result verification and knowledge refinement. Therefore, fuzzy logic results of resource allocation can be more responsive and adaptive to the actual production situation by refining the fuzzy rules with reference to the RFID-captured data.     

基于GIS的动态应急资源调度系统设计与实现*

为提高应急响应能力,利用实时的道路信息、救援状态信息和应急资源配置信息,设计了一个实时、动态的应急资源调度系统。在地理信息系统基础上,实现了利用实时信息动态生成应急资源调度方案。最终通过一个实例应用,结果证明了系统的实用价值,可以为应急资源救援提供科学的决策支持。     

Action rule discovery from incomplete data

Action rule is an implication rule that shows the expected change in a decision value of an object as a result of changes made to some of its conditional values. An example of an action rule is ‘credit card holders of young age are expected to keep their cards for an extended period of time if they receive a movie ticket once a year’. In this case, the decision value is the account status, and the condition value is whether the movie ticket is sent to the customer. The type of action that can be taken by the company is to send out movie tickets to young customers. The conventional action rule discovery algorithms build action rules from existing classification rules. This paper discusses an agglomerative strategy that generates the shortest action rules directly from a decision system. In particular, the algorithm can be used to discover rules from an incomplete decision system where attribute values are partially incomplete. As one of the testing domains for our research we take HEPAR system that was built through a collaboration between the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences and physicians at the Medical Center of Postgraduate Education in Warsaw, Poland. HEPAR was designed for gathering and processing clinical data on patients with liver disorders. Action rules will be used to construct the decision-support module for HEPAR.     

Information tradeoffs in model building: A network routing application

An integral part of the model-building process is the modeler's choice of how much information to gather and encode in the decision model. Obtaining more detailed and accurate information enables a more precise problem representation which, in turn, leads to more effective decision making. However, acquiring extensive and accurate information entails higher costs and delays. This paper uses a network routing decision context to illustrate the tradeoff between model precision and decision effectiveness, and explores a formal decision-theoretic approach to determine an appropriate model specification that balances information gathering costs and decision quality. We propose optimal and heuristic methods for generating good information search strategies, and report computational results based on random test problems. Our results highlight the importance of simultaneously considering information costs and decision payoffs for constructing a decision model to support routing decisions. The issues raised in this paper are especially significant for modeling dynamic, real-time decision contexts where delays induced by information gathering activities could have significant economic impact.     

武器装备远程测试保障系统研究

文章提出了适应武器装备综合保障发展方向的远程测试维修维护、远程技术支援的体系模型；结合网络中心战作战体系的构成形式和作战保障要求，综合利用异域、异构的各种保障信息、远程信息传输技术以及分布式远程故障诊断模式，提供了武器装备维修维护的远程信息获取手段，以及诊断知识自学习和海量数据挖掘等信息处理手段，实现了维修维护过程中的动态资源调度、远程协同保障和辅助维修决策处理；通过对验证原型实例的分析，远程测试保障系统的部署实施，能够降低武器装备的保障压力，缩短快速响应决策的时间，从而提高系统的综合保障能力。     

A Strategy of Dynamic Reasoning in Knowledge-Based System with Fuzzy Production Rules

Fuzzy production rules have been successfully applied to represent uncertainty in a knowledge-based system. The knowledge organized as a knowledge base is static. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a strategy to reflect the dynamic nature of a system when we make reasoning with a knowledge-based system.This paper proposes a strategy of dynamic reasoning that can be used to takes account the dynamic behavior of decision-making with the knowledge-based system consisted of fuzzy rules. A degree of match (DM) between actual input information and antecedent of a rule is represented by a value in interval [0, 1]. Weights of relative importance of attributes in a rule are obtained by the AHP (Analytic Hierarchy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with the Min operator, into a single DM for the rule. In this way, the importance of attributes of a rule, which can be changed from time to time, can be reflected to reasoning in knowledge-based system with fuzzy rules.With the proposed reasoning procedure, a decision maker can take his judgment on the given decision environment into a static knowledge base with fuzzy rules when he makes decision with the knowledge base. This procedure can be automated as a pre-processing system for fuzzy expert systems. Thereby the quality of decisions could be enhanced.     

Combining belief functions taking into consideration error in judgement

ABSTRACT

Dempster–Shafer (D–S) evidence theory is very efficient and widely used mathematical tool for uncertain and imprecise information fusion for decision making. D–S rule is criticised by many researchers as it gives illogical and counterintuitive results especially when the series of evidence provided by various experts are in a high degree of conflict. Various attempts have been made and several alternatives proposed to this rule. In this paper, a new alternative is proposed which considers the possibility of an error made by experts while providing evidence, calculates the error and incorporates in the revised masses. The validity and efficiency of the proposed approach have been demonstrated with numerous examples and the results are compared with already existing methods.

Highlights

• An alternative method is proposed to handle the conflicting evidence.

• An Error In Judgement while gathering evidence is considered and incorporated before combining evidence.

• The method is simple and gives better and reasonable results than other previous methods when evidence conflicts

     

A fuzzy expert database system

Fuzzy concepts always exist in much of human reasoning as well as decision making. This paper presents a fuzzy expert database system which is an integration of a fuzzy expert system building tool called SYSTEM Z-II and a database management system called Rdb/VMS. This system is able to extract fuzzy data and terms stored in a database and used in the fuzzy reasoning in an expert system. It can also retrieve information by fuzzy database-queries which are generated by the expert system automatically. Many expert systems in different domain areas such as decision making can be constructed. Sample applications are described to demonstrate the flexibility and power of this system. The fuzzy query language defined and used in the system can also be used independently as a fuzzy enquiry tool in database applications.     

钢铁企业集团多级成本管理系统模型研究*

从钢铁企业集团成本管理的特点和需求出发,将信息技术和现代管理技术相结合提出了一种多级成本管理系统的体系架构,它把企业集团看成各股份公司的各分厂或设备的集合体。在分厂或设备层次,分别对各分厂或设备实施作业成本管理,侧重于战术决策。在股份层次,对本公司各分厂的实施情况进行信息综合,支持股份的战略决策。在集团层次对各股份的信息进行综合分析决策,支持集团的战略决策。使用的基于多重资源分配的作业成本核算模型,从分配路径、统一的动因管理、统一的分配管理和与其他系统的集成进行了扩展,从而增加了模型的适用性。结合体系结构     

Optimal resource allocation for time-reservation systems

This paper studies the optimal resource allocation in time-reservation systems. Customers arrive at a service facility and receive service in two steps; in the first step information is gathered from the customer, which is then sent to a pool of computing resources, and in the second step the information is processed after which the customer leaves the system. A central decision maker has to decide when to reserve computing power from the pool of resources, such that the customer does not have to wait for the start of the second service step and that the processing capacity is not wasted due to the customer still being serviced at the first step. The decision maker simultaneously has to decide on how many processors to allocate for the second processing step such that reservation and holding costs are minimized. Since an exact analysis of the system is difficult, we decompose the system into two parts which are solved sequentially leading to nearly optimal solutions. We show via dynamic programming that the near-optimal number of processors follows a step function with as an extreme policy the bang-bang control. Moreover, we provide new fundamental insights in the dependence of the near-optimal policy on the distribution of the information gathering times. Numerical experiments demonstrate that the near-optimal policy closely matches the performance of the optimal policy of the original problem.     

Big Board: Teleconferencing Over Maps for Shared Situational Awareness

Collaborative technologies for information sharing are an invaluable resource for emergency managers to respond to and manage highly dynamic events such as natural disasters and other emergencies. However, many standard collaboration tools can be limited either because they provide passive presentation and dissemination of information, or because they are targeted towards highly specific usage scenarios that require considerable training to use the tools. We present a real-time gather and share system called “Big Board” which facilitates collaboration over maps. The Big Board is an open-source, web based, real time visual collaborative environment that runs on all modern web browsers and uses open-source web standards developed by the Open Geospatial Consortium (OGC) and WorldWideWeb Consortium (W3C). An evaluation of Big Board was conducted by school representatives in North Carolina for use in situational understanding for school closure decisions during winter weather events. The decision to close schools has major societal impacts and is one that is usually made based on how well a teenage driver could handle wintry precipitation on a road. Collecting information on the conditions of roads is especially critical, however gathering and sharing of this information within a county can be difficult. Participants in the study found the Big Board intuitive and useful for sharing real time information, such as road conditions and temperatures, leading up to and during a winter storm scenario. We have adapted the Big Board to manage risks and hazards during other types of emergencies such as tropical storm conditions.     

Different roles and mutual dependencies of data, information, and knowledge — An AI perspective on their integration

The unclear distinction between data, information, and knowledge has impaired their combination and utilization for the development of integrated systems. There is need for a unified definitional model of data, information, and knowledge based on their roles in computational and cognitive information processing. An attempt to clarify these basic notions is made, and a conceptual framework for integration is suggested by focusing on their different roles and frames of reference within a decision-making process. On this basis, ways of integrating the functionalities of databases, information systems and knowledge-based systems are discussed by taking a knowledge level perspective to the analysis and modeling of systems behaviour. Motivated by recent work in the area of case-based reasoning related to decision support systems, it is further shown that a specific problem solving episode, or case, may be viewed as data, information, or knowledge, depending on its role in decision making and learning from experience. An outline of a case-based system architecture is presented, and used to show that a focus on the retaining and reuse of past cases facilitates a gradual and evolutionary transition from an information system to a knowledge-based system.     

Autonomic self healing and recovery informed by environment knowledge

An important goal of autonomic computing is the development of computing systems that are capable of self healing with a minimum of human intervention. Typically, recovery from even a simple fault will require knowledge of the environment in which a computing system operates. To meet this need, we present an approach to self healing and recovery informed by environment knowledge that combines case based reasoning (CBR) and rule based reasoning. Specifically, CBR is used for fault diagnosis and rule based reasoning for fault remediation, recovery, and referral. We also show how automated information gathering from available sources in a computing system’s environment can increase problem solving efficiency and help to reduce the occurrence of service failures. Finally, we demonstrate the approach in an intelligent system for fault management in a local printer network.     

Extrapolation of fuzzy values from incomplete data bases

This paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory.     

Employing optimized combinations of one-class classifiers for automated currency validation

Automated currency validation requires a decision to be made regarding the authenticity of a banknote presented to the validation system. This decision often has to be made with little or no information regarding the characteristics of possible counterfeits as is the case for issues of new currency. A method for automated currency validation is presented which segments the whole banknote into different regions, builds individual classifiers on each region and then combines a small subset of the region specific classifiers to provide an overall decision. The segmentation and combination of region specific classifiers to provide optimized false positive and false negative rates is achieved by employing a genetic algorithm. Experiments based on high value notes of Sterling currency were carried out to assess the effectiveness of the proposed solution.     

基于智能主体的决策资源管理

随着Internet的广泛普及,人们可以随时随地获取自己想要的信息,然而海量信息却带来了一场新的知识危机,也就是说,人们被知识的海洋所淹没。知识管理技术正是解决这种知识危机的重要而有效的手段,是知识工程和信息系统中的重要研究内容。论文介绍了该技术在决策资源管理中的应用,提出了一个基于智能主体的决策支持系统的体系结构,并且详细描述了基于本体与RDF的决策资源的知识表示,最后用一个实例阐述了这种决策资源管理方法的实现过程。     

Advanced resource planning as a decision support module for ERP

The planning and decision support capabilities of the manufacturing planning and control system, which provides the core of any enterprise resource planning package, can be enhanced substantively by the inclusion of a decision support module as an add-on at the midterm planning level. This module, called advanced resource planning (ARP), provides a parameter-setting process, with the ultimate goal of yielding realistic information about production lead times for scheduling purposes, sales and marketing, strategic and operational decision making, and suppliers and customers. This article illustrates the ARP approach with reports from several real-life implementations by large industrial companies.     

A case-based method for service-oriented value chain and sustainable network design

PurposeThe purpose of this research is to present a case-based analytic method for a service-oriented value chain and a sustainable network design considering customer, environmental and social values. Enterprises can enhance competitive advantage by providing more values to all stakeholders in the network.Design/methodology/approachOur model employs a stylized database to identify successful cases of value chain application under similar company marketing conditions, illustrating potential value chains and sustainable networks as references. This work first identifies economic benefits, environmental friendliness and social contribution values based on prior studies. Next, a search engine which is developed based on the rough set theory will search and map similarities to find similar or parallel cases in the database. Finally, a visualized network mapping will be automatically generated to possible value chains.FindingsThis study applies a case-based methodology to assist enterprises in developing a service-oriented value chain design. For decision makers, this can reduce survey time and inspire innovative works based on previous successful experience. Besides, successful ideas from prior cases can be reused. In addition to customer values, this methodology incorporates environment and social values that may encourage a company to build their value chain in a more comprehensive and sustainable manner.Research implicationsThis is a pilot study which attempts to utilize computer-aided methodology to assist in service or value-related design. The pertinent existing solutions can be filtered from an array of cases to engage the advantages from both product-oriented and service-oriented companies. Finally, the visualized display of value network is formed to illustrate the results.Practical implicationsA customized service-oriented value chains which incorporates environment and social values can be designed according to different conditions. Also, this system engages the advantages from both product-oriented and service-oriented companies to build a more comprehensive value network. Apart from this, the system can be utilized as a benchmarking tool, and it could remind the decision makers to consider potential value from a more multifaceted perspective.Originality/valueThis is the first paper that applied a computer-aided method to design service-oriented value chains. This work also can serve as a decision support and benchmarking system because decision makers can develop different value networks according to various emphasized values. Finally, the visualized display of value network can improve the communication among stakeholders.