空间任务论证仿真系统中异类RTI连接技术研究

为使空间任务论证仿真系统具有可重用性和扩展性,将异类运行支撑环境(runtime infrastructure,RTI)连接技术引入其中,使其能够在不同任务的论证过程中使用已有的联邦成员.通过分析高层体系结构(high level architecture,HLA)在该系统中的应用关键技术,以及基于桥接盟员和异类RTI的概念,设计并实现了桥接软件以连接采用不同RTI建立的联邦成员,从而能够快速构建针对不同任务的空间任务论证仿真系统.对桥接软件的时间推进请求响应速度进行了测试,实验结果表明该桥接软件高效且可行.     

ARIANEXPERT: A knowledge based system to analyze ARIANE's mission data

The ARIANE launcher post mission analysis is done at ARIANESPACE. This activity is called the ‘level 0 post flight analysis’ (PFA) and is carried out after each launch by about 60 engineers who are working together under the leadership of ARIANESPACE.

The PFA is one of the most critical of ARIANE operations, for several reasons:

• - The launch rate (8 a year for ARIANE 4) leaves a very short time to carry out all the verification work. Moreover, the PFA is a mandatory step before authorizing the next launch.

• - The complexity of the ARIANE launcher results in a very high demand on the PFA engineers. Moreover, there are problems of availability of people with relevant expert knowledge (characterized by a substantial staff turn-over during the 10 year life duration of ARIANE 4) which could potentially result in errors or omissions.

It is very important to be able to take into account the experience of the preceding flights and to record the results and the knowledge accumulated for each launch.

• - The quality and the reliability of the PFA mainly depends on the accessibility of data and on the used methodology.

Because the PFA is still largely done manually, and does not benefit from improved methodologies and advanced technologies providing computerized support for data processing and diagnosis, ARIANESPACE has sponsored MATRA ESPACE for the development of a knowledge based system, called ARIANEXPERT, for supporting the PFA activity. This system combines AI techniques and numerical analysis techniques, together with advanced graphical capabilities.

A prototype has been delivered in April 1990 and has been used since 6 months by ARIANESPACE during real PFAs. Several lessons have been drawn from this operational experience and are described in this paper. They concern:

• - The utility and justification of the use of AI techniques mostly coming from the explanation capabilities and the stress put on capturing the expert knowledge.

• - The difficulties associated with the integration of such systems in the exploitation of ARIANE due to the introduction of very new tasks.

• - The user point of view which evolved from reluctant to convinced.

     

CALM — computer aided logistics management

Logistics functions directly support the principal operation. In the international petroleum industry they mainly are maintenance, materials and transport. CALM is a microcomputer system which integrates the arrangement of these functions. It operates at the plant level.

There are six CALM subsystems: 1) equipment control; 2) maintenance work control; 3) materials control; 4) transport control; 5) budgeting and costs and 6) management reporting.

CALM is a collection of relational data bases and application programs. Its modules are distributed and are under user control. Data bases are designed for three organizational levels: 1) local area networks on microcomputers at the user level (CALM ); 2) relational data bases on minicomputers at the plant level and 3) relational data bases on main frame computers at the corporate level. This is said to be a 3-level computer system. Data base design is optimized over the three levels.

System integration requires strict discipline over the design of identification codes (equipment, spare parts, job plans, job orders, failure reports, etc.). The paper suggests standard code formats which have proved to be successful in industry.

Besides CALM, integrated systems from four multinational oil companies are discussed. Design errors experienced in these projects are described. Specific design precautions are emphasized.     

基于VC++和Prolog语言混合编程的专家系统框架

为解决专家系统开发周期长的问题,提出并实现了用PROLOG与VC 混合编程方法开发专家系统框架的方案,用VC 实现专家系统框架的人机界面,用PROLOG语言构建知识库并实现推理过程.该框架具有较好的用户界面,用户只要输入或导入脚本编写的知识库、事实库和目标,就可以进行目标求解,因此简化了专家系统的开发过程.介绍了该专家系统框架的实现原理和设计思想,给出了导入导出模块、脚本语言语法检测模块和解释机制的实现方法.     

基于模糊理论的造纸专家系统--知识库的设计

基于模糊理论的造纸专家系统(PMES)的研究对于保障设备的稳定运行,提高产品质量具有重要的意义.本文探讨了模糊理论在知识表示方面如何和专家系统进行有效地结合,并对PMES的知识库进行设计.对知识库采用知识分级的方式,使知识的表达更具有层次性.通过各个知识表中的相互约束关系保证知识的一致性.     

IPSS: An approach towards automated decisions in CIM systems

IPSS (Industrial Problem Solving System), a specialized prototype Expert System development environment for operations planning. This hybrid system combines features of knowledge based systems as well as conventional procedural knowledge. IPSS architecture is presented and applications are discussed.     

协同专家系统的研究与实现

协同设计和协同仿真在产品设计中起着越来越重要的作用,对设计方案和仿真结果的评估也逐渐成为产品设计的一个重要环节.然而,依靠单领域进行设计评估往往考虑的内容不够全面,导致设计结果无法达到理想的状态.针对舰艇武器系统是涉及多领域的复杂系统这一特点,为满足多领域评估的要求,提出了舰艇武器系统协同评估专家系统的体系结构,研究了协同专家系统的知识库和推理技术,开发了原型系统.通过多个子专家系统协同来解决复杂问题,在实践中取得了理想的效果.     

An expert system for assembly based on Axiomatic Design principles

Increasing demands for lower cost of goods, due to international competition, has developed a new area of rationalization for increased productivity which can be achieved by applying new radical methods of production principles. Design for Assembly (DFA) is one of such methods that should be considered in the early design stage in order to cope with the increasing demands of lower cost, improved working environment, and higher wages. When Axiomatic Design (AD) is implemented with DFA in an intelligent way, a new area of design concepts would be realized. This study examines some elements of intelligent design systems to assess manufacturability of a product through the development of a knowledge based expert system for assembly (KBESA). The knowledge base has been acquired from DFA along with AD concepts with emphasis on the conceptual design stage where the structure of the product as a whole is considered. These concepts have been implemented in a case study illustrating its applicability.     

基于并行工程的软件可靠性专家系统的研究与实现

通过对专家系统工具的深入研究,将并行工程的思想引入了专家系统,提出了可靠性专家系统的基本框架,给出了基于并行工程的专家系统可靠性设计的方法,通过面向用户的设计和基于仿真的测试来实现。最终基于CLIPS实现了某潜艇设计评估专家系统的可靠性验证。     

A new expert system for learning management systems evaluation based on neutrosophic sets

There has been a sudden increase in the usage of Learning Management Systems applications to support learner's learning process in higher education. Many studies in learning management system evaluation are implemented under complete information, while the real environment has uncertainty aspects. As these systems were described by development organizations with uncertainty terms such as vague, imprecise, ambiguity and inconsistent, that is why traditional evaluation methods may not be effective. This paper suggests neutrosophic logic as a better option to simulate human thinking than fuzzy logic because unlike fuzzy logic, it is able to handle indeterminacy of information which expresses the percentage of unknown parameters. As previous studies suggested neutrosophic decision maker and neutrosophic expert systems as future work in ecommerce and e‐learning applications, this paper presents neutrosphic expert system for learning management systems evaluation. Information for building and validating the neutrosophic expert system is collected from five experts using surveys, and then analysis is done by using Fuzzytech 5.54d software. Finally, the comparison between fuzzy expert system and neutrosophic expert system results show that the neutrosophic logic is capable of representing uncertainty in human thinking for evaluating Learning Management Systems.     

烧结法氧化铝配料知识库编辑维护系统的实现

根据烧结法氧化铝生料浆配料机理和长期积累的专家经验知识,设计了一种适用于烧结法氧化铝配料的知识库编辑和维护系统,该系统从生产过程出发,将机理知识和群体专家知识统一为一种形式,通过产生式知识表示,对本系统的知识的特点进行了阐述,然后由知识的特点分别建立有关配料参数、状态、关系等字典,最后对系统的编辑和维护功能的实现进行了说明.实际使用效果表明,该知识库系统操作简单,编辑和维护方便.     

模糊控制技术在立式磨系统控制中的研究与应用

针对立式磨生产工况复杂多变,难用准确的数学模型来描述以及常规模糊控制器的控制效果不理想等问题,通过引入专家系统,提出了基于模糊推理的贴近度决策方法,修正控制回路的运行参数,改善模糊控制器的动态及稳态性能,增强控制系统的适应能力.实验结果表明该方法改善了负荷控制性能,提高了产品质量和磨机生产效率.     

Loss behavior in space priority queue with batch Markovian arrival process — discrete-time case

This paper applies matrix-analytic approach to the examination of the loss behavior of a space priority queue. In addition to the evaluation of the long-term high-priority and low-priority packet loss probabilities, we examine the bursty nature of packet losses by means of conditional statistics with respect to critical and non-critical periods that occur in an alternating manner. The critical period corresponds to having more than a certain number of packets in the buffer; non-critical corresponds to the opposite. Hence there is a threshold buffer level that splits the state space into two. By such a state-space decomposition, two hypothesized Markov chains are devised to describe the alternating renewal process. The distributions of various absorbing times in the two hypothesized Markov chains are derived to compute the average durations of the two periods and the conditional high-priority packet loss probability encountered during a critical period. These performance measures greatly assist the space priority mechanism for determining a proper threshold. The overall complexity of computing these performance measures is of the order O(K²m₁³m₂³), where K is the buffer capacity, and m₁ and m₂ are the numbers of phases of the underlying Markovian structures for the high-priority and low-priority packet arrival processes, respectively. Thus the results obtained are computationally tractable and numerical results show that, by choosing a proper threshold, a space priority queue not only can maintain the quality of service for the high-priority traffic but also can provide the near-optimum utilization of the capacity for the low-priority traffic.     

An artificial neural network based decision support system for energy efficient ship operations

Reducing fuel consumption of ships against volatile fuel prices and greenhouse gas emissions resulted from international shipping are the challenges that the industry faces today. The potential for fuel savings is possible for new builds, as well as for existing ships through increased energy efficiency measures; technical and operational respectively. The limitations of implementing technical measures increase the potential of operational measures for energy efficient ship operations. Ship owners and operators need to rationalise their energy use and produce energy efficient solutions. Reducing the speed of the ship is the most efficient method in terms of fuel economy and environmental impact. The aim of this paper is twofold: (i) predict ship fuel consumption for various operational conditions through an inexact method, Artificial Neural Network ANN; (ii) develop a decision support system (DSS) employing ANN-based fuel prediction model to be used on-board ships on a real time basis for energy efficient ship operations. The fuel prediction model uses operating data – ‘Noon Data’ – which provides information on a ship’s daily fuel consumption. The parameters considered for fuel prediction are ship speed, revolutions per minute (RPM), mean draft, trim, cargo quantity on board, wind and sea effects, in which output data of ANN is fuel consumption. The performance of the ANN is compared with multiple regression analysis (MR), a widely used surface fitting method, and its superiority is confirmed. The developed DSS is exemplified with two scenarios, and it can be concluded that it has a promising potential to provide strategic approach when ship operators have to make their decisions at an operational level considering both the economic and environmental aspects.     

Implementing a fuzzy expert system for ensuring information technology supply chain

In the business environment, information technology (IT) plays an important role for firms' performance. It provides information flow that makes the supply chain more robust and resilient without undermining its efficiency. Smart systems use artificial intelligence methods for solving problems and facilitating decision‐making through rule‐based deduction. Accordingly, these systems can present specialists' skills and simulate their thinking process. The primary goal of expert systems is to implement knowledge acquisition process by converting knowledge to wisdom. This process is vital for critical decision‐making regarding important issues such as determining necessities of a particular contract. Companies use professional liability insurance of the products and services to ensure the purchasers and prevent potential losses. Although this practice is highly prevalent, there is not any particular procedure for measuring necessities of contracts. The main purpose of this paper is to design a fuzzy expert system for measuring the necessities of professional contracts regarding insurance coverage and improve the supply chain management using IT. This system can measure and report these obligations, considering specifications of each project. Taking into perspective variety of professional services/products, we consider software as a type of professional contracts, extract its important indices and give it to the system as the input. After the necessary stages, the system produces a proper response and presents the generated response to the user. The software of this expert system is web based, and there are four operating layers in its architecture. We implemented this program in MS Visual Studio Framework with C#.NET programming language. Moreover, we implemented MS SQL‐Server Database Management.     

EXSHOF: An artificial intelligence approach to high-order filter synthesis

A two-tier expert-system-based synthesis of high-order filters is developed. Expert-system techniques have been used for choosing a particular biquad structure and for selection of the high-order filter structure as well. The data inputs will be either filter specifications or transfer functions and the output will be a detailed filter circuit with all its element values. EXSHOF ( pert System based ynthesis of igh rder ilter) is totally menu-driven and highly interactive. It assumes little knowledge of computers or filters from the user. The complete package is implemented in Turbo PASCAL and Turbo PROLOG languages.     

An expert system interface for an identification program

This paper describes an expert system interface, named (ihs), for the interactive data analysis and system identification program Idpac. The interface works as an intelligent help system. The system is completely noninvasive and uses the previous command history to understand what the user is doing and gives help according to this. This way of monitoring the user's activities is called the command spy strategy. Scripts are used for representing procedural knowledge, and production rules for diagnostic knowledge. The system has been implemented and a knowledge database handling system identification with the maximum-likelihood method has been developed. An example run with the system is included.     

LogGP in theory and practice – An in-depth analysis of modern interconnection networks and benchmarking methods for collective operations

Accurate measurement and modeling of network performance is important for predicting and optimizing the running time of high-performance computing applications. Although the LogP family of models has proven to be a valuable tool for assessing the communication performance of parallel architectures, non-intrusive LogP parameter assessment of real systems remains a difficult task. Based on an analysis of accuracy and contention properties of existing measurement methods, we develop a new low-overhead measurement method which also assesses protocol changes in the underlying transport layers. We use the gathered parameters to simulate LogGP models of collective operations and demonstrate the errors in common benchmarking methods for collective operations. The simulations provide new insight into the nature of collective algorithms and their pipelining properties. We show that the error of conventional benchmark methods can grow linearly with the system size.