Basic onboard real-time advisory system for a duel situation of distant air fight

The structure of the knowledge base of an onboard real-time advisory system for distant air fight 1 × 1 in which current information on the external situation is used for activation of one of the problem subsituations chosen from the total set of these subsituations is presented. Based on the analysis of the subject domain of distant air fight 1 × 1, four problem subsituations are formed: the problem subsituation no. 1 “taking the tactically advantageous position”; the problem subsituation no. 2 “attack”, the problem subsituation no. 3 “defense with attack”, and the problem subsituation no. 4 “defense”. For each of these subsituations on the basis of virtual simulation of the proposed development of the air fight and the corresponding set of production rules, the recommendations to the crew on rational method of its resolution are developed. The results of mathematical simulation of the operation of the onboard real-time advisory system for distant air fight 1 × 1 in the problem subsituation no. 2 are presented.     

Computer simulation systems for development of knowledge bases of onboard online intelligent systems of system-generating core of anthropocentric object

Classification and pattern of computer simulation systems is presented; these systems provide improvement of knowledge bases of onboard intelligent systems at particular stages of their development. For intelligent information system (first global control level of anthropocentric object) “Situation awareness of the crew”, the presence of a man-operator in the simulation loop is mandatory, and for onboard online advisory expert systems for typical situations of functioning an anthropocentric object (second global level of object control), the simulation of the operator work by a special situation control block is admissible.     

A mathematical model of aircraft motion for knowledge bases of onboard online advisory expert systems

A model of the controlled motion of an aircraft as a point particle is described. The model is designated for real-time operation in knowledge bases of onboard advisory expert systems. The model implements a set of trajectory fragments which provides forming different trajectories of aircraft guidance to a target, antimissile, and free maneuvers. The model is parametrically adjusted to aerodynamic, mobile, and performance characteristics of a particular aircraft.     

Operational goal setting in anthropocentric objects from the viewpoint of the conceptual model called Etap: II. Operation modes of the on-board real-time advisory expert system and its dialog with the crew

The operational goal setting is the “first control phase” in anthropocentric objects. In terms of the Etap model, this is a change of the typical situation of the current session of the object’s operation. The structure of the operational goal setting is as follows: a priori information: (a) the given sequence of typical situations of the next anthropocentric object’s operation session, which ensures that the task of this session will be accomplished; (b) the set of typical situations describing the counteraction to external threats that can occur in the course of the execution of the session and the set of counteractions to onboard threats that frequently occur on board similar anthropocentric objects. The positive experience gained in using similar anthropocentric objects represented by knowledge matrices with the terms of the linguistic variable for each pair (typical session situation)–(typical situation of a counteraction to a threat), (typical situation of a counteraction to a threat)–(typical session situation). The precedent-based inference mechanism that makes it possible to select an appropriate typical situation and pass it to the object’s crew as the current operational goal. A classification of the threats, types of recommendations for the crew, and the crew’s dialogs with the onboard advisory operational goal setting expert system are described. This paper is a sequel to [1], and some concepts from that paper are repeated here to make it easier to understand.     

A shell of an onboard online advisory expert system for typical flight situation “Introduction of a group into an air fight”

The following knowledge base is presented: a hierarchical two-level knowledge base of onboard online advisory expert system for the subject area “Introduction of a group into an air fight”, in which mechanisms of inference mechanisms by precedent and multicriteria choice are used along with production rules. Examples of partial filling the knowledge base for the general problem “Patrol Escort of Strike Air Forces” are given.     

Knowledge-based system for telecontrol of anaerobic wastewater treatment plants

This paper describes the design and implementation of an intelligent real-time supervision system for the monitoring and control of wastewater treatment plants. The system presents a hybrid structure which integrates knowledge engineering techniques and methodologies (an expert system based on production rules embodying non-mathematical or semiquantitative knowledge of unit operation) and algorithmic process-related methods (data acquisition, signal preprocessing, calculation of plant operation parameters etc.). The fundamental design aspects consist of temporal information treatment, artifact detection and a client- server structure which allows the telesupervision of various plants by a central system.     

An expert system for real-time fault diagnosis of complex chemical processes

This paper presents the development and implementation of an expert system for real-time fault diagnosis of chemical processes. The expert system is applied as a real-time computer aided decision support system, providing operation suggestions to help field operators when abnormal situations occur. The knowledge base structure, representation of knowledge, and access to expertise are technically considered. Industrial applications to the fluid catalystic cracking process in refinery indicate that the expert system diagnoses abnormal events efficiently and promptly.     

Development of an expert system for optimizing natural gas pipeline operations

This paper presents an expert system as a decision support tool to optimize natural gas pipeline operations. A natural gas pipeline control system is a controlling system that involves many complicated operating processes. Since a dispatcher (who operates the system) might not be able to handle all of his or her tasks consistently, an expert system has been developed for optimizing the operations by providing consistent, fast and reliable decision support to the dispatcher. Consequently, inconsistency in the dispatcher's performance can be minimized. To build an expert system, the knowledge from an experienced dispatcher, who is familiar with the process in this controlling system is acquired and that knowledge has been implemented as rules in the knowledge base of the expert system. When this expert system has been validated by gas pipeline experts, it can help inexperienced dispatchers to operate the processes more effectively. The expert system is implemented on the real-time expert system shell G2 (trademark of Gensym Corp. of USA). The system also consists of a user interface that helps dispatchers visualize system conditions.     

面向问题分析与决策的专家系统

专家系统的根本目标在于为实际应用问题提供强有力的分析与决策能力。以人类通过长期实践活动总结的复杂问题分析与决策方法为指导思想,建立了以问题对象为核心、相关对象为问题主体、问题现象为表现形式、因果关系为问题变化驱动力、过程知识和原理知识为参考对象的面向问题分析与决策的专家系统。这种专家系统围绕应用领域中的问题构建知识库,而不是使用规则,所以得到的知识系统比较合理、清晰,不容易产生知识矛盾与冲突,有利于大型知识库的构建;同时,采用基于问题的推理,与人类的思维习惯相符合,可以大大提高推理效率;此外,开发这种专家     

RAPS: a rule-based language for specifying resource allocation andtime-tabling problems

A general language for specifying resource allocation and time-tabling problems is presented. The language is based on an expert system paradigm that was developed previously by the authors and that enables the solution of resource allocation problems by using experts' knowledge and heuristics. The language enables the specification of a problem in terms of resources, activities, allocation rules, and constraints, and thus provides a convenient knowledge acquisition tool. The language syntax is powerful and allows the specification of rules and constraints that are very difficult to formulate with traditional approaches, and it also supports the specification of various control and backtracking strategies. We constructed a generalized inference engine that runs compiled resource allocation problem specification language (RAPS) programs and provides all necessary control structures. This engine acts as an expert system shell and is called expert system for resource allocation (ESRA). The performance of RAPS combined with ESRA is demonstrated by analyzing its solution of a typical resource allocation problem     

Visual programming environment for hybrid expert systems

This paper proposes an architecture for hybrid expert system development which combines expert problem-solving functions and other conventional computational functions by visual programming technology. The visual programming technique is used both for task-specific knowledge representation and for procedural programming for connecting functional components. In knowledge representation, knowledge is visually represented in the form of decision tables and decision trees. In procedural visual programming, each functional object is displayed as a box-shaped icon with accessible ports which are connected by wires on the graphic editor. Based on the architecture, an expert system shell for the classification task, called HOLON/VP(DT), is incorporated in a visual programming system called HOLON/VP. This paper briefly describes the tool and its evaluation based on some application systems developed with the tool.     

ITONUS: Expert system for machining on a lathe

A microcomputer-based expert system for the diagnosis of lathe machining operations has been developed using the EXSYS shell on an IBM AT. Interviews with a journeyman machinist resulted in an initial knowledge base of rules containing basic concepts and relationships concerning set-up and control of lathe machining. The system provides the user with analysis and advice regarding the diagnosis and certain set-up aspects of common lathe operations, and has shown that it is feasible to elicit and mimic at least a portion of an expert machinist's knowledge and special skills.     

临近空间成像资源配置专家决策系统研究

针对临近空间成像资源配置的多目标组合优化特性,为了降低该问题的求解难度,迅速求解合理可行的临近空间成像资源配置方案,研究了融合决策支持模型的专家决策系统,建立了专家知识库、决策推理机以及规则管理模块,基于专家知识、决策支持模型,运用多级推理机制,其多级推理机制主要包括约束过滤、冲突过滤与综合评价决策,求解临近空间资源配置方案,实际运行结果表明,该系统能较好地解决临近空间资源配置问题.     

Mapping knowledge to rules for scheduling expert systems

Although the theoretical framework of expert systems has been well established, the process of developing a non-trivial expert system is still considered a difficult task. The main reason for this is that the nature of expert systems is knowledge-intensive. Also, it is usually difficult for domain experts to explain or communicate their expertise to the system professionals. Many methodologies have been proposed to overcome this domain knowledge representation problem. Most of them require the assistance of an expert system shell (tool). However, with a purpose of helping the system development in mind, most of them were not satisfactory. This research takes the experience of implementing a course scheduling expert system, and suggests two analysis methods to describe the characteristics of course scheduling knowledge. It is shown that these methods provide assistance on clarifying the complicated scheduling problem. Another favorable advantage of this method is its capability helping the transferring of domain knowledge to rules in the knowledge base.     

DIVA: Recognition of typical situations for turbine generator diagnosis

DIVA is an expert system for turbine generator diagnosis. Its aim is to help a plant operator interpret vibration evolution to diagnose developing faults. Interpretation of vibration evolution is primarily a recognition process which is achieved by a particular model of heuristic classification. DIVA tries to recognize the observed situation among a hierarchy of typical situations.The purpose of this paper is to present the model we used for heuristic classification, based on prototypes. Prototypes represent typical problem situations and may also be seen as experts with special knowledge of what to do in such situations. We argue that this model presents significant advantages to deal with complex problems such as vibration surveillance.     

Development of an Expert System for Selection of Dam Type on Alluvium Foundations

. A knowledge-based expert system was developed to aid in the selection of the type of dam. The dam type selector expert system (DTSA ES) was designed to determine the type of dam on the alluvium foundations. Detailed expert knowledge is required to estimate the type of dam and to develop an expert system. The DTSA ES utilizes rules of thumb used by an expert for determining the selection of the type of dam. The DTSA ES was developed using a shell program. The expert system was tested on several dam sites in order to validate the decision obtained. The use of this expert system, containing knowledge about the selection of dam type, can be helpful to students, potential owners or contractors in selecting dam types. The current prototype always needs additional parameters for more detailed analyses of new developments. However, the current DTSA ES is designed to include existing information about dam types.     

一个专家控制系统的Matlab程序实现

本文首先简述基于粗集方法的专家控制系统的基本构成、知识表达方式及学习推理方法,通过研究导师的知识与学习者的知识之间的依赖程度,提出了一个专家控制系统的生产过程中决策控制规律推理的方法,最后给出了利用Matlab实现该生产系统简化及决策控制规律推理的程序。     

Quantitative knowledge acquisition for expert systems

A common problem in the design of expert systems is the definition of rules from data obtained in system operation or simulation. Whilte it is relatively easy to collect data and to log the comments of human operators engaged in experiments, generalizing such information to a set of rules has not previously been a straightforward task. This paper presents a statistical method for generating rule bases from numerical data, motivated by an example based on aircraft navigation with multiple sensors. The specific objective is to design an expert system that selects a satisfactory suite of measurements from a dissimilar, redundant set, given an arbitrary navigation geometry and possible sensor failures. This paper describes the systematic development of a Navigation Sensor Management (NSM) Expert System from Kalman Filter covariance data. The development method invokes two statistical techniques: Analysis of Variance (ANOVA) and the ID3 algorithm. The ANOVA technique indicates whether variations of problem parameters give statistically different covariance results, and the ID3 algorithm identifies the relationships between the problem parameters using probabilistic knowledge extracted from a simulation example set. ANOVA results show that statistically different position accuracies are obtained when different navigation aids are used, the number of navigation aids is changed, the trajectory is varied, or the performance history is altered. By indicating that these four factors significantly affect the decision metric, an appropriate parameter framework was designed, and a simulation example base was created. The example base contained over 900 training examples from nearly 300 simulations. The ID3 algorithm was then applied to the example base, yielding classification “rules” in the form of decision trees. The NSM expert system consists of seventeen decision trees that predict the performance of a specified integrated navigation sensor configuration. The performance of these decision trees was assessed on two arbitrary trajectories, and the performance results are presented using a predictive metric. The test trajectories used to evaluate the system's performance show that the NSM Expert adapts to new situations and provides reasonable estimates of sensor configuration performance.