Linking the witness simulation software to an expert system to represent a decision-making process

Expert systems, and artificial intelligence more generally, can provide a useful means for representing decision-making processes. By linking expert systems software to simulation software an effective means of including these decision-making processes in a simulation model can be achieved. This paper demonstrates how a commercial-off-the-shelf simulation package (Witness) can be linked to an expert systems package (XpertRule) through a Visual Basic interface. The methodology adopted could be used for models, and possibly software, other than those presented here.

An expert system for the development of a health and safety policy/risk assessment in the plastics industry

Health and safety policies may be regarded as the cornerstone for positive prevention of occupational accidents and diseases. The Health and Safety at Work, etc Act 1974 makes it a legal duty for employers to prepare and revise a written statement of a general policy with respect to the health and safety at work of employees as well as the organisation and arrangements for carrying out that policy. Despite their importance and the legal equipment to prepare them, health and safety policies have been found, in a large number of plastics processing companies (particularly small companies), to be poorly prepared, inadequately implemented and monitored. An important cause of these inadequacies is the lack of necessary health and safety knowledge and expertise to prepare, implement and monitor policies. One possible way of remedying this problem is to investigate the feasibility of using computers to develop expert system programs to simulate the health and safety (HS) experts' task of preparing the policies and assisting companies implement and monitor them. Such programs use artificial intelligence (AI) techniques to solve this sort of problems which are heuristic in nature and require symbolic reasoning. Expert systems have been used successfully in a variety of fields such as medicine and engineering. An important phase in the feasibility of development of such systems is the engineering of knowledge which consists of identifying the knowledge required, eliciting, structuring and representing it in an appropriate computer programming language.

Expert system design for cold form sections

The concept of an Expert System (ES) has been acknowledged as a very useful tool, but few studies have been carried out in its application to the design of cold rolled sections. This study involves primarily the use of an ES as a tool to improve the design process and to capture the draughtsman's knowledge. Its main purpose is to reduce substantially the time taken to produce a section drawing, thereby facilitating a speedy feedback to the customer. In order to communicate with a draughtsman, it is necessary to use sketches, symbolic representations and numerical data. This increases the complexity of programming an ES, as it is necessary to use a combination of languages so that decisions, calculations, graphical drawings and control of the system can be effected. A production system approach is used and a further step has been taken by introducing an Activator which is an autoexecute operation set up by the ES to operate an external program automatically. To speed up the absorption of new knowledge into the knowledge base, a new Learning System has been constructed. In addition to developing the ES, other software has been written to assist the design process. The section properties software has been introduced to improve the speed and consistency of calculating the section properties. A method of selecting or comparing the most appropriate section for a given specification is also implemented. Simple loading facilities have been introduced to guide the designer as to the loading capacity of the section. This research has concluded that the application of an ES is beneficial and with the activator approach, automated designing can be achieved. On average a complex drawing can be displayed on the screen in about 100 seconds, where over 95% of the initial section design time for repetitive or similar profile can be saved.

METEX: An expert system for metamorphic petrography

Classification of metamorphic rocks is normally carried out using a poorly defined, subjective classification scheme making this an area in which many undergraduate geologists experience difficulties. An expert system to assist in such classification is presented which is capable of classifying rocks and also giving further details about a particular rock type. A mixed knowledge representation is used with frame, semantic and production rule systems available. Classification in the domain requires that different facets of a rock be classified. To implement this, rocks are represented by 'context' frames with slots representing each facet. Slots are satisfied by calling a pre-defined ruleset to carry out the necessary inference. The inference is handled by an interpreter which uses a dependency graph representation for the propagation of evidence. Uncertainty is handled by the system using a combination of the MYCIN certainty factor system and the Dempster-Shafer range mechanism. This allows for positive and negative reasoning, with rules capable of representing necessity and sufficiency of evidence, whilst also allowing the implementation of an alpha-beta pruning algorithm to guide question selection during inference. The system also utilizes a semantic net type structure to allow the expert to encode simple relationships between terms enabling rules to be written with a sensible level of abstraction. Using frames to represent rock types where subclassification is possible allows the knowledge base to be built in a modular fashion with subclassification frames only defined once the higher level of classification is functioning. Rulesets can similarly be added in modular fashion with the individual rules being essentially declarative allowing for simple updating and maintenance. The knowledge base so far developed for metamorphic classification serves to demonstrate the performance of the interpreter design whilst also moving some way towards providing a useful assistant to the non-expert metamorphic petrologist. The system demonstrates the possibilities for a fully developed knowledge base to handle the classification of igneous, sedimentary and metamorphic rocks. The current knowledge base and interpreter have been evaluated by potential users and experts. The results of the evaluation show that the system performs to an acceptable level and should be of use as a tool for both undergraduates and researchers from outside the metamorphic petrography field. .

Fish farm effluent control and the development of an expert system

In recent years, freshwater fish farmers have come under increasing pressure from the Water Authorities to control the quality of their farm effluents. This project aimed to investigate methods of treating aquacultural effluent in an efficient and cost-effective manner, and to incorporate the knowledge gained into an Expert System which could then be used in an advice service to farmers. From the results of this research it was established that sedimentation and the use of low pollution diets are the only cost effective methods of controlling the quality of fish farm effluents. Settlement has been extensively investigated and it was found that the removal of suspended solids in a settlement pond is only likely to be effective if the inlet solids concentration is in excess of 8 mg/litre. The probability of good settlement can be enhanced by keeping the ratio of length/retention time (a form of mean fluid velocity) below 4.0 metres/minute. The removal of BOD requires inlet solids concentrations in excess of 20 mg/litre to be effective, and this is seldom attained on commercial fish farms. Settlement, generally, does not remove appreciable quantities of ammonia from effluents, but algae can absorb ammonia by nutrient uptake under certain conditions. The use of low pollution, high performance diets gives pollutant yields which are low when compared with published figures obtained by many previous workers. Two Expert Systems were constructed, both of which diagnose possible causes of poor effluent quality on fish farms and suggest solutions. The first system uses knowledge gained from a literature review and the second employs the knowledge obtained from this project's experimental work. Consent details for over 100 fish farms were obtained from the public registers kept by the Water Authorities. Large variations in policy from one Authority to the next were found. These data have been compiled in a computer file for ease of comparison.

The development of an expert system for the identification anodic coating process defects as a contribution to the dissemination of anodizing technology

Initially this thesis examines the various mechanisms by which technology is acquired within anodizing plants. In so doing the history of the evolution of anodizing technology is recorded, with particular reference to the growth of major markets and to the contribution of the marketing efforts of the aluminium industry. The business economics of various types of anodizing plants are analyzed. Consideration is also given to the impact of developments in anodizing technology on production economics and market growth. The economic costs associated with work rejected for process defects are considered. Recent changes in the industry have created conditions whereby information technology has a potentially important role to play in retaining existing knowledge. One such contribution is exemplified by the expert system which has been developed for the identification of anodizing process defects. Instead of using a "rule-based" expert system, a commercial neural networks program has been adapted for the task. The advantages of neural networks over 'rule-based' systems is that they are better suited to production problems, since the actual conditions prevailing when the defect was produced are often not known with certainty. In using the expert system, the user first identifies the process stage at which the defect probably occurred and is then directed to a file enabling the actual defects to be identified. After making this identification, the user can consult a database which gives a more detailed description of the defect, advises on remedial action and provides a bibliography of papers relating to the defect. The database uses a proprietary hypertext program, which also provides rapid cross-referencing to similar types of defect. Additionally, a graphics file can be accessed which (where appropriate) will display a graphic of the defect on screen. A total of 117 defects are included, together with 221 literature references, supplemented by 48 cross-reference hyperlinks. The main text of the thesis contains 179 literature references. (DX186565)

Self-organization of Functioning Process of Expert System with the Use of Subject Domain Ontology

Optimization of design, creation, functioning and accompaniment processes of expert system is the important problem of artificial intelligence theory and decisions making methods techniques. In this paper the approach to its solving with the use of technology, being based on methodology of systems analysis, ontology of subject domain, principles and methods of self-organisation, is offered. The aspects of such approach realization, being based on construction of accordance between the ontology hierarchical structure and sequence of questions in automated systems for examination, are expounded.

Expert System for Decision-Making Problem in Economics

An expert system (ES) is a class of computer programs developed by researchers in artificial intelligence. In essence, they are programs made up of a set of rules that analyze information about a specific class of problems, as well as provide analysis of the problems, and, depending upon their design, recommend a course of user action in order to implement corrections. ES are computerized tools designed to enhance the quality and availability of knowledge required by decision makers in a wide range of industries. Decision-making is important for the financial institutions involved due to the high level of risk associated with wrong decisions. The process of making decision is complex and unstructured. The existing models for decision-making do not capture the learned knowledge well enough. In this study, we analyze the beneficial aspects of using ES for decision- making process.

From client's dreams to achievable projects: An expert system for determining web site feasibility

This paper presents a web based expert system application that carries out an initial assessment of the feasibility of a web project. The system allows detection of inconsistency problems before design starts, and suggests correcting actions to solve them. The developed system presents important advantages not only for determining the feasibility of a web project but also by acting as a means of communication between the client company and the web development team, making the requirements specification clearer.

An analysis of users' reactions to an expert advisory system

Ignorance of user factors can be seen as one of the nontechnical issues contributing to expert system failure. An expert advisory system is built for nonexpert users; the users' acceptance is a very important factor for its successful implementation. If an expert advisory system satisfactorily represents the expertise in the domain, there still remains the question: "Will the end-users use the system?" This paper aims to address users' issues by analysing their reactions towards an expert advisory system called ADGAME, developed to help its users make better decisions in playing a competitive business game. Two experiments with ADGAME have been carried out. The research results show that, when the use of the expert advisory system is optional, there is considerable reluctance to use it, particularly amongst the "worst" potential users. Users also doubt the potential benefits in terms of improved learning and confidence in decisions made. Strangely, the one positive expectation that users had, that the system would save them time, proved not to be the case in practice; ADGAME appears to improve the users' effectiveness rather than their efficiency. © 1995.

Selection of intrusion detection system threshold bounds for effective sensor fusion

The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

A Multiple-Context Equality-Based Reasoning System

Expert systems are too slow. This work attacks that problem by speeding up a useful system component that remembers facts and tracks down simple consequences. The redesigned component can assimilate new facts more quickly because it uses a compact, grammar-based internal representation to deal with whole classes of equivalent expressions at once. It can support faster hypothetical reasoning because it remembers the consequences of several assumption sets at once. The new design is targeted for situations in which many of the stored facts are equalities. The deductive machinery considered here supplements stored premises with simple new conclusions. The stored premises include permanently asserted facts and temporarily adopted assumptions. The new conclusions are derived by substituting equals for equals and using the properties of the logical connectives AND, Or, and NOT. The deductive system provides supporting premises for its derived conclusions. Reasoning that involves quantifiers is beyond the scope of its limited and automatic operation. The expert system of which the reasoning system is a component is expected to be responsible for overall control of reasoning.