An expert system coupled with the gamma spectrum analysis system SAMPO has been developed for automating the qualitative identification of radionuclides as well as for determining the quantitative parameters of the spectrum components. The program is written in C-language and runs in various environments ranging from PCs to UNIX workstations. The expert system utilizes a complete gamma library with over 2600 nuclides and 80,000 lines, and a rule base of about fifty criteria including energies, relative peak intensities, genesis modes, half lives, parent-daughter relationships, etc. The rule base is furthermore extensible by the user. This is not an original contribution but a somewhat updated version of papers and reports previously published elsewhere. (author)
Framentec is the artificial intelligence subsidiary of FRAMATOME. It is involved in expert-system activities of Shells, developments, methodology and software for maintenance (Maintex) and consulting and methodology. Specific applications in the nuclear field are presented. The first is an expert system to assist in the piping support design prototype, the second is an expert system that assists an ultrasonic testing operator in determining the nature of a welding defect and the third is a welding machine diagnosis advisor. Maintex is a software tool to provide assistance in the repair of complex industrial equipment. (author)
Expert systems mimic the problem-solving activity of human experts in specialized domains by capturing and representing expert knowledge. Expert systems include a knowledge base, an inference engine that derives conclusions from the knowledge, and a user interface. Knowledge may be stored as if-then rules, orusing other formalisms such as frames and predicate logic. Uncertain knowledge may be represented using certainty factors, Bayesian networks, Dempster-Shafer belief functions, or fuzzy se...
Full Text Available Stroke always comes unexpected and the general public is not usually aware of its symptoms. Individuals who have had their first stroke with permanent damage could become an economic burden to their family and a social burden to the society due to their unproductive nature. Stroke could be prevented and its risk factors have been identified. Through a stroke prevention information system, the user could be made more aware of stroke risks and symptoms. An expert system would be able to direct and motivate users to keep themselves healthy therefore preventing first and recurrent strokes. The expert system is built using an inference engine that provides stroke risk level based on information provided by the user. Information collected are self measured blood pressure, cigarettes consumed, amount of physical activity and body mass index. Users are presented with suggested preventive tasks to reduce their stroke risk.
Parkinson, W. J.; Luger, G. F.; Bretz, R. E.
We have written three expert systems, using the CLIPS PC-based expert system shell. These three expert systems are rule based and are relatively small, with the largest containing slightly less than 200 rules. The first expert system is an expert assistant that was written to help users of the ASPEN computer code choose the proper thermodynamic package to use with their particular vapor-liquid equilibrium problem. The second expert system was designed to help petroleum engineers choose the proper enhanced oil recovery method to be used with a given reservoir. The effectiveness of each technique is highly dependent upon the reservoir conditions. The third expert system is a combination consultant and control system. This system was designed specifically for silicon carbide whisker growth. Silicon carbide whiskers are an extremely strong product used to make ceramic and metal composites. The manufacture of whiskers is a very complicated process. which to date. has defied a good mathematical model. The process was run by experts who had gained their expertise by trial and error. A system of rules was devised by these experts both for procedure setup and for the process control. In this paper we discuss the three problem areas of the design, development and evaluation of the CLIPS-based programs.
Mofreh Hogo; Khaled Fouad; Fouad Mousa,
Internet and expert systems have offered new ways of sharing and distributing knowledge, but there is a lack of researches in the area of web-based expert systems. This paper introduces a development of a web-based expert system for the regulations of civil service in the Kingdom of Saudi Arabia named as RCSES. It is the first time to develop such system (application of civil service regulations) as well the development of it using web-based approach. The proposed system considers 17 regulati...
Hossain, Mohammad Shahadat; Khalid, Md. Saifuddin; Akter, Shamima;
, development and application of an expert system to diagnose influenza under uncertainty. The recently developed generic belief rule-based inference methodology by using the evidential reasoning (RIMER) approach is employed to develop this expert system, termed as Belief Rule Based Expert System (BRBES). The...... RIMER approach can handle different types of uncertainties, both in knowledge representation, and in inference procedures. The knowledge-base of this system was constructed by using records of the real patient data along with in consultation with the Influenza specialists of Bangladesh. Practical case...
Jones, Robert E.; Liberman, Eugene M.
Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.
Full Text Available Internet and expert systems have offered new ways of sharing and distributing knowledge, but there is a lack of researches in the area of web-based expert systems. This paper introduces a development of a web-based expert system for the regulations of civil service in the Kingdom of Saudi Arabia named as RCSES. It is the first time to develop such system (application of civil service regulations as well the development of it using web-based approach. The proposed system considers 17 regulations of the civil service system. The different phases of developing the RCSES system are presented, as knowledge acquiring and selection, ontology and knowledge representations using XML format. XML-Rule-based knowledge sources and the inference mechanisms were implemented using ASP.net technique. An interactive tool for entering the ontology and knowledge base, and the inferencing was built. It gives the ability to use, modify, update, and extend the existing knowledge base in an easy way. The knowledge was validated by experts in the domain of civil service regulations, and the proposed RCSES was tested, verified, and validated by different technical users and the developers’ staff. The RCSES system is compared with other related web based expert systems, that comparison proved the goodness, usability, and high performance of RCSES.Keywords- Knowledge base; Ontology; RCSES; and Civil regulation;
The hybrid expert system SMOPLEX contains expert systems based on the algebra of uncertainties with memory and traditional simulations of chemical reactions based on functional equations. This expert system gives qualitative advices on the optimization of polymerization process
Full Text Available Expert system Nephrology is a computer program that exhibits, within a specific domain, a degree of expertise in problem solving that is comparable to that of a human expert. The knowledge base consistsof information about a particular problem area. This information is collected from domain experts (doctors. This system mainly contains two modules one is Information System and the other is Expert Advisory system. The Information System contains the static information about different diseases and drugs in the field of Nephrology. This information system helps the patients /users to know about the problems related to kidneys. The Nephrology Advisory system helps the Patients /users to get the required and suitable advice depending on their queries. This medical expert system is developedusing Java Server Pages (JSP as front-end and MYSQL database as Backend in such a way that all the activities are carried out in a user-friendly manner. Improved Ant Colony Optimization Algorithm (ACO along with RETE algorithm is also used for better results.
An expert system for traffic safety uses a "knowledge-base" for the interpretation of the "databases" in which accident data and the characteristics of roads and traffic are stored. Computerized procedures are developed for detection, diagnosis, and remedy. The procedures will be based on what is kn
Munaiseche, C. P. C.; Liando, O. E. S.
Usability usually defined as a point of human acceptance to a product or a system based on understands and right reaction to an interface. The performance of web application has been influence by the quality of the interface of that web to supporting information transfer process. Preferably, before the applications of expert systems were installed in the operational environment, these applications must be evaluated first by usability testing. This research aimed to measure the usability of the expert system application using tasks as interaction media. This study uses an expert system application to diagnose skin disease in human using questionnaire method which utilize the tasks as interaction media in measuring the usability. Certain tasks were executed by the participants in observing usability value of the application. The usability aspects observed were learnability, efficiency, memorability, errors, and satisfaction. Each questionnaire question represent aspects of usability. The results present the usability value for each aspect and the total average merit for all the five-usability aspect was 4.28, this indicated that the tested expert system application is in the range excellent for the usability level, so the application can be implemented as the operated system by user. The main contribution of the study is the research became the first step in using task model in the usability evaluation for the expert system application software.
As a branch of artificial intelligence, expert system has been revealed day after day in more and more engineering scopes since the successful applications of MYCIN in diagnosis and DENDRAL in the molecular structure of organic compounds etc.. But in the design scope of pressure vessel, as we know, only a few papers have so far been published with respect to the expert system. The necessity and feasibility of accompanying CAD-PV with expert system attracted more scholars to engage in. Although many countries, including China, have regularized the design standards or codes for pressure vessel, but of which no one can solve all of the problems concerning the various practical occasions and experiences. In general, the more domain knowledges a design engineer possesses of, the better decision will be made by him. By virtue of the expert system any less experienced engineer could make the optimum decision in design as well as a skilled senior engineer in addition to the application of design code. It is the due significance for developing high level expert system as an intelligence assistant in the plan option of CAD-PV. In this paper we attempt to introduce a specified software JACKPV used in the design procedure of jacketed pressure vessel as an intelligence front in CAD-PV. JACKPV consists of the function of expert system based on the personal computer IBM-PC/XT with the language PASCAL in its program. It was proved that an ordinary CAD software could be effectively improved while equipped with expert system. (orig.)
Dewa Gede Hendra Divayana
Full Text Available Digital library is a very interesting phenomenon in the world of libraries. In this era of globalization, the digital library is needed by students, faculty, and the community in the search for quick reference through internet access, so that students, faculty, and the community does not have to come directly to the library. Accessing collections of digital libraries can also be done anytime and anywhere. Digital Library development also occurred at Indonesia Technology University. That University offers a digital library based of expert system. The concept of digital library is utilizing science expert system in the process of cataloging and searching digital collections. By using this digital library based of expert system, users can search the collection, reading collection, and download the desired collection by online system. The digital library based of expert system at Indonesia Technology University is built using the PHP programming language, MySQL database as a data base management system, and developed the method of forward chaining and backward chaining as inference engine.
Full Text Available In view of the fact that supply strategies alone could not solve urban congestion, many cities around the globe have adopted Transport Demand Management (TDM strategies as part and partial of their congestion mitigation plan. TDM comprises several strategies and policies that aim to modifying travelers behaviour. TDM comprises strategies and policies that are different in nature which can be divided into several categories according to how they affect travelers’ behavior. Selecting and determining suitable TDM strategies for a particular congestion mitigation goal can be a complex task; thus requires expertise. In this regards, the effectiveness of a TDM strategy is primarily depending on whether its selection was appropriately examined prior to its field implementation. This paper presents the development of a Knowledge based expert advisory system for TDM. The process of organizing the available knowledge of TDM strategies, as well as the process leading to the selection of one or more strategy advice, is encoded in the knowledge based expert system shell developed for the purpose by using shell expert system Kappa-PC version 2.4 which was adopted object oriented and high resolution graphical user interface. The advice given from the working system was evaluated and validated by comparing the output of the system against the recommendations made by transportation professionals. The evaluations indicate favourable results for the system. The expert advisory system can be used as a decision support system as well as a teaching tool for junior transportation engineers, planners, private developers, and government officials.
Wu, J. G.; Ho, W. P. C.; Hu, Y. H.; Yun, D. Y. Y.; Parng, T. M.
In this paper, we present a model-based expert system for automatic digital systems design. The goal of digital systems design is to generate a workable and efficient design from high level specifications. The formalization of the design process is a necessity for building an efficient automatic CAD system. Our approach combines model-based, heuristic best-first search, and meta-planning techniques from AI to facilitate the design process. The design process is decomposed into three subprocesses. First, the high-level behavioral specifications are translated into sequences of primitive behavioral operations. Next, primitive operations are grouped to form intermediate-level behavioral functions. Finally, structural function modules are selected to implement these functions. Using model-based reasoning on the primitive behavioral operations level extends the solution space considered in design and provides more opportunity for minimization. Heuristic best-first search and meta-planning tech-niques control the decision-making in the latter two subprocesses to optimize the final design. They also facilitate system maintenance by separating design strategy from design knowledge.
Framatome makes wide use of expert systems, computer-assisted engineering, production management and personnel training. It has set up separate business units and subsidiaries and also participates in other companies which have the relevant expertise. Five examples of the products and services available in these are discussed. These are in the field of applied artificial intelligence and expert-systems, in integrated computer-aid design and engineering, structural analysis, computer-related products and services and document management systems. The structure of the companies involved and the work they are doing is discussed. (UK)
Babb, Stephen M.
The advent of space vehicles with their increased data requirements are reflected in the complexity of future telemetry systems. Space based operations with its immense operating costs will shift the burden of data processing and routine analysis from the space station to the Orbital Transfer Vehicle (OTV). A research and development project is described which addresses the real time onboard data processing tasks associated with a space based vehicle, specifically focusing on an implementation of an expert system.
Several expert system development tools are available for personal computers today. We have used one of the LISP-based high end tools for nearly two years in developing an expert system for identification of gamma sources. The system contains a radionuclide database of 2055 nuclides and 48000 gamma transitions with a knowledge base of about sixty rules. This application combines a LISP-based inference engine with database management and relatively heavy numerical calculations performed using C-language. The most important feature needed has been the possibility to use LISP and C together with the more advanced object oriented features of the development tool. Main difficulties have been long response times and the big amount (10-16 MB) of computer memory required
Full Text Available This paper presents the method for the creation of an expert knowledge base of a military object, for example a radar system. Such a knowldge base can be widely used to support the process of the maintenance of a complex technical object. The first step is a maintenance evaluation of the object. During this kind of analysis, it is necessary to perform the grouping and classification of the functional elements of the object.It is realised using the functional scheme of the object presented. Further, diagnostic information is combined with specialised experts' knowledge and transformed it into a set of servicing information. The participation of experts in the process of expert knowledge base preparation is significant. The purpose is to capture information that will be a fundamental for the design of a maintenance system dedicated to the particulartechnical object. The methods proposed were verified with appropriate examples, in which the set of specialised diagnostic information of the object was determined.Defence Science Journal, 2010, 60(5, pp.531-540, DOI:http://dx.doi.org/10.14429/dsj.60.84
Very often changes in the mechanical condition of the rotating machinery can be observed as changes in its vibration. This paper presents an expert system for vibration-based diagnosis of rotating machines by describing the architecture of the developed prototype system. The importance of modelling the problem solving knowledge as well as the domain knowledge is emphasized by presenting the knowledge in several levels
Shupeng Zhao; Miao Tian; Shifang Zhang; Jiuxi Li; Lijuan Du; Ye Wang
Engine fault has a high rate in the car. Considering about the distinguishing feature of the engine, Engine Diagnosis Expert System was investigated based on Diagnosis Tree module, Fuzzy Neural Network module, and commix reasoning module. It was researched including Knowledge base and Reasoning machine, and so on. In Diagnosis Tree module, the origin problem was searched in right method. In which module distinguishing rate and low error and least cost was the aim. By means of synthesize judge...
Sullivan, Gerald A.
Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up
Kahn, M. G.; Steib, S. A.; Fraser, V J; Dunagan, W C
Hospital-acquired infections represent a significant cause of prolonged inpatient days and additional hospital charges. We describe an expert system, called GERMWATCHER, which applies the Centers for Disease Control's National Nosocomial Infection Surveillance culture-based criteria for detecting nosocomial infections. GERMWATCHER has been deployed at Barnes Hospital, a large tertiary-care teaching hospital, since February 1993. We describe the Barnes Hospital infection control environment, t...
Chinniah, P.; Dr. S.Muttan
Medical diagnosis process involves many levels and considerable amount of time and money are invariably spent for the first level of diagnosis usually made by the physician for all the patients every time. Hence there is a need for a computer based system which not only asks relevant questions to the patients but also aids the physician by giving a set of possible diseases from the symptoms obtained using logic at inference. In this work, an ICD10 based Medical Expert System that provides adv...
NI Zhi-wei; JIA Rui-yu
On the basis of data mining and neural network, this paper proposes a general framework of the neural network expert system and discusses the key techniques in this kind of system. We apply these ideas on agricultural expert system to find some unknown useful knowledge and get some satisfactory results.
Medical diagnosis process involves many levels and considerable amount of time and money are invariably spent for the first level of diagnosis usually made by the physician for all the patients every time. Hence there is a need for a computer based system which not only asks relevant questions to the patients but also aids the physician by giving a set of possible diseases from the symptoms obtained using logic at inference. In this work, an ICD10 based Medical Expert System that provides advice, information and recommendation to the physician using fuzzy temporal logic. The knowledge base used in this system consists of facts of symptoms and rules on diseases. It also provides fuzzy severity scale and weight factor for symptom and disease and can vary with respect to time. The system generates the possible disease conditions based on modified Euclidean metric using Elders algorithm for effective clustering. The minimum similarity value is used as the decision parameter to identify a disease.
Full Text Available Engine fault has a high rate in the car. Considering about the distinguishing feature of the engine, Engine Diagnosis Expert System was investigated based on Diagnosis Tree module, Fuzzy Neural Network module, and commix reasoning module. It was researched including Knowledge base and Reasoning machine, and so on. In Diagnosis Tree module, the origin problem was searched in right method. In which module distinguishing rate and low error and least cost was the aim. By means of synthesize judge and fuzzy relation reasoning to get fault origin from symptom, fuzzy synthesize reasoning diagnosis module was researched. Expert knowledge included failure symptom, engine system failure and engine part failure. In the system, Self-diagnosis method and general instruments method worked together, complex failure diagnosis became efficient. The system was intelligent, which was combined by fuzzy logic reasoning and the traditional neural network system. And it became more convenience for failure origin searching, because of utilizing the three methods. The system fuzzy neural networks were combined with fuzzy reasoning and traditional neural networks. Fuzzy neural network failure diagnosis module of system, as a important model was applied to engine diagnosis, with more advantages such as higher efficiency of searching and higher self-learning ability, which was compared with the traditional BP network
This paper presents the method for the creation of an expert knowledge base of a military object, for example a radar system. Such a knowldge base can be widely used to support the process of the maintenance of a complex technical object. The first step is a maintenance evaluation of the object. During this kind of analysis, it is necessary to perform the grouping and classification of the functional elements of the object.It is realised using the functional scheme of the object presented. Fu...
Prasad Babu M.S
Full Text Available Tomato is now the most widely grown vegetable crop in World. It is grown throughout the world in farm gardens, small home-gardens, and by market gardeners for fresh consumption as well as for processingpurposes. This Tomato crop expert advisory system is aimed at a collaborative venture with eminent Agriculture Scientist and Experts in the area of Tomato Plantation with an excellent team of computer Engineers, programmers and designers. This Expert System contains two main parts one is Tomato Information System and the other is Tomato Crop Expert System where in Information system, the user can get all the static information about different species, Diseases,Symptoms, chemical controls, Preventions, Pests, Virus of Tomato fruits and plants. In Advisory System, the user is having aninteraction with the expert system online; the user has to answer the questions asked by the Expert System. Depends on the response by the user the expert system decides the disease and displays its control measure of disease. This Tomato Crop Information Expert System deals with different varieties of Tomato Crop, Identification of various diseases generally occurs to tomato crop based on the symptoms.This Rule based Expert System validates the symptoms of the tomato crop using the techniques of ID3 Algorithm and some optimization algorithms. This is a Web based Expert System with java as the front end and SQL as the backend.
Tseng, Kevin C; Wu, Chia-Chuan
This paper presents an expert diagnosis system based on cloud computing. It classifies a user's fitness level based on supervised machine learning techniques. This system is able to learn and make customized diagnoses according to the user's physiological data, such as age, gender, and body mass index (BMI). In addition, an elastic algorithm based on Poisson distribution is presented to allocate computation resources dynamically. It predicts the required resources in the future according to the exponential moving average of past observations. The experimental results show that Naïve Bayes is the best classifier with the highest accuracy (90.8%) and that the elastic algorithm is able to capture tightly the trend of requests generated from the Internet and thus assign corresponding computation resources to ensure the quality of service. PMID:24723842
This paper presents the results of the second phase of a three-phase Severe Accident Management expert system program underway. The primary objectives of the second phase were to develop and demonstrate four capabilities of neural networks with respect to nuclear power plant severe accident monitoring and prediction. A second objective of the program was to develop an interactive graphical user interface which presented the system's information in an easily accessible and straightforward manner to the user. This paper describes the technical and regulatory foundation upon which the expert system is based and provides a background on the development of a new severe accident management tool. This tool provides data to assist in; (1) planning and developing priorities for recovery actions, (2) evaluating recovery action feasibility, (3) identifying recovery action options, and (4) assessing the timing and possible effects of potential recovery strategies. These performance characteristics represent the goals identified for the Severe Accident Management Strategies Online Network (SAMSON) which is currently under development. 4 refs, 1 fig., 1 tab
The purpose of this article is to introduce readers to the basic principles of rule-based expert systems. Four topics are discussed in subsequent sections: (1) Definition; (2) Structure of an expert system; (3) State of the art and (4) Impact and future research. (orig.)
Full Text Available Medical diagnosis process involves many levels and considerable amount of time and money are invariably spent for the first level of diagnosis usually made by the physician for all the patients every time. Hence there is a need for a computer based system which not only asks relevant questions to the patients but also aids the physician by giving a set of possible diseases from the symptoms obtained using logic at inference. In this work, an ICD10 based Medical Expert System that provides advice, information and recommendation to the physician using fuzzy temporal logic. The knowledge base used in this system consists of facts of symptoms and rules on diseases. It also provides fuzzy severity scale and weight factor for symptom and disease and can vary with respect to time. The system generates the possible disease conditions based on modified Euclidean metric using Elder’s algorithm for effective clustering. The minimum similarity value is used as the decision parameter to identify a disease. Keywords -Fuzzy clustering, symptoms, fuzzy severity scale, weight factor, Minkowski distance, ICD, WHO, Rules Base, TSQL
Rajaram, N. S.
One of the principal objectives of the NASA AgRISTARS program is the inventory of global crop resources using remotely sensed data gathered by Land Satellites (LANDSAT). A central problem in any such crop inventory procedure is the interpretation of LANDSAT images and identification of parts of each image which are covered by a particular crop of interest. This task of labeling is largely a manual one done by trained human analysts and consequently presents obstacles to the development of totally automated crop inventory systems. However, development in knowledge engineering as well as widespread availability of inexpensive hardware and software for artificial intelligence work offers possibilities for developing expert systems for labeling of crops. Such a knowledge based approach to labeling is presented.
Bardina, Jorge E.; Thirumalainambi, Rajkumar
The simulation and modeling of launch operations is based on a representation of the organization of the operations suitable to experiment of the physical, procedural, software, hardware and psychological aspects of space flight operations. The virtual test bed consists of a weather expert system to advice on the effect of weather to the launch operations. It also simulates toxic gas dispersion model, and the risk impact on human health. Since all modeling and simulation is based on the internet, it could reduce the cost of operations of launch and range safety by conducting extensive research before a particular launch. Each model has an independent decision making module to derive the best decision for launch.
As part of its evaluation of new technologies, the Artificial Intelligence Section of the Mission Planning and Analysis Div. at NASA-Johnson has made timing tests of several expert system building tools. Among the production systems tested were Automated Reasoning Tool, several versions of OPS5, and CLIPS (C Language Integrated Production System), an expert system builder developed by the AI section. Also included in the test were a Zetalisp version of the benchmark along with four versions of the benchmark written in Knowledge Engineering Environment, an object oriented, frame based expert system tool. The benchmarks used for testing are studied.
Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and...
Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith
Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.
Tobias, L.; Scoggins, J. L.
A prototype expert system was developed for the time scheduling of aircraft into the terminal area. The three functions of the air traffic control schedule advisor are as follows: first, for each new arrival, it develops an admissible flight plan for that aircraft. Second, as the aircraft progresses through the terminal area, it monitors deviations from the flight plan and provides advisories to return the aircraft to its assigned schedule. Third, if major disruptions such as missed approaches occur, it develops a revised plan. The advisor is operational on a Symbolics 3600, and is programed in MRS (a logic programming language), Lisp, and FORTRAN.
Abdel Nasser H. Zaied
Full Text Available Information Systems (IS are increasingly becoming regarded as crucial to an organization's success. Information Systems Development Methodologies (ISDMs are used by organizations to structure the information system development process. ISDMs are essential for structuring project participants’ thinking and actions; therefore ISDMs play an important role to achieve successful projects. There are different ISDMs and no methodology can claim that it can be applied to any organization. The problem facing decision makers is how to select an appropriate development methodology that may increase the probability of system success. This paper takes this issue into account when study ISDMs and provides a Rule-based Expert System as a tool for selecting appropriate ISDMs. The proposed expert system consists of three main phases to automate the process of selecting ISDMs.Three approaches were used to test the proposed expert system. Face validation through six professors and six IS professionals, predictive validation through twenty four experts and blind validation through nine employees working in IT field.The results show that the proposed system was found to be run without any errors, offered a friendly user interface and its suggestions matching user expectations with 95.8%. It also can help project managers, systems' engineers, systems' developers, consultants, and planners in the process of selecting the suitable ISDM. Finally, the results show that the proposed Rule-based Expert System can facilities the selection process especially for new users and non-specialist in Information System field.
Mohammad Hossein Fazel Zarandi
Full Text Available A fuzzy rule-based expert system is developed for evaluating intellectual capital. A fuzzy linguistic approach assists managers to understand and evaluate the level of each intellectual capital item. The proposed fuzzy rule-based expert system applies fuzzy linguistic variables to express the level of qualitative evaluation and criteria of experts. Feasibility of the proposed model is demonstrated by the result of intellectual capital performance evaluation for a sample company.
Full Text Available In this study, the knowledge-based expert system approach was used to design a programmer using shell expert system of KAPPA PC Version 2.4 that is object oriented and displaying higher graphic resolutions. The flexible pavement design based on the accumulation of knowledge from several experts, books and journals results in a modular approach. Normally, the process of flexible pavement design is done by experts. The process was computerized and apply artificial intelligent that is a new technology in providing a system that can design and give the suggestion for user to choices the best and economy of the thickness of pavement layers. The expert system was tested using several design calculation samples. From the test, the success is 100% for pavement design. The expert system has revealed satisfactorily findings in a faster layers design.
In order to study intelligent fault diagnosis methods based on fuzzy neural network (NN) expert systemand build up intelligent fault diagnosis for a type of mis-sile weapon system, the concrete implementation of a fuzzyNN fault diagnosis expert system is given in this paper. Based on thorough research of knowledge presentation, theintelligent fault diagnosis system is implemented with artificial intelligence for a large-scale missile weapon equipment.The method is an effective way to perform fuzzy fault diagnosis. Moreover, it provides a new way of the fault diagnosisfor large-scale missile weapon equipment.
Liberman, Eugene M.; Jones, Robert E.
Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.
A brief exposition of the nature and functions of expert systems (knowledge based systems) and some remarks upon the way in which they resemble, but fall far short of, the very largely intuitive action of the human brain are given. The remainder of the article consists of summaries of the work being done in this field by organisations in Italy, namely: ISPRA; Delphi Electronic Design Systems, VIAREGGIO; SPL Italia SPA, (VA), Milan; Italservice Srl, Milan; and Artificial Intelligence Software, Rovigo.
Full Text Available Citrus fruits have a prominent place among popular and exclusively grown tropical and sub-tropical fruits. Their nature ,multifold nutritional and medicinal values have made them so important. Sweet Orange Crop expert advisory system is aimed at a collaborative venture with eminent Agriculture Scientist and Experts in the area of Sweet Orange Plantation with an excellent team of computer Engineers, Programmers and designers. This Expert System contains two main parts one is Sweet Orange Information System and the other is Sweet Orange Crop Expert System where information system, the user can get all the static information about different species, Diseases, Symptoms, chemical controls, Preventions, Pests, Virus of Sweet Orange fruits and plants. In Advisory System , the user is having an interaction with the expert system online; the user has to answer the questions asked by the Expert System. Depends on the response by the user the expert system decides the disease and displays its control measureof disease. This Sweet Orange Crop Information Expert System deals with different varieties of Sweet Crop, Identification of various diseases generally occurs to Sweet Orange crop based on the symptoms.
The adoption of expert systems mainly as operator supporting systems is becoming increasingly popular as the control algorithms of system become more and more sophisticated and complicated. As a result of this popularity, a large number of expert systems are developed. The nature of expert systems, however, requires that they be verified and validated carefully and that detailed methodologies for their development be devised. Therefore, it is widely noted that assuring the reliability of expert systems is very important, especially in nuclear industry, and it is also recognized that the process of verification and validation is an essential part of reliability assurance for these systems. Research and practices have produced numerous methods for expert system verification and validation (V and V) that suggest traditional software and system approaches to V and V. However, many approaches and methods for expert system V and V are partial, unreliable, and not uniform. The purpose of this paper is to present a new approach to expert system V and V, based on Petri nets, providing a uniform model. We devise and suggest an automated tool, called COKEP (Checker Of Knowledge base using Extended Petri net), for checking incorrectness, inconsistency, and incompleteness in a knowledge base. We also suggest heuristic analysis for validation process to show that the reasoning path is correct
Dijkstra, JJ; Liebrand, WBG; Timminga, E; Liebrand, Wim B.G.
Expert system advice is not always evaluated by examining its contents. Users can be persuaded by expert system advice because they have certain beliefs about advice given by a computer. The experiment in this paper shows that subjects (n = 84) thought that, given the same argumentation, expert syst
Rogers, Steven K.; Kabrisky, Matthew; Anderson, Steven; Mills, James P.
This paper describes a knowledge-based expert system that uses return features, provided by image analysts, to identify an object as a specific instance or class of object, such as a tank or truck. Partial feature sets allow the expert system to classify occluded and unfamiliar or falsified object data returns to the most likely class with a specified reasoning path. The rule based system was developed using the Prolog version of Ml.
ShunxiangWu; WentingHuang; XiaoshengWang; JiandeGu; MaoqingLi; ShifengLiu
This paper applies the relevant principles and methods of SQL database and Expert System, trying to research the methods and techniques of combining them and design a template of production expert system that is based on SQL database and drived by the database so as to simplify the structure of the knowledge base carried by database, generating the system more conveniently and operating it more effectively.
The computer code system which can evaluate the mass balance and cycle cost in nuclear fuel cycle has been developing a PNC using an artificial intelligence technique. This system is composed of the expert system, data base and analysis codes. The expert system is the most important one in the system and the content of the expert system is explained in this paper. The expert system has the three functions. The first is the function of understanding the meaning of user's questions by natural language, the second is the function of selecting the best way to solve the problem given by the user using the knowledge which is already installed in the system, and the last is the function of answering the questions. The knowledge of the experts installed in the expert system is represented by the frame-type rules. Therefore, the knowledge will be simply added to the system, and consequently the system will be easily extended. (author)
The ALICE experiment at CERN employs a number of human operators (shifters), who have to make sure that the experiment is always in a state compatible with taking Physics data. Given the complexity of the system and the myriad of errors that can arise, this is not always a trivial task. The aim of this paper is to describe an expert system that is capable of assisting human shifters in the ALICE control room. The system diagnoses potential issues and attempts to make smart recommendations for troubleshooting. At its core, a Prolog engine infers whether a Physics or a technical run can be started based on the current state of the underlying sub-systems. A separate C++ component queries certain SMI objects and stores their state as facts in a Prolog knowledge base. By mining the data stored in dierent system logs, the expert system can also diagnose errors arising during a run. Currently the system is used by the on-call experts for faster response times, but we expect it to be adopted as a standard tool by reg...
An expert system for prediction the impact of nitrogen fertilizer on groundwater pollution potential was established by using CLIPS (NASA's Jonson Space Centre). The knowledge base could be extracted from FAO reports, ministry of agriculture and rural development Malaysia report, established literature and domain expert for preparing an expert system skeleton. An expert system was used to correlate the availability of nitrogen fertilizer with the vulnerability of groundwater to pollution in Peninsula Malaysia and to identify potential groundwater quality problems. An n-fertilizer groundwater pollution potential index produced b using the vulnerability of groundwater to pollution yields a more accurate screening toll for identifying potential pollution problems than by considering vulnerability alone. An expert system can predict the groundwater pollution potential under several conditions of agricultural activities and existing environments. (authors)
Bo, Ma; Zhi-nong, Jiang; Zhong-qing, Wei
The operating mechanism of expert systems widely used in fault diagnosis is to formulate a set of diagnostic rules, according to the mechanism and symptoms of faults, in order to instruct the fault diagnosis or directly give diagnostic results. In practice, due to differences existing in such aspects as production technology, drivers, etc., a certain fault may derive from different causes, which will lead to a lower diagnostic accuracy of expert systems. Besides, a variety of expert systems now available have a dual problem of low generality and low expandability, of which the former can lead to the repeated development of expert systems for different machines, while the latter restricts users from expanding the system. Aimed at these problems, a type of task-based software architecture of expert system is proposed in this paper, which permits a specific optimization based on a set of common rules, and allows users to add or modify rules on a man-machine dialog so as to keep on absorbing and improving the expert knowledge. Finally, the integration of the expert system with the condition monitoring system to implement the automatic and semi-automatic diagnosis is introduced.
The operating mechanism of expert systems widely used in fault diagnosis is to formulate a set of diagnostic rules, according to the mechanism and symptoms of faults, in order to instruct the fault diagnosis or directly give diagnostic results. In practice, due to differences existing in such aspects as production technology, drivers, etc., a certain fault may derive from different causes, which will lead to a lower diagnostic accuracy of expert systems. Besides, a variety of expert systems now available have a dual problem of low generality and low expandability, of which the former can lead to the repeated development of expert systems for different machines, while the latter restricts users from expanding the system. Aimed at these problems, a type of task-based software architecture of expert system is proposed in this paper, which permits a specific optimization based on a set of common rules, and allows users to add or modify rules on a man-machine dialog so as to keep on absorbing and improving the expert knowledge. Finally, the integration of the expert system with the condition monitoring system to implement the automatic and semi-automatic diagnosis is introduced.
Verification is a necessary work in developing a reliable expert system. Verification is a process aimed at demonstrating whether a system meets it's specified requirements. As expert systems are used in various applications, the knowledge base verification of systems takes an important position. The conventional Petri net approach that has been studied recently in order to verify the knowledge base is found that it is inadequate to verify the knowledge base of large and complex system, such as alarm processing system of nuclear power plant. Thus, we propose an improved method that models the knowledge base as enhanced colored Petri net. In this study, we analyze the reachability and the error characteristics of the knowledge base. Generally, verification process requires computational support by automated tools. For this reason, this study developed a tool for knowledge base verification based on Design/CPN, which is a tool for editing, modeling, and simulating Colored Petri net. This tool uses Enhanced Colored Petri net as a modeling method. By applying this tool to the knowledge base of nuclear power plant, it is noticed that it can successfully check most of the anomalies that can occur in a knowledge base
YANG BingRu; SONG Wei; XU ZhangYan
Knowledge acquisition is the bottleneck of expert system. To solve this problem, KD (D&K), which is a comprehensive knowledge discovery process model cooperating both database and knowledge base, and related technology are proposed. Then based on KD (D&K) and related technology, the new construction of Expert System based on Knowledge Discovery (ESKD) is proposed. As the key knowledge acquisition component of ESKD, KD (D&K) is composed of KDD* and KDK*. KDD*-the new process model based on double bases cooperating mechanism; KDK*- the new process model based on double-basis fusion mechanism are introduced, respectively. The overall framework of ESKD is proposed. Some sub-systems and dynamic knowledge base system are discussed. Finally, the effectiveness and advantages of ESKD are tested in a real-world agriculture database. We hope that ESKD may be useful for the new generation of expert systems.
It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.
Particle accelerators are generators that produce beams of charged particles, acquiring different energies, depending on the accelerator type. The MGC-20 cyclotron is a cyclic particle accelerator used for accelerating protons, deuterons, alpha particles, and helium-3 to different energies. Its applications include isotope production, nuclear reaction, and mass spectroscopy studies. It is a complicated machine, it consists of five main parts, the ion source, the deflector, the beam transport system, the concentric and harmonic coils, and the radio frequency system. The diagnosis of this device is a very complex task. it depends on the conditions of 27 indicators of the control panel of the device. The accurate diagnosis can lead to a high system reliability and save maintenance costs. so an expert system for the cyclotron fault diagnosis is necessary to be built. In this thesis , a hybrid expert system was developed for the fault diagnosis of the MGC-20 cyclotron. Two intelligent techniques, multilayer feed forward back propagation neural network and the rule based expert system, are integrated as a pre-processor loosely coupled model to build the proposed hybrid expert system. The architecture of the developed hybrid expert system consists of two levels. The first level is two feed forward back propagation neural networks, used for isolating the faulty part of the cyclotron. The second level is the rule based expert system, used for troubleshooting the faults inside the isolated faulty part. 4-6 tabs., 4-5 figs., 36 refs
New techniques are now available for use in the protection of the environment. One of these techniques is the use of expert system for prediction groundwater pollution potential. Groundwater Pollution Expert system (GWPES) rules are a collection of principles and procedures used to know the comprehension of groundwater pollution prediction. The rules of groundwater pollution expert system in the form of questions, choice, radio-box, slide rule, button or frame are translated in to IF-THEN rule. The rules including of variables, types, domains and descriptions were used by the function of wxCLIPS (C Language Integrate Production System) expert system shell. (author)
Full Text Available Lack of traffic safety has become a serious issue in residential areas. In this paper, a web-based advisory expert system for the purpose of applying traffic calming strategies on residential streets is described because there currently lacks a structured framework for the implementation of such strategies. Developing an expert system can assist and advise engineers for dealing with traffic safety problems. This expert system is developed to fill the gap between the traffic safety experts and people who seek to employ traffic calming strategies including decision makers, engineers, and students. In order to build the expert system, examining sources related to traffic calming studies as well as interviewing with domain experts have been carried out. The system includes above 150 rules and 200 images for different types of measures. The system has three main functions including classifying traffic calming measures, prioritizing traffic calming strategies, and presenting solutions for different traffic safety problems. Verifying, validating processes, and comparing the system with similar works have shown that the system is consistent and acceptable for practical uses. Finally, some recommendations for improving the system are presented.
The structure of the warning message system is outlined and the feasibility of its adaptation to user needs is discussed. The system can be operated on an AT 386 or AT 486 personal computer or on an HP 300 workstation. The version for PC's runs under DOS 5.00, the version for workstations, under operating system HP-UX 7.00. The system can be interfaced to various sources of measured data, which can be completed with calculated data, and the whole is entered into the RECON expert system. This system performs a knowledge-base analysis and according to the results, messages are generated and transmitted to the display module serving as the interactive computer-user unit. The knowledge bases are described for controlling the automated systems at the Mochovce NPP and for WWER-440 reactor shutdown. Basic information is presented concerning the principles, structure and performance of the RECON expert system, including guidelines for operating the various parts of the system. (J.B.). 8 figs
Huang, Han; Rajotte, Edwin G.; Li, Zhihong; Chen, Ke; Zhang, Shengfang
Stored insect pests can seriously depredate stored products causing worldwide economic losses. Pests enter countries traveling with transported goods. Inspection and Quarantine activities are essential to prevent the invasion and spread of pests. Identification of quarantine stored insect pests is an important component of the China's Inspection and Quarantine procedure, and it is necessary not only to identify whether the species captured is an invasive species, but determine control procedures for stored insect pests. With the development of information technologies, many expert systems that aid in the identification of agricultural pests have been developed. Expert systems for the identification of quarantine stored insect pests are rare and are mainly developed for stand-alone PCs. This paper describes the development of a web-based expert system for identification of quarantine stored insect pests as part of the China 11th Five-Year National Scientific and Technological Support Project (115 Project). Based on user needs, textual knowledge and images were gathered from the literature and expert interviews. ASP.NET, C# and SQL language were used to program the system. Improvement of identification efficiency and flexibility was achieved using a new inference method called characteristic-select-based spatial distance method. The expert system can assist identifying 150 species of quarantine stored insect pests and provide detailed information for each species. The expert system has also been evaluated using two steps: system testing and identification testing. With a 85% rate of correct identification and high efficiency, the system evaluation shows that this expert system can be used in identification work of quarantine stored insect pests.
LI Wen-hong; SUN Shao-wen; ZHANG Qi
A mechinery fault diagnosis expert system based on case-based reasoning (CBR) technology was established. The process of the CBR fault diagnosis is analyzed from three main aspects: expression and memory, retrieving and matching, and modification and maintenance of a case. The results indicate that the CBR method is flexible and simple to implement, and it has strong self-studying ability. Using a large enough number of case reasoning sets, it can accumulate the experience of problem solving, avoid the difficulty of knowledge acquisition, shorten the course of solving problems, improve efficiency of reasoning, and save the time of developing.
Ebrahimi, Alireza Pour; Toloui Ashlaghi, Abbas; Mahdavy Rad, Maryam
Background: The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV. Materials and Methods: In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stag...
Using large finite element analysis codes for heat transfer computations and for stresses and displacements under thermal loads computations are not always very simple because of the complexity of the problems and the number of domains involved. Often faulty results from computations are being used until an expert discovers that something was wrong in the simulation. As a result of recent advances in artificial intelligence techniques, solutions to these problems are now possible by making use of knowledge based systems in which expertise in several domains can easily be introduced. In this paper, we present an application of knowledge based systems for a finite element analysis code in heat transfer. The system is fairly general, and we think that application to any well structured numerical code should be straightforward. (orig.)
Full Text Available The presently developed paper deals with the concepts of web based online expert systems and machine learning Algorithms in the field of Artificial Intelligence. An expert system follows the methodology of task-based specification and it is independent in case of problem solving. Where as, the machine learning technique is used to find the good optimal solution. This paper mainly focuses on the investigations on the diseases and treatment to the diseases which were effected to the chilli plants by using the mechanism of Rule based system and Artificial Bee Colony1 (ABC algorithm. The rules in the database is processed by the rule based system and if the required rules are not present in the database, then the system goes to the Machine learning algorithm technique used expert system. Thus, by applying machine learning techniques, resulting to best global optimized solution for recognizing the diseases in chilli plants. This expert system is a web based online application for online users with java as front end and MySQL as backend.
Копей, Володимир Богданович; Семанишин, Леся Михайлівна
On the basis of frames for knowledge representation have been proposed principles for the development of knowledge bases and expert systems on general-purpose programming language Python. Object-oriented and introspection capabilities of Python have been analyzed. The demo of knowledge base and the examples of querying to it have been developed
WANGLing; MUZhi-Chun; GUOHui
A new approach is proposed to model nonlinear dynamic systems by combining SOM(self-organizing feature map) with support vector regression (SVR) based on expert system. The whole system has a two-stage neural network architecture. In the first stage SOM is used as a clustering algorithm to partition the whole input space into several disjointed regions. A hierarchical architecture is adopted in the partition to avoid the problem of predetermining the number of partitioned regions. Then, in the second stage, multiple SVR, also called SVR experts, that best fit each partitioned region by the combination of different kernel function of SVR and promote the configuration and tuning of SVR. Finally, to apply this new approach to time-series prediction problems based on the Mackey-Glass differential equation and Santa Fe data, the results show that SVR experts has effective improvement in the generalization performance in comparison with the single SVR model.
Δάμη, Μαρία; Vella, Alfred
The problem of misuse of statistical packages and hence statistical methods has long peen recognised but no real solution has yet appeared, although some useful work has been done in related fields. This problem appears to lend itself to expert system technology. This paper outlines the history of research in statistical expert systems, showing how the demands of data analysis are different from those of other fields. Furthermore, the paper reviews some recent work and discu...
Full Text Available Environmental impact assessments [EIA] involve identifying, measuring, and assessing impacts. This complex process deals with considerable amount of information and requires processing and analysis of quantitative data, qualitative information as well as expert human judgements. Often, available information is incomplete, subjective, and inconsistent. This challenge of collecting, processing, analyzing, and reporting EIA information can be met by computer systems. A Cloud-based Environmental Impact Assessment [EIA] system is proposed in this paper to overcome the many challenges faced by practitioners. Fiji’s EIA process is used as a case study. The steps involved in the process are automated as a sequence of computer executable programs with Expert System. Based on the information provided about projects, the EIA system is expected to compute environmental impacts and produce Environment Impact Statements. With the system, a user enters information about the environmental settings in which the development project is expected to take place as well as the proposed development project activities. Based on the input, an expert system with an inference engine uses rules to check the knowledge base and report on possible impacts and mitigation actions. The knowledge base is connected to databases on domain experts, GIS and simulation models.
In this paper a steam turbine vibration monitoring system is described that uses a rule-based expert system for data review and fault diagnosis. Steady-state, coast-down, and steam temperature transient vibration signature techniques used by the monitor to detect transverse rotor cracks are summarized. A histogram technique for enhancing the initial appearance of a shallow crack 2/rev response is presented. The use of an expert system to fully automate diagnosis of turbine faults is discussed. Rotor crack and misalignment diagnostic rules are outlined
Sanjeev Kumar Jha; Singh, D.K.
The development of expert system for treatment of Diabetes disease by using natural methods is new information technology derived from Artificial Intelligent research using ESTA (Expert System Text Animation) System. The proposed expert system contains knowledge about various methods of natural treatment methods (Massage, Herbal/Proper Nutrition, Acupuncture, Gems) for Diabetes diseases of Human Beings. The system is developed in the ESTA (Expert System shell for Text Animation) which is Visu...
The operator's mental activity is the most important part of his work. A processing of a large amount of the information by the operator is possible only if he/she possesses appropriate cognitive skills. To facilitate the novice's acquisition of the experienced operator's cognitive skills of the decision-making process a special type of the expert system was developed. The cognitive engineering's models and problem-solving methodology constitutes the basis of this expert system. The article gives an account of the prototype of the mentioned expert system developed to aid the whole mental activity of the nuclear power plant operator during his decision-making process. (author)
In this work, an Expert System is presented, designed to assist the operator of the CAREM-25 Power Station during postulated Severe Accidents. CAREM-25 is a new generation, very low power (100 MWth, 25 Mwe net) nuclear station. The knowledge base of the Expert System was constructed from the Containment Events Trees of the corresponding PSA made for this Power Station. At the same time, the calculations of probabilities were improved. They were implemented in the different branches of the Containment Events Trees using fuzzy arithmetic. The Expert System has been designed in Fuzzy CLIPS V6.04A. In its present state of development it interacts with the user by asking questions that help to determine the state of damage of the plant. Like answers, it gives the data that characterize the state of the plant and the probable states at which the containment would arrive as well as the values from the associated probability. (author)
Tonn, B.; MacGregor, D.
This paper discusses psychological problems relevant to developing and designing expert systems. With respect to the former, the psychological literature suggests that several cognitive biases may affect the elicitation of a valid knowledge base from the expert. The literature also suggests that common expert system inference engines may be quite inconsistent with reasoning heuristics employed by experts. With respect to expert system user interfaces, care should be taken when eliciting uncertainty estimates from users, presenting system conclusions, and ordering questions.
Hossain, Mohammad Shahadat; Zander, Pär-Ola Mikael; Kamal, Md Sarwar;
requires continuous evaluation of the overall e-government system as well as evaluation of its various dimensions such as determinants, characteristics and results. E-government development is often complex, with multiple stakeholders, large user bases and complex goals. Consequently, even experts have...
Sanjeev Kumar Jha
Full Text Available The development of expert system for treatment of Diabetes disease by using natural methods is new information technology derived from Artificial Intelligent research using ESTA (Expert System Text Animation System. The proposed expert system contains knowledge about various methods of natural treatment methods (Massage, Herbal/Proper Nutrition, Acupuncture, Gems for Diabetes diseases of Human Beings. The system is developed in the ESTA (Expert System shell for Text Animation which is Visual Prolog 7.3 Application. The knowledge for the said system will be acquired from domain experts, texts and other related sources
Jha, Sanjeev Kumar
The development of expert system for treatment of Diabetes disease by using natural methods is new information technology derived from Artificial Intelligent research using ESTA (Expert System Text Animation) System. The proposed expert system contains knowledge about various methods of natural treatment methods (Massage, Herbal/Proper Nutrition, Acupuncture, Gems) for Diabetes diseases of Human Beings. The system is developed in the ESTA (Expert System shell for Text Animation) which is Visual Prolog 7.3 Application. The knowledge for the said system will be acquired from domain experts, texts and other related sources.
In the development of a rule based expert system, one of key issues is how to acquire knowledge and to build knowledge base (KB). On building the KB of DISKET, which is an expert system for nuclear reactor accident diagnosis developed in JAERI, several problems have been experienced as follows. To write rules is a time consuming task, and it is difficult to keep the objectivity and consistency of rules as the number of rules increase. Further, certainty factors (CFs) must be often determined according to engineering judgement, i.e. empirically or intuitively. A systematic approach was attempted to handle these difficulties and to build an objective KB efficiently. The approach described in this report is based on the concept that a prototype KB, colloquially speaking ''an initial guess'', should first be generated in a systematic way and then is to be modified and/or improved by human experts for practical use. Statistical methods, principally Factor Analysis, were used as the systematic way to build a prototype KB for the DISKET using a PWR plant simulator data. The source information is a number of data obtained from the simulation of transients, such as the status of components and annunciators etc., and major process parameters like pressures, temperatures and so on. The results of diagnoses shows that the statistical method, Factor Analysis, is powerful for building a prototype of knowledge base of an expert system for reactor accident diagnosis like DISKET. (author)
Full Text Available Inks, drilling fluids, shower gels and drug delivery vehicles are just a few examples of the many industrial and consumer products based on colloidal and nanostructured complex fluids. The successful formulation of these materials is promoted by understanding how rheological behaviour, which typically dictates performance, relates to underlying microstructure. However, this knowledge can be difficult to obtain for those without the necessary expertise. This article shows how recent developments in rheometer technology address this issue. New rheometers, exemplified by the Kinexus from Malvern have expert knowledge embedded within the instrument and are able to guide users through measurement and data analysis to relevant information. Such systems facilitate development of the design rules to optimize formulations and generate novel and high performance materials of the future.
MacRae, Jayden; Love, Tom; Michael G Baker; Dowell, Anthony; Carnachan, Matthew; Stubbe, Maria; McBain, Lynn
Background We designed and validated a rule-based expert system to identify influenza like illness (ILI) from routinely recorded general practice clinical narrative to aid a larger retrospective research study into the impact of the 2009 influenza pandemic in New Zealand. Methods Rules were assessed using pattern matching heuristics on routine clinical narrative. The system was trained using data from 623 clinical encounters and validated using a clinical expert as a gold standard against a m...
By combining the artificial neural network with the rule reasoning expert system,an expert diagnosing system for a rotation mechanism was established. This expert system takes advantage of both a neural network and a rule reasoning expert system; it can also make use of all kinds of knowledge in the repository to diagnose the fault with the positive and negative mixing reasoning mode. The binary system was adopted to denote all kinds of fault in a rotation mechanism. The neural networks were trained with a random parallel algorithm (Alopex). The expert system overcomes the self-learning difficulty of the rule reasoning expert system and the shortcoming of poor system control of the neural network.The expert system developed in this paper has powerful diagnosing ability.
Qiaodan HU; Peng LUO; Yi YANG; Liliang CHEN
We develop a neuro-knowledge-based expert system (NKBES) frame in this work. The system mainly concerns with decision of gating system and die casting machine based on a neuro-inference engine launched under the MATLAB software environment. For enhancement of reasoning agility, an error back-propagation neural network was applied.A rapidly convergent adaptive learning rate (ALR) and a momentum-based error back-propagation algorithm was used to conduct neuro-reasoning. The working effect of the system was compared to a conventional expert system that is based on a two-way (forward and backward) chaining inference mechanism. As the reference, the present paper provided the neural networks sum-squared error (SSE) and ALR vs iterative epoch curves of process planning case mentioned above. The study suggests that the neuro-modeling optimization application to die casting process design has good feasibility, and based on that a novel and effective intelligent expert system can be launched at low cost.
Full Text Available It is important to find optimal solutions for structural errors in rule-based expert systems .Solutions to discovering such errors by using model checking techniques have already been proposed, but these solutions have problems such as state space explosion. In this paper, to overcome these problems, we model the rule-based systems as finite state transition systems and express confliction and unreachabilityas Computation Tree Logic (CTL logic formula and then use the technique of model checking to detect confliction and unreachability in rule-based systems with the model checker UPPAAL.
Olusegun Folorunso; Olusegun Afeez Mustapha
Crowdsourcing has been widely accepted across a broad range of application areas. In crowdsourcing environments, the possibility of performing human computation is characterized with risks due to the openness of their web-based platforms where each crowd worker joins and participates in the process at any time, causing serious effect on the quality of its computation. In this paper, a combination of Trust-Based Access Control (TBAC) strategy and fuzzy-expert systems was used to enhance the qu...
This paper describes the development of an expert system for fault analysis of electronic instruments in the CIRUS nuclear reactor. The system was developed in Prolog on an IBM PC-XT compatible computer. A 'model-based' approach (Button et al, 1986) was adopted combining 'frames' and 'rules' to provide flexible control over the inferencing mechanisms. Frames represent the domain-objects as well as the inter-object relationships. They include 'demons' or 'active values' for triggering actions. Rules, along with frames, are used for fault analysis. The rules can be activated either in a data-driven or a goal-driven manner. The use of frames makes rule management easier. It is felt that developing in-house shell proved advantageous, compared to using commercially available shells. Choosing the model-based approach was efficient compared to a production system architecture. Therefore, the use of hybrid representations for diagnostic applications is advocated. Based on the experience, some general recommendations for developing such systems are presented. The expert system helps novice operators to understand the process of diagnosis and achieve a significant required level of competence. The system may not achieve the required level of proficiency by itself, but it can be used to train operators to become experts. (author). 12 refs
Bertaud Gounot, Valérie; Donfack, Valéry; Lasbleiz, Jérémy; Bourde, Annabel; Duvauferrier, Régis
Expert systems of the 1980s have failed on the difficulties of maintaining large rule bases. The current work proposes a method to achieve and maintain rule bases grounded on ontologies (like NCIT). The process described here for an expert system on plasma cell disorder encompasses extraction of a sub-ontology and automatic and comprehensive generation of production rules. The creation of rules is not based directly on classes, but on individuals (instances). Instances can be considered as prototypes of diseases formally defined by "destrictions" in the ontology. Thus, it is possible to use this process to make diagnoses of diseases. The perspectives of this work are considered: the process described with an ontology formalized in OWL1 can be extended by using an ontology in OWL2 and allow reasoning about numerical data in addition to symbolic data. PMID:21893840
The US Nuclear Regulatory Commission (NRC) and the Electric Power Research Institute have initiated a broad-based exploration of means to evaluate the potential applications of expert systems in the nuclear industry. This exploratory effort will assess the use of expert systems to augment the diagnostic and decision-making capabilities of personnel with the goal of enhancing productivity, reliability, and performance. The initial research effort is the development and documentation of guidelines for verifying and validating (V and V) expert systems. An initial application of expert systems in the nuclear industry is to aid operations and maintenance personnel in decision-making tasks. The scope of the decision aiding covers all types of cognitive behavior consisting of skill, rule, and knowledge-based behavior. For example, procedure trackers were designed and tested to support rule-based behavior. Further, these systems automate many of the tedious, error-prone human monitoring tasks, thereby reducing the potential for human error. The paper version of the procedure contains the knowledge base and the rules and thus serves as the basis of the design verification of the procedure tracker. Person-in-the-loop tests serve as the basis for the validation of a procedure tracker. When conducting validation tests, it is important to ascertain that the human retains the locus of control in the use of the expert system
Som, Pradip; Chitturi, Ramesh; Babu, A. J. G.
Expert system, a special branch of Artificial Intelligence finds its way in the domain of manufacturing. This paper presents the basic ideas and features of the expert systems, problems in manufacturing and application of expert systems in manufacturing. As the process planning is an important phase in manufacturing, the suitability of expert systems for process planning area has been highlighted. Several expert systems, developed to solve manufacturing problems are also discussed in the paper.
Full Text Available From the first applications to this day, expert systems have obtained remarkable results in many areas, by using knowledge extracted and transferred from human experts. The main reason behind the advent of expert systems was the potential to provide recommendations to a large number of users. In today’s world, the spread of the Internet and web applications generated an exponential growth of the quantity of information that needs to be processed by an increasing number of users. Under these circumstances emerged the convergence of web technologies with expert systems, resulting in the category of web based expert systems. The potential of traditional expert systems was harnessed by using web technologies, offering new ways of disseminating expertise and knowledge to a mass audience. In this paper we will first review base concepts and features of traditional expert systems and then point out the benefits brought by the development and the use of web based expert systems.
Kraines, Steven; Guo, Weisen
Work towards creation of a knowledge sharing system for sustainability science through the application of semantic data modeling is described. An ontology grounded in description logics was developed based on the ISO 15926 data model to describe three types of sustainability science conceptualizations: situational knowledge, analytic methods, and scenario frameworks. Semantic statements were then created using this ontology to describe expert knowledge expressed in research proposals and pape...
Emergency Operating Procedures (EOPs) generally and an accident management (AM) particularly play a significant part in the safety philosophy on NPPs since many years. A better methodology for development and validation of EOPs is desired. A prototype of an Emergency Operating Procedures Analysis System (EOPAS), which has been developed at GRS, is presented in the paper. The hardware configuration and software organisation of the system is briefly reviewed. The main components of the system such as the knowledge base of an expert system and the engineering simulator are described. (author)
Full Text Available This paper deals with the development of Web based online expert systems using Evolutionary Algorithms. An expert system is a computer application that performs a task that would otherwise be performed by a human expert. Here one of the evolutionary algorithms (ACO Algorithm is considered to find a good match of symptoms in the database. In the present paper, Ant Colony Optimization1 (ACO algorithm has been taken as the base and the concept of optimization is included, so that the new algorithm mainly focuses on the determination of the quality of eggs in the poultry farms. At first, the symptoms provided by the user are processed by a rule based expert system for identifying the quality of the eggs. If the rules required for processing the data by the above are not present in the database, then the system automatically calls the machine learning algorithm technique. As a whole, the system results good optimized solution for recognizing the quality and viruses if any affected to eggs in poultry farms. And corresponding treatments to the viruses may also be suggested to the users. This expert system is designed with JSP as front end and MySQL as backend.
The feasibility of using expert systems as an aid in regulatory compliance functions has been investigated. A literature review was carried out to identify applications of expert systems to regulatory affairs. A bibliography of the small literature on such applications was prepared. A prototype system, ARIES, was developed to demonstrate the use of an expert system as an aid to a Project Officer in assuring compliance with licence requirements. The system runs on a personal computer with a graphical interface. Extensive use is made of hypertext to link interrelated rules and requirements as well as to provide an explanation facility. Based on the performance of ARIES the development of a field version is recommended
Full Text Available Tread winding technology is widely used in the process of tire molding. Technologists use traditional process of developing new products with tread winding line relying only on personal experience for operations like manually layering of the new product tread outline. In this way, the rubber distribution stability of each layer will be affected, prolong development time, and increase the development cost and rejection rate. In this paper, we propose an intelligent layering expert system with technology expert experience based on the LabVIEW by analyzing the mass of data and building a mathematical model of automatic layering rules. In practical application, this system reduces the shortcomings of the traditional development by shortening the impact of the production research, development cycle and reducing the development cost and hence provision of good economic benefits.
In the development of a rule based expert system, one of the key issues is how to acquire knowledge and to build knowledge base (KB). On building the KB of DISKET, which is an expert system for nuclear reactor accident diagnosis developed in JAERI, several problems have been experienced as follows. To write rules is a time consuming task, and it is difficult to keep the objectivity and consistency of rules as the number of rules increase. Further, certainty factors (CFs) must be often determined according to engineering judgment, i.e., empirically or intuitively. A systematic approach was attempted to handle these difficulties and to build an objective KB efficiently. The approach described in this paper is based on the concept that a prototype KB, colloquially speaking an initial guess, should first be generated in a systematic way and then is to be modified and/or improved by human experts for practical use. Statistical methods, principally Factor Analysis, were used as the systematic way to build a prototype KB for the DISKET using a PWR plant simulator data. The source information is a number of data obtained from the simulation of transients, such as the status of components and annunciator etc., and major process parameters like pressures, temperatures and so on
Based on the fuzzy expert system fault diagnosis theory, the knowledge base architecture and inference engine algorithm are put forward for avionic device fault diagnosis. The knowledge base is constructed by fault query network, of which the basic element is the test-diagnosis fault unit. Every underlying fault cause's membership degree is calculated using fuzzy product inference algorithm, and the fault answer best selection algorithm is developed, to which the deep knowledge is applied. Using some examples,the proposed algorithm is analyzed for its capability of synthesis diagnosis and its improvement compared to greater membership degree first principle.
HAN Liu-xin; WANG Huan-chen; ZHANG Xian-hui
A detailed study of the capabilities of artificial neural networks to diagnoses cracks in massive concrete structures is presented. This paper includes the components of the expert system such as design thought, basic structure, building of knowledge base and the implementation of neural network applied model. The realizing method of neural network based clustering algorithm in the knowledge base and selfstudy is analyzed emphatically and stimulated by means of the computer. From the above study, some important conclusions have been drawn and some new viewpoints have been suggested.
The adoption of expert systems mainly as operator supporting systems is becoming increasingly popular as the control algorithms of system become more and more sophisticated and complicated. The verification phase of knowledge base is an important part for developing reliable expert systems, especially in nuclear industry. Although several strategies or tools have been developed to perform potential error checking, they often neglect the reliability of verification methods. Because a Petri net provides a uniform mathematical formalization of knowledge base, it has been employed for knowledge base verification. In this work, we devise and suggest an automated tool, called COKEP(Checker of Knowledge base using Extended Petri net), for detecting incorrectness, inconsistency, and incompleteness in a knowledge base. The scope of the verification problem is expended to chained errors, unlike previous studies that assume error incidence to be limited to rule pairs only. In addition, we consider certainty factor in checking, because most of knowledge bases have certainly factors. 8 refs,. 2 figs,. 4 tabs. (author)
Nuclear reactor operators are required to pay special attention to spatial xenon oscillations during the load-follow operation of pressurized water reactors. They are expected to observe the axial offset of the core, and to estimate the correct time and amount of necessary control action based on heuristic rules given in axial xenon oscillations are knowledge intensive, and heuristic in nature. An expert system, ACES (Axial offset Control using Expert Systems) is developed to implement a heuristic constant axial offset control procedure to aid reactor operators in increasing the plant reliability by reducing the human error component of the failure probability. ACES is written in a production system language, OPS5, based on the forward chaining algorithm. It samples reactor data with a certain time interval in terms of measurable parameters, such as the power, period, and the axial offset of the core. It then processes the core status utilizing a set of equations which are used in a back of the envelope calculations by domain experts. Heuristic rules of ACES identify the control variable to be used among the full and part length control rods and boron concentration, while a knowledge base is used to determine the amount of control. ACES is designed as a set of generic rules to avoid reducing the system into a set of patterns. Instead ACES evaluates the system, determines the necessary corrective actions in terms of reactivity insertion, and provides this reactivity insertion using the control variables. The amount of control action is determined using a knowledge base which consists of the differential rod worth curves, and the boron reactivity worth of a given reactor. Having the reactor dependent parameters in its knowledge base, ACES is applicable to an arbitrary reactor for axial offset control purposes
Shadbolt, N R
This paper examines the origins, current state and future prospects for expert systems. The origins are traced from the schism with classic Artificial Intelligence. The characteristics of early expert systems are described and contrasted with more recent developments. A number of influential forces operating on present day systems are reviewed. The future trends in the evolution of expert systems are discussed.
The first expert systems prototypes intended for advising physicians on diagnosis or therapy selection have been designed more than ten years ago. However, a few of them are already in use in clinical practice after years of research and development efforts. The capabilities of these systems to reason symbolically and to mimic the hypothetico-deductive processes used by physicians distinguishes them from conventional computer programs. Their power comes from their knowledge-base which embeds a large quantity of high-level, specialized knowledge captured from medical experts. Common methods for knowledge representation include production rules and frames. These methods also provide a mean for organizing and structuring the knowledge according to hierarchical or causal links. The best expert-systems perform at the level of the experts. They are easy to learn and use, and can communicate with the user in pseudo-natural language. Moreover they are able to explain their line of reasoning. These capabilities make them potentially useful, usable and acceptable by physicians. However if the problems related to difficulties and costs in building expert-systems are on the way to be solved within the next few years, forensic and ethical issues should have to be addressed before one can envisage their routine use in clinical practice
Butler, G. F.; Graves, A. T.; Disbrow, J. D.; Duke, E. L.
A joint activity between the Dryden Flight Research Facility of the NASA Ames Research Center (Ames-Dryden) and the Royal Aerospace Establishment (RAE) on knowledge-based systems has been agreed. Under the agreement, a flight status monitor knowledge base developed at Ames-Dryden has been implemented using the real-time AI (artificial intelligence) toolkit MUSE, which was developed in the UK. Here, the background to the cooperation is described and the details of the flight status monitor and a prototype MUSE implementation are presented. It is noted that the capabilities of the expert-system flight status monitor to monitor data downlinked from the flight test aircraft and to generate information on the state and health of the system for the test engineers provides increased safety during flight testing of new systems. Furthermore, the expert-system flight status monitor provides the systems engineers with ready access to the large amount of information required to describe a complex aircraft system.
A new superstructure from of heat exchanger networks(HEN) is proposed based on expert system (ES). The new superstructure from is combined with the practical engineering.The different investment cost formula for different heat exchanger is also presented based on ES.The mathematical model for the simultaneous optimization of network configuration is established and solved by a genetic algorithm.This method can deal with larger scale HEN synthesis and the optimal HEN configuration is obtained automatically.Finally,a case study is presented to demonstrate the effectiveness of the method.
Bagby, D. G.; Cormier, R. A.
A real-time expert system intended for detecting and diagnosing faults in a 20 kW microwave transmitter heat exchanger is described. The expert system was developed on a LISP machine, Incorporated (LMI), Lambda Plus computer using Process Intelligent Control (PICON) software. The Heat Exhanger Expert System was tested and debugged. Future applications and extensions of the expert system to transmitters, masers, and antenna subassemblies are discussed.
Cabrera, Mariana Maceiras
This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the implementation of the adaptation stage, from the integration of Case Based Reasoning and Rule Based Expert Systems. In this adaptation stage we use a higher level RBC that stores and allows reutilizing change experiences, combined with a classic rule-based inference engine. In order to take into account the most evident clinical situation, a pre-diagnosis stage is implemented using a rule engine that, given an evident situation, emits the corresponding diagnosis and avoids the complete process.
Full Text Available As it is known, the expert systems- particularlyreferring to the ones in the economical area, represent a currentissue of our days, them being approached by all the economicalbranches. Starting from these aspects, we wish to present somenecessary principles and considerations regarding the expertsystems, representation of the facts, systems based onproduction rules. The objective of this paper is aimed toidentifying the exigencies of the production system based onrules.
This research concerns the development of artificial intelligence (AI) techniques suitable for application to the diagnostics and control of nuclear power plant systems. The overall objective of the current effort is to build a prototype simulation-based expert system for diagnosing accidents in nuclear reactors. The system is being designed to analyze plant data heuristically using fuzzy logic to form a set of hypotheses about a particular transient. Hypothesis testing, fault magnitude estimation and transient analysis is performed using simulation programs to model plant behavior. An adaptive learning technique has been developed for achieving accurate simulations of plant dynamics using low-order physical models of plant components. The results of the diagnostics and simulation analysis of the plant transient are to be analyzed by an expert system for final diagnoses and control guidance. To date, significant progress has been made toward achieving the primary goals of this project. Based on a critical safety functions approach, an overall design for the nuclear plant expert system has been developed. The methodology for performing diagnostic reasoning on plant signals has been developed and the algorithms implemented and tested. A methodology for utilizing the information contained in the physical models of plant components has also been developed. This work included the derivation of a unique Kalman filtering algorithm for using power plant data to systematically improve on-line simulations through the judicious adjustment of key model parameters. A few simulation models of key plant components have been developed and implemented to demonstrate the method on a realistic accident scenario. The chosen transient is a loss of feed flow exasperated by a stuck open relief valve, similar to the initiating event of the Three Mile Island Unit 2 accident in 1979
Prasad, Kanika; Chakraborty, Shankar
Computer numerical control (CNC) machine tools are automated devices capable of generating complicated and intricate product shapes in shorter time. Selection of the best CNC machine tool is a critical, complex and time-consuming task due to availability of a wide range of alternatives and conflicting nature of several evaluation criteria. Although, the past researchers had attempted to select the appropriate machining centres using different knowledge-based systems, mathematical models and multi-criteria decision-making methods, none of those approaches has given due importance to the voice of customers. The aforesaid limitation can be overcome using quality function deployment (QFD) technique, which is a systematic approach for integrating customers' needs and designing the product to meet those needs first time and every time. In this paper, the adopted QFD-based methodology helps in selecting CNC turning centres for a manufacturing organization, providing due importance to the voice of customers to meet their requirements. An expert system based on QFD technique is developed in Visual BASIC 6.0 to automate the CNC turning centre selection procedure for different production plans. Three illustrative examples are demonstrated to explain the real-time applicability of the developed expert system.
Hull, Larry; Gilstrap, Lewey
A risk-based expert-system development methodology has been developed to provide guidance to managers and technical personnel and to serve as a standard for developing expert systems. Expert-system development differs from conventional software development in that the information needed to prepare system requirements for expert systems is not known at the outset of a project and is obtained by knowledge engineering methods. The paper describes the expert-system life cycle, development methodology, and the approach taken in this methodology to manage and reduce the risks in expert system development. Also examined are the risks of using and of not using a methodology, the studies undertaken to validate the provisions of the expert system development methodology, and the results of these validation studies.
This experiment which was the second in a series, conducted at the OECD Halden Reactor Project, Halden, Norway in the spring 1991, aimed to assess the effect on nuclear power plant operators diagnostic behaviour when using a rule based diagnostic expert system. The rule based expert system used in the experiment is called DISKET (Diagnosis System Using Knowledge Engineering Technique) and was originally developed by the Japan Atomic Energy Research Institute (JAERI). The experiment was performed in the Halden man-machine laboratory using a full scope pressurized water reactor simulator called NORS. Operator performance in terms of quality of diagnosis is improved by the use of SISKET. The use of the DISKET system also influences operators problem solving behaviour. The main difference between the two experimental conditions can be characterized as while the DISKET users during the diagnosis process are following a strategy which is direct and narrowed, the non-DISKET users are using a much broader and less focused search when trying to diagnose a disturbance. (author)
Herrin, Stephanie; Iverson, David; Spukovska, Lilly; Souza, Kenneth A. (Technical Monitor)
Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.
GaneshKumar, Pugalendhi; Rani, Chellasamy; Devaraj, Durairaj; Victoire, T Aruldoss Albert
Accuracy maximization and complexity minimization are the two main goals of a fuzzy expert system based microarray data classification. Our previous Genetic Swarm Algorithm (GSA) approach has improved the classification accuracy of the fuzzy expert system at the cost of their interpretability. The if-then rules produced by the GSA are lengthy and complex which is difficult for the physician to understand. To address this interpretability-accuracy tradeoff, the rule set is represented using integer numbers and the task of rule generation is treated as a combinatorial optimization task. Ant colony optimization (ACO) with local and global pheromone updations are applied to find out the fuzzy partition based on the gene expression values for generating simpler rule set. In order to address the formless and continuous expression values of a gene, this paper employs artificial bee colony (ABC) algorithm to evolve the points of membership function. Mutual Information is used for idenfication of informative genes. The performance of the proposed hybrid Ant Bee Algorithm (ABA) is evaluated using six gene expression data sets. From the simulation study, it is found that the proposed approach generated an accurate fuzzy system with highly interpretable and compact rules for all the data sets when compared with other approaches. PMID:26355782
The components and functioning of the GPCS information system applicable for intelligent process monitoring and alarm generation in a WWER-440 type nuclear power plant are described. The prototype system has been developed by using the G2 expert system, plant measurements were simulated by a WWER-440 compact simulator and by archive replay sessions performed by the VERONA-u core monitoring system. The GPCS contains an object oriented description of the basic subsystems of the plant and concentrates on the fast evaluation/displaying of measurements and alarms. The high-level information reflecting actual plant safety status is synthesized from primary measured data, by forming global alarms and by evaluating logical diagrams. (author). 10 refs, 4 figs
The need of predicting the integrity of the steam generator(SG) tubes and environmental conditions that affect their integrity is growing to secure nuclear power plant(NPP) safety and enhance plant availability. To achieve their objectives it is important to diagnose the integrity of the SG tubes. An expert system called FEMODES(failure mode diagnosis expert system) has been developed for diagnosis of such tube degradation phenomena as denting, intergranular attack(IGA) and stress corrosion cracking(SCC) in the secondary side of the SG. It is possible with use of FEMODES to estimate possibilities of SG tube degradation and diagnosis environmental conditions that influence such tube degradation. The method of certainty factor theory(CFT) and the rule based backward reasoning inference strategy are used to develop FEMODES. The information required for diagnosis is acquired from SG tube degradation experiences of two local reference plants, some limited oversea plants and technical reports/research papers about such tube degradation. Overall results estimated with use of FEMODES are in reasonable agreement with actual SG tube degradation. Some discrepancy observed in several estimated values of SG tube degradation appears to be due to insufficient heuristic knowledge for knowledge data base of FEMODES
Full Text Available Crowdsourcing has been widely accepted across a broad range of application areas. In crowdsourcing environments, the possibility of performing human computation is characterized with risks due to the openness of their web-based platforms where each crowd worker joins and participates in the process at any time, causing serious effect on the quality of its computation. In this paper, a combination of Trust-Based Access Control (TBAC strategy and fuzzy-expert systems was used to enhance the quality of human computation in crowdsourcing environment. A TBAC-fuzzy algorithm was developed and implemented using MATLAB 7.6.0 to compute trust value (Tvalue, priority value as evaluated by fuzzy inference system (FIS and finally generate access decision to each crowd-worker. In conclusion, the use of TBAC is feasible in improving quality of human computation in crowdsourcing environments.
Leila Ooshaksaraie; Alireza Mardookhpour
Problem statement: The construction industry generates lots of construction waste which caused significant impacts on the environment and aroused growing public concern in the local community. Construction waste is becoming a serious environmental problem in many large cities in the world. Approach: In recent years, expert systems have been used extensively in different applications areas including environmental studies. In this study, expert system software -CDWM- developed by using Microsof...
Full Text Available Problem statement: The construction industry generates lots of construction waste which caused significant impacts on the environment and aroused growing public concern in the local community. Construction waste is becoming a serious environmental problem in many large cities in the world. Approach: In recent years, expert systems have been used extensively in different applications areas including environmental studies. In this study, expert system software -CDWM- developed by using Microsoft Visual Basic was introduced. CDWM to be used for construction waste management plan was designed based on the legal process. Results: According to the construction waste management regulation enacted, construction activities require mandatory construction waste management plan before staring activities. CDWM primarily aims to provide educational and support system for construction engineers and decision-makers during construction activities. It displays construction waste management plan in report form and the best location of construction waste storage area in GIS format. Conclusion: When the use of CDWM in construction waste management plan becomes widespread, it is highly possible that it will be benefited in terms of having more accurate and objective decisions on construction projects which are mainly focused on reducing the construction waste.
Yekini Nureni Asafe
Full Text Available The use of Information Technologies have played and currently playing prominent roles in many organizations, such as business, education, commerce. The tourism industry has witnessed the use and application of various computer-based systems in carrying out one or more activities or operation. But currently there is no computer-based system tourist destination to integrate the tourists (from outside Nigeria and tourists center within Nigeria, so that tourists can make a pre destination plan and decision before venturing into tourism journey to the country Nigeria. The authors of this paper proposed the design of web-based Expert Decision System (WEDSS, to provide tourist to Nigeria and its environ essential data and tools to managing their tours and to base all the decisions concerning to queries on the, tourist centers and hotels based on the following issue; climate, road conditions, cultural aspects, lodging, health facilities, banking, etc. of the location to be visited on sound and rational bases. Web-Based Tourist Decision Support System (WEDSS for Nigeria will be developed to allow the tourist to find their route in Nigeria and ask for information about sights, accommodations and other places of interest which are nearby to him to improve the convenience, safety, efficiency of travel and enhance tourism attraction of tourists.
MA Rui; LIU Yu-shu; DU Yan-hui
In order to improve the detection efficiency of rule-based expert systems, an intrusion detection approach using connectionist expert system is proposed. The approach converts the AND/OR nodes into the corresponding neurons, adopts the three-layered feed forward network with full interconnection between layers,translates the feature values into the continuous values belong to the interval [0, 1 ], shows the confidence degree about intrusion detection rules using the weight values of the neural networks and makes uncertain inference with sigmoid function. Compared with the rule-based expert system, the neural network expert system improves the inference efficiency.
Matsumoto, N.; Kuraoka, H.; Ohka, N.; Ohba, M.; Tabe, T.
In this paper we discuss how to generate the command value for the optimal regulator in an automotive antiskid system. First, the behavior of the vehicle at braking is expressed as a mathematical model with the formulation by physical consideration and identification of the hydraulic system by statistical methods. An optimal regulator with additional integral is applied to the automotive antiskid control in order to make the each wheel speed follow any command value. However, the desired command value to stop the vehicle efficiently and stably is dependent on ambiguous road surface conditions. Thus, how to determine the desired command value under the moment-to-moment conditions is most important. A method for inferring the conditions is developed using fuzzy logic, with three fuzzy variables expressing the conditions adequately. On the basis of the inference, the ideal command values are generated. Outstanding control performance and good adaptability are obtained in vehicle experiments. Consequently, the Expert Antiskid System, employing modern control theory and fuzzy logic, can stop a vehicle efficiently and stably under any condition.
Hadipriono, Fabian C.; Diaz, Carlos F.; Merritt, Earl S.
The research project results in a powerful yet user friendly CROPCAST expert system for use by a client to determine the crop yield production of a certain crop field. The study is based on the facts that heuristic assessment and decision making in agriculture are significant and dominate much of agribusiness. Transfer of the expert knowledge concerning remote sensing based crop yield production into a specific expert system is the key program in this study. A knowledge base consisting of a root frame, CROP-YIELD-FORECAST, and four subframes, namely, SATELLITE, PLANT-PHYSIOLOGY, GROUND, and MODEL were developed to accommodate the production rules obtained from the domain expert. The expert system shell Personal Consultant Plus version 4.0. was used for this purpose. An external geographic program was integrated to the system. This project is the first part of a completely built expert system. The study reveals that much effort was given to the development of the rules. Such effort is inevitable if workable, efficient, and accurate rules are desired. Furthermore, abundant help statements and graphics were included. Internal and external display routines add to the visual capability of the system. The work results in a useful tool for the client for making decisions on crop yield production.
Arie Segev; J. Leon Zhao
Expert database systems combine database and expert systems technologies to support the effective management of both rules and data. This paper studies rule processing strategies in expert database systems involving rules that are conditional on joins of relational data. Auxiliary constructs for processing join rules are proposed, and a framework of join rule processing strategies is developed. Cost functions of several strategies are derived based on a stochastic model that characterizes the...
The ASME Section XI Working Group on Implementation of Risk-Based (RB) Examination produced a code case to define risk-based selection rules that could be used for In-Service Inspection (ISI) of Class 1, 2 and 3 piping. To provide guidelines for practical implementation of the code case, EPRI sponsored work to develop evaluation procedures and criteria. The approach focuses inspections on locations which are selected based upon an explicit consideration of experienced degradation mechanisms and potential consequences. Software has been developed to execute and document this approach. Data and expert system modules address system operating characteristics, design attributes, the potential for damage mechanisms and the impact of component failures (i.e., loss of pressure boundary integrity). These modules are integrated in a stand alone software package. In addition, because the system is microcomputer based, the software is not cumbersome or costly to deploy. The goal of this effort was to develop a tool that will accomplish two tasks. That is, (1) Reduce the cost of the Risk Based Inservice Inspection (RBISI) evaluation effort by increasing the productivity of the BISI analyst, and (2) Provide a structured analytical and documentation package that lends itself to increases in consistency within an individual plant application, as well as across the industry
Owing to continuous production lines with large amount of consecutive controls, various control signals and huge logistic relations, this paper introduced the methods and principles of the development of knowledge base in a fault diagnosis expert system that was based on machine learning by the four-layer perceptron neural network. An example was presented. By combining differential function with not differentia function and back propagation of error with back propagation of expectation, the four-layer perceptron neural network was established. And it was good for solving such a bottleneck problem in knowledge acquisition in expert system and enhancing real-time on-line diagnosis. A method of synthetic back propagation was designed, which broke the limit to non-differentiable function in BP neural network.
Full Text Available Background. The early detection of rheumatic diseases and the treatment to target have become of utmost importance to control the disease and improve its prognosis. However, establishing a diagnosis in early stages is challenging as many diseases initially present with similar symptoms and signs. Expert systems are computer programs designed to support the human decision making and have been developed in almost every field of medicine. Methods. This review focuses on the developments in the field of rheumatology to give a comprehensive insight. Medline, Embase, and Cochrane Library were searched. Results. Reports of 25 expert systems with different design and field of application were found. The performance of 19 of the identified expert systems was evaluated. The proportion of correctly diagnosed cases was between 43.1 and 99.9%. Sensitivity and specificity ranged from 62 to 100 and 88 to 98%, respectively. Conclusions. Promising diagnostic expert systems with moderate to excellent performance were identified. The validation process was in general underappreciated. None of the systems, however, seemed to have succeeded in daily practice. This review identifies optimal characteristics to increase the survival rate of expert systems and may serve as valuable information for future developments in the field.
At General Electric (GE), an on-line expert system to support maintenance decisions for BWR recirculation pumps for nuclear power plants has been developed. This diagnostic expert system is an interactive on-line system that furnishes diagnostic information concerning BWR recirculation pump operational problems. It effectively provides the recirculation pump diagnostic expertise in the plant control room continuously 24 hours a day. The expert system is interfaced to an on-line monitoring system, which uses existing plant sensors to acquire non-safety related data in real time. The expert system correlates and evaluates process data and vibration data by applying expert rules to determine the condition of a BWR recirculation pump system by applying knowledge based rules. Any diagnosis will be automatically displayed, indicating which pump may have a problem, the category of the problem, and the degree of concern expressed by the validity index and color hierarchy. The rules incorporate the expert knowledge from various technical sources such as plant experience, engineering principles, and published reports. These rules are installed in IF-THEN formats and the resulting truth values are also expressed in fuzzy terms and a certainty factor called a validity index. This GE Recirculation Pump Expert System uses industry-standard software, hardware, and network access to provide flexible interfaces with other possible data acquisition systems. Gensym G2 Real-Time Expert System is used for the expert shell and provides the graphical user interface, knowledge base, and inference engine capabilities. (author)
Full Text Available Due to enhance in complexity of services, there is a necessity for dynamic interaction models. For a service-oriented system to work properly, we need a context-sensitive trust based search. Automatic information transfer is also deficient when unexpected query is given. However, it shows that search engines are vulnerable in answering intellectual queries and shows an unreliable outcome. The user cannot have a fulfillment with these results due to lack of trusts on blogs. In our modified trust algorithm, which process exact skill matching and retrieval of information based on proper content rank. Our contribution to this system is new modified trust algorithm with automatic formulation of meaningful query search to retrieve the exact contents from the top-ranked documents based on the expert rank and their content quality verified of their resources provided. Some semantic search engines cannot show their important performance in improving precision and lowering recall. It hence effectively reduces complexity in combining HPS and software services.
An Artificial Intelligence-Expert System called APES (Analysis of Proliferation by Expert System) has been developed and tested to permit a non proliferation expert to evaluate the capability and capacity of a specified LWR reactor and PUREX reprocessing system for producing and separating plutonium even when system information may be limited and uncertain. APES employs an expert system coded in LISP and based upon an HP-RL (Hewlett Packard-Representational Language) Expert System Shell. The user I/O interface communicates with a blackboard and the knowledge base which contains the quantitative models required to describe the reactor, selected fission product production and radioactive decay processes, Purex reprocessing and ancillary knowledge
Liu, X.; Skidmore, A.K.; Bronsveld, M.C.
To conserve giant panda effectively, it is important to understand the spatial pattern and temporal change of its habitat. Mapping is an effective approach for wildlife habitat evaluation and monitoring. The application of recently developed artificial intelligence tools, including expert systems an
Reihani, Kamran; Thompson, Wiley E.
The proposed artificial intelligence-based vision model incorporates natural recognition processes depicted as a visual pyramid and hierarchical representation of objects in the database. The visual pyramid, with based and apex representing pixels and image, respectively, is used as an analogy for a vision system. This paper provides an overview of recognition activities and states in the framework of an inductive model. Also, it presents a natural vision system and a counterpart expert system model that incorporates the described operations.
Hoppe, Patricia Anne
Outcomes of a project designed to develop the knowledge base necessary for creating an expert system that would help nonprofit organizations select fund-raising software are presented in this paper. When the system is completed, its components will ask the user for information that will assist in determining the organization's administrative needs…
Describes the development of a prototype Web-based database selection expert system at the University of Illinois at Urbana-Champaign that is based on reference librarians' database selection strategy which allows users to simultaneously search all available databases to identify those most relevant to their search using free-text keywords or…
Verhodubs, O; Grundspeņķis, J
The paper presents a conception of the Semantic Web Expert System which is the logical continuation of the expert system development. The Semantic Web Expert System emerges as the result of evolution of expert system concept and it means expert system moving toward the Web and using new Semantic Web technologies. The proposed conception of the Semantic Web Expert System promises to have new useful features that distinguish it from other types of expert systems
This report describes the activities of the research project entitled 'Development of a Vibration Pattern and Maintenance-data Based Expert System...', in the period from January 1994 to November 1994. In keeping with the detailed work plan for the past 12 months we have: developed of the prototype expert system of MCPs including knowledge base development, maintenance event data base development, tuning of the users interface; tested and tuned the system, with respect to the users' requirements; enlarged the preliminary knowledge base related to the behaviour of MCPs of WWER type NPPs; developed a prototype expert system using LEVEL5 object, together with the MMI and KB mentioned above. The ARGUS-E expert system is design to support the maintenance personnel, and wants to be a tool on the palette of the state dependent maintenance or RCM. To enlarge the knowledge base we used the measuring and diagnostic experience gathered with ARGUS diagnostic systems, at Paks (Hungary) NPP, and by the maintenance personnel of the power plant. (author). 7 refs, 2 figs
Full Text Available Hepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus. The virus interferes with the function of the liver while replicating in hepatocytes. It is a major global health problem and the most serious type of viral hepatitis. Chronic liver disease is caused by viral hepatitis and putting people at high risk of death from cirrhosis of the liver and liver cancer. Medical information available is extensive and which is utilized by the clinical specialists. The ranging of information is from details of clinical symptoms to various types of biochemical data. Information provided by each data is evaluated and assigned to a particular pathology during the diagnostic process. Artificial intelligence methods especially computer aided diagnosis and artificial neural networks can be employed to streamline the diagnostic process. These adaptive learning algorithms can handle diverse types of medical data and integrate them into categorized outputs. Artificial neural networks are finding many uses in the medical diagnosis application. In this study we have proposed a Generalized Regression Neural Network (GRNN based expert system for the diagnosis of the hepatitis B virus disease. The system classifies each patient into infected and non-infected. If infected then how severe it is in terms of intensity rate.
The components and functioning of the GPCS information system is described as applied for process monitoring and alarm generation in WWER-440 type nuclear power plant. The prototype system was developed by using the G2 real-time expert system shell, measurements were simulated by a WWER-440 compact simulator and by the archive replay of a core monitoring system. The benefits of the object oriented technology description, expert system approach and information integration are emphasized. (author) 21 refs.; 17 figs
Full Text Available Expert systems are built with the help of: specialised programming languages or expert system generators (shell. But this structure was reached after tens of years of work and research, because expert systems are nothing but pragmatic capitalisation of the results of research carried out in artificial intelligence and theory of knowledge.
Amany Ramadan Taha
The research discusses the use and usefulness of Agricultural Expert Systems as information source, Those Expert Systems as very important supporting tools for helping people in the decision making process, also this research discusses the role of Central laboratory of Agricultural Expert Systems (CLAES) to support and development the Agricultural Expert System as the main supportive unit to Agricultural Expert Systems in Egypt
The expert system developed to improve the monitoring of purification cycles in nuclear fuel reprocessing plants is biefly described and its adaptation to optimization in the chemical industry is considered
Talebzadeh, Houman; Mandutianu, Sanda; Winner, Christian F.
Countrywide loan-underwriting expert system (clues) is an advanced, automated mortgage-underwriting rule-based expert system. The system was developed to increase the production capacity and productivity of Countrywide branches, improve the consistency of underwriting, and reduce the cost of originating a loan. The system receives selected information from the loan application, credit report, and appraisal. It then decides whether the loan should be approved or whether it requires further rev...
Ibrahiem Abdul Razak Al-Hadu; Lariyah Mohd Sidek; Mohamed Nor Mohamed Desa; Noor Ezlin Ahmad Desa
Construction activities generate enormous amount of erosion and sediments that are the result of soil disturbance during construction activities, thus, will pollute the adjacent water bodies and make it unfeasible for different uses. This paper aimed to develop and create the main features of an expert system prototype (ESCES) for minimising erosion and sedimentation due to stormwater generated from the construction activities by recommending a feasible BMPs. Multi criteria Analysis (MCA) tec...
Jingwen Tian; Meijuan Gao; Yonggang He
Since the control system of the welding gun pose in whole‐position welding is complicated and nonlinear, an intelligent control system of welding gun pose for a pipeline welding robot based on an improved radial basis function neural network (IRBFNN) and expert system (ES) is presented in this paper. The structure of the IRBFNN is constructed and the improved genetic algorithm is adopted to optimize the network structure. This control system makes full use of the characteristics of the IRBFNN...
Gevarter, W. B.
An expert system is defined and its basic structure is discussed. The knowledge base, the inference engine, and uses of expert systems are discussed. Architecture is considered, including choice of solution direction, reasoning in the presence of uncertainty, searching small and large search spaces, handling large search spaces by transforming them and by developing alternative or additional spaces, and dealing with time. Existing expert systems are reviewed. Tools for building such systems, construction, and knowledge acquisition and learning are discussed. Centers of research and funding sources are listed. The state-of-the-art, current problems, required research, and future trends are summarized.
Li, Guiquing; Ge, Qihong; Zhong, Luo; Xie, Weiping
The design of many industrial and engineering systems can often be accomplished using flow graphs of various types. Examples include manufacturing processes and data processing applications, Graph Transformation Expert System, is an expert system which has been developed by WUT for applying techniques of artificial intelligence to the architectural design of data and signal processing systems. Software and hardware architectures may be defined for such systems using data flow graphs, in which nodes represent data processing steps and directed areas represent the `flow' of data between the processing steps. Starting with a user- defined generic processing graphic, this expert will transform the graph by applying transformation rules in order to specialize the processing graph to satisfy specified design goals and/or hardware constraints. Although the particular application for which this expert is designed is that of data and signal processing systems, it can provide an expert system framework for other problems specified graphically; for example, manufacturing systems, information systems, and product distribution systems.
Ibrahiem Abdul Razak Al-Hadu
Full Text Available Construction activities generate enormous amount of erosion and sediments that are the result of soil disturbance during construction activities, thus, will pollute the adjacent water bodies and make it unfeasible for different uses. This paper aimed to develop and create the main features of an expert system prototype (ESCES for minimising erosion and sedimentation due to stormwater generated from the construction activities by recommending a feasible BMPs. Multi criteria Analysis (MCA technique has been integrated so as to select the best control measure among many stormwater control alternatives. A questionnaire has been distributed to the relevant experts so as to rank the stormwater control measures to be used in the MCA technique. Using Visual Basic 6, Graphical User Interfaces (GUIs were developed. The knowledge and experience were acquired from various textural sources (i.e. guidelines, manuals, literature, and humanexpert. Results from this study showed that the Best Management Practices (BMPs recommended have good suited the site characteristics as the relevant experts have showed their convenience to the developed prototype since they asked to fill in simple questionnaire after developing the system and presented to them. The conclusion drawn from this study indicates that the ESCES can be considered as “Green Technology Tool” since it helps in protecting the environment and preserve good quality of water adjacent to the construction sites in Malaysia.
The great debate concerning the Italian high-school reform has induced a ferment of activity among the most interested and sensible of people. This was clearly demonstrated by the course 'Innovazione metodologico-didattica e tecnologie informatiche' organized for the staff of the 'lstituto Professionale L. Einaudi' of Lamezia Terme. The course was an interesting opportunity for discussions and interaction between the world of School and computer technology used in the Research field. This three day course included theoretical and practical lessons, showing computer facilities that could be useful for teaching. During the practical lessons some computer tools were presented from the very simple Electronic Sheets to the more complicated information Retrieval on CD-ROM interactive realizations. The main topics will be discussed later. They are: Modelling, Data Base, Integrated Information Systems, Expert Systems, Information Retrieval. (author)
Henrion, Max; Breese, John S.; Horvitz, Eric J.
Decision analysis and expert systems are technologies intended to support human reasoning and decision making by formalizing expert knowledge so that it is amenable to mechanized reasoning methods. Despite some common goals, these two paradigms have evolved divergently, with fundamental differences in principle and practice. Recent recognition of the deficiencies of traditional AI techniques for treating uncertainty, coupled with the development of belief nets and influence diagrams, is stimu...
Gonzelez, Avelino J.; Ragusa, James M.
Artificial intelligence (AI) technology, and in particular expert systems, has shown potential applicability in many areas of operation at the Kennedy Space Center (KSC). In an era of limited resources, the early identification of good expert system applications, and their segregation from inappropriate ones can result in a more efficient use of available NASA resources. On the other hand, the education of students in a highly technical area such as AI requires an extensive hands-on effort. The nature of expert systems is such that proper sample applications for the educational process are difficult to find. A pilot project between NASA-KSC and the University of Central Florida which was designed to simultaneously address the needs of both institutions at a minimum cost. This project, referred to as Expert Systems Prototype Training Project (ESPTP), provided NASA with relatively inexpensive development of initial prototype versions of certain applications. University students likewise benefit by having expertise on a non-trivial problem accessible to them at no cost. Such expertise is indispensible in a hands-on training approach to developing expert systems.
李蓓智; 杨建国; 周亚勤; 邵世煌
Based on the biological immune concept, immune response mechanism and expert system, a dynamic and intelligent scheduling model toward the disturbance of the production such as machine fault,task insert and cancel etc. Is proposed. The antibody generation method based on the sequence constraints and the coding rule of antibody for the machining procedure is also presented. Using the heuristic antibody generation method based on the physiology immune mechanism, the validity of the scheduling optimization is improved, and based on the immune and expert system under the event-driven constraints, not only Job-shop scheduling problem with multi-objective can be solved, but also the disturbance of the production be handled rapidly. A case of the job-shop scheduling is studied and dynamic optimal solutions with multi-objective function for agile manufacturing are obtained in this paper. And the event-driven dynamic rescheduling result is compared with right-shift rescheduling and total rescheduling.
This paper presents a new method for the correct selection of mining methods and prediction of main technological and economic indexes of the face in the gentle inclined thick seams with the application of the artificial neural network theory and the expert system. The theory analysis and calculating results indicate that the method is reliable, practical and precise. This method has strongly capabilities of self-study and non-linear dynamic data process. It is expected to be widely applied in the policy decision and prediction of mining technology in coal mine.
Oluwatoyin Catherine Agbonifo
Full Text Available Artificial intelligence (AI is the core of computing research that makes machine to mimic the intelligence of a man. Intelligent means less of user interaction and automated adaptation to changing environment. When compared to other primitive techniques used in the past, AI has been highly efficient in knowledge acquisition in diverse areas of application. In the light of this, the paper focuses on intelligent technique of determining the possible diseases that affect the life of cattle. Hence, fuzzy expert technique is proposed for the diagnosis of the Antrax, Babesiosis, Blackleg and Epizootic Hemorrrhapic diseases. The result generated by the system was sufficient to demonstrate its performance.
This report describes Jess, a clone of the popular CLIPS expert system shell written entirely in Java. Jess supports the development of rule-based expert systems which can be tightly coupled to code written in the powerful, portable Java language. The syntax of the Jess language is discussed, and a comprehensive list of supported functions is presented. A guide to extending Jess by writing Java code is also included.
Full Text Available Some remarks on the problem of knowledge representation and processing, as recognized in connection with the use of computers in the scientific research work, emphasizes the relevance of these problems for the studies on both the theory of languages and the expert system. A consideration of the common traits in the recent history of these studies, with reference to the use of computers on texts in natural language motivates the introduction of set theoretic and algebraic methods, suitable for applications in the analysis and in the automatic treatment of languages, based on the concept of model sets and on relational structures suggested from the connections between syntax and semantics evidenced in some example of sub-languages corresponding to theories of different classes of physical phenomena. Some details of these methods are evidenced, which have already successfully used or whose applications appears suggestive of interesting development.
The applicability of artificial intelligence methodologies for the automation of energy storage management, in this case, nickel cadmium batteries, is demonstrated. With the Hubble Space Telescope Electrical Power System (HST/EPS) testbed as the application domain, an expert system was developed which incorporates the physical characterization of the EPS, in particular, the nickel cadmium batteries, as well as the human's operational knowledge. The expert system returns not only fault diagnostics but also status and advice along with justifications and explanations in the form of decision support.
This paper reports on an expert system for generating control rod patterns that has been developed. The knowledge is transformed into IF-THEN rules. The inference engine uses the Rete pattern matching algorithm to match facts, and rule premises and conflict resolution strategies to make the system function intelligently. A forward-chaining mechanism is adopted in the inference engine. The system is implemented in the Common Lisp programming language. The three-dimensional core simulation model performs the core status and burnup calculations. The system is successfully demonstrated by generating control rod programming for the 2894-MW (thermal) Kuosheng nuclear power plant in Taiwan. The computing time is tremendously reduced compared to programs using mathematical methods
This work develops a prototype for the system model based on Artificial Intelligence devices able to perform functions related to scintigraphic image analysis of the urinary system. Criteria used by medical experts for analysis images obtained with 99m Tc+DTPA and/or 99m Tc+DMSA were modeled and a multi resolution diagnosis technique was implemented. Special attention was given to the programs user interface design. Human Factor Engineering techniques were considered so as to ally friendliness and robustness. Results obtained using Artificial Neural Networks for the qualitative image analysis and the knowledge model constructed shows the feasibility of Artificial Intelligence implementation that use 'inherent' abilities of each technique in the resolution of diagnosis image analysis problems. (author). 12 refs., 2 figs., 2 tabs
Feasible strategies for automatic BWR control rod pattern generation have been implemented in a rule-based expert system. These strategies are majorly based on a concept for which exposure distributions are hovering around the Haling exposure distribution through a cycle while radial and axial power distributions are dominantly controlled by some abstracted factors indicating the desired distributions. The system can either automatically generate expert-level control rod patterns or search for criteria-satisfied patterns originated from user's input. It has successfully been demonstrated by generating control rod patterns for the the 1775 MWth Chinshan plant in Unit I Cycle 13 alternate loading pattern and Unit 2 Cycle 8 but with longer cycle length. All rod patterns for two cycles result in all-rod-out at EOC and no violation against the four criteria. The demonstrations show that the system is considerably good in choosing initial trial rod patterns and adjusting rod patterns to satisfy the design criteria. (author)
In 1990, an expert system for turbo-generator diagnostics (EST-D) was installed at the 3rd and 4th units of the Paks NPP (Hungary). The expert system is strongly integrated to the ARGUS II vibration monitoring and diagnostics system. The system works on IBM PC AT. The VEIKI's and the NPP's human experts were interviewed to fill up the knowledgebase. The system is able to identify 13 different faults of the parts of a turbogenerator. The knowledgebase consists of ca 200 rules. The rules were built in and the system was verified and validated using a model of the turbines and using the experiences gathered with ARGUS II during the last 3 years. The maintenance personnel is authorized to modify and/or extend the knowledgebase. The input data for evaluation come from measured vibration patterns produced by the ARGUS II system, database of events, and maintenance data input by the maintenance personnel. The expert system is based on the modified GENESYS 2.1 shell (developed by SZAMALK, Hungary). Some limitations from PC application were eliminated, and a new, independent explanation module and man-machine interface were developed. Using this man-machine interface, one of the basic goals of the expert system developments was achieved: the human experts contribution is not necessary for diagnoses. The operator of the diagnostics system is able to produce the reports of diagnoses. Of course the interface allows the human experts to see the diagnoses through. It should be mentioned, at the beginning of 1991, we installed a similar expert system at the 1st 1000 MW WWER type unit of the Kalinin NPP (Soviet Union). In this paper, the operation of the EST-D, the man-machine interface and the operational experiences of the first 4 months work are explained. 2 refs., 14 figs
An Expert System Development (ESD) Shell design implementation is desribed in detail. The shell provides high-level generic facilities for Knowledge Representation (KR) and inferencing and tools for developing user interfaces. Powerful set of tools in the shell relieves much of the programming burden in the ES development. The shell is written in PROLOG under IBM PC/AT. KR facilities are based on two very powerful formalisms namely, frames and rules. Inference Engine (IE) draws most of its power from unification and backward reasoning strategy in PROLOG. This basic mechanism is enhanced further by incorporating both forward and backward chaining of rules and frame-based inferencing. Overall programming style integrates multiple paradigms including logic, object oriented, access-oriented and imperative programming. This permits ES designer a lot of flexibility in organizing inference control. Creation and maintainance of knowledge base is a major activity. The shell, therefore, provides number of facilities to simplify these tasks. Shell design also takes note of the fact that final success of any system depends on end-user satisfaction and hence provides features to build use-friendly interfaces. The shell also provides a set of interfacing predicates so that it can be embedded within any PROLOG program to incorporate functionalilty of the shell in the user program. (author). 10 refs., 8 figs
Full Text Available Since the control system of the welding gun pose in whole‐position welding is complicated and nonlinear, an intelligent control system of welding gun pose for a pipeline welding robot based on an improved radial basis function neural network (IRBFNN and expert system (ES is presented in this paper. The structure of the IRBFNN is constructed and the improved genetic algorithm is adopted to optimize the network structure. This control system makes full use of the characteristics of the IRBFNN and the ES. The ADXRS300 micro‐mechanical gyro is used as the welding gun position sensor in this system. When the welding gun position is obtained, an appropriate pitch angle can be obtained through expert knowledge and the numeric reasoning capacity of the IRBFNN. ARM is used as the controller to drive the welding gun pitch angle step motor in order to adjust the pitch angle of the welding gun in real‐time. The experiment results show that the intelligent control system of the welding gun pose using the IRBFNN and expert system is feasible and it enhances the welding quality. This system has wide prospects for application.
There is a processing need for a fast, easy and accurate classification system for oil palm fruit ripeness. Such a system will be invaluable to farmers and plantation managers who need to sell their oil palm fresh fruit bunch (FFB) for the mill as this will avoid disputes. In this paper,a new approach was developed under the name of expert rules-based systembased on the image processing techniques results of thethree different oil palm FFB region of interests (ROIs), namely; ROI1 (300x300 pixels), ROI2 (50x50 pixels) and ROI3 (100x100 pixels). The results show that the best rule-based ROIs for statistical colour feature extraction with k-nearest neighbors (KNN) classifier at 94% were chosen as well as the ROIs that indicated results higher than the rule-based outcome, such as the ROIs of statistical colour feature extraction with artificial neural network (ANN) classifier at 94%, were selected for further FFB ripeness inspection system
Abdel Nasser H. Zaied; Samah Ibrahim Abdel Aal; Mohamed Monir Hassan
Information Systems (IS) are increasingly becoming regarded as crucial to an organization's success. Information Systems Development Methodologies (ISDMs) are used by organizations to structure the information system development process. ISDMs are essential for structuring project participants’ thinking and actions; therefore ISDMs play an important role to achieve successful projects. There are different ISDMs and no methodology can claim that it can be applied to any organization. The probl...
The expert systems development within a real time context, requires both to master the necessary reasoning about the time as well as to master the necessary response time for reasoning. Although rigorous temporal logic formalisms exist, strategies for temporal reasoning are either incomplete or else imply unacceptable response times. The first part presents the logic formalism upon which is based the production system. This formalism contains a three-valued logic system with truth-valued matrix, and a deductive system with a formal system. It does a rigorous work for this no standard logic, where the notions of consistency and completeness can be studied. Its development supports itself on the will to formalise the reasoning used at the elaboration time of the strategies to make them more explicit as the natural deduction method. The second part proposes an extension for the source logic formalism to take explicitly the time into account. The approach proposed through 'TANIS', the prototype of such an expert system shell, using a natural reasoning application is proposed. It allows, at the generation time, the implementation within the expert system, of an adapted deduction strategy to the symbolic temporal reasoning which is complete and ease the determination of the response time. (author)
High-temperature environmental attack often limits the useful service life of the hot section components in gas turbines, for aircraft, marine and industrial applications. High-temperature coatings are mandatory to obtain acceptable service life, but the life of these coatings often determines the refurbishment intervals. This paper addresses the use of computerized data bases and expert systems for high-temperature corrosion and high-temperature coatings, which have not always been useful fo...
Health problem is still a crucial one in some countries. It is so important that it becomes a major handicap in economic and social development. In order to solve this problem, we have conceived an expert system that we called MITSABO, which means TO HEAL, to help the physicians to diagnose tropical diseases. It is clear that by extending the data base and the knowledge base, we can extend the application of the software to more general areas. In our expert system, we used the concept of 'self organization' of neural network based on the determination of the eigenvalues and the eigenvectors associated to the correlation matrix XXt. The projection of the data on the two first eigenvectors gives a classification of the diseases which is used to get a first approach in the diagnosis of the patient. This diagnosis is improved by using an expert system which is built from the knowledge base.
Renal function can be measured noninvasively with radionuclides in a extremely safe way compared to other diagnosis techniques. Nevertheless, due to the fact that radioactive materials are used in this procedure, it is necessary to maximize its benefits, therefore all efforts are justifiable in the development of data analysis support tools for this diagnosis modality. The objective of this work is to develop a prototype for a system model based on Artificial Intelligence devices able to perform functions related to cintilographic image analysis of the urinary system. Rules used by medical experts in the analysis of images obtained with 99m Tc+DTPA and /or 99m Tc+DMSA were modeled and a Neural Network diagnosis technique was implemented. Special attention was given for designing programs user-interface. Human Factor Engineering techniques were taking in account allowing friendliness and robustness. The image segmentation adopts a model based on Ideal ROIs, which represent the normal anatomic concept for urinary system organs. Results obtained using Artificial Neural Networks for qualitative image analysis and knowledge model constructed show the feasibility of Artificial Neural Networks for qualitative image analysis and knowledge model constructed show feasibility of Artificial Intelligence implementation that uses inherent abilities of each technique in the medical diagnosis image analysis. (author)
Yasser A. Nada
Full Text Available The Extensible Markup Language (XML is a subset of SGML that is completely described in this paper. Its goal is to enable generic SGML to be served, received, and processed on the Web in the way that is now possible with HTML. XML has been designed for ease of implementation and for interoperability with both SGML and HTML. An expert system is a computer program designed to simulate the problem-solving behavior of a human who is an expert in a narrow domain or discipline. Expert Systems (ES, also called Knowledge Based System (KBS, are computer application programs that take the knowledge of one or more human experts in a field and computerize it so that it is readily available for use. The main objective of this paper was to investigate the usage of different refinement methodologies for different layers of knowledge base modeling and investigate the possibility of building an expert system development and refinement tool. In our work we used XML as a knowledge representation to represent the knowledge base. Therefore we used the mathematical model to refinement of a knowledge base.
Lee, S. Daniel
We propose a distributed agent architecture (DAA) that can support a variety of paradigms based on both traditional real-time computing and artificial intelligence. DAA consists of distributed agents that are classified into two categories: reactive and cognitive. Reactive agents can be implemented directly in Ada to meet hard real-time requirements and be deployed on on-board embedded processors. A traditional real-time computing methodology under consideration is the rate monotonic theory that can guarantee schedulability based on analytical methods. AI techniques under consideration for reactive agents are approximate or anytime reasoning that can be implemented using Bayesian belief networks as in Guardian. Cognitive agents are traditional expert systems that can be implemented in ART-Ada to meet soft real-time requirements. During the initial design of cognitive agents, it is critical to consider the migration path that would allow initial deployment on ground-based workstations with eventual deployment on on-board processors. ART-Ada technology enables this migration while Lisp-based technologies make it difficult if not impossible. In addition to reactive and cognitive agents, a meta-level agent would be needed to coordinate multiple agents and to provide meta-level control.
The advisory expert system MAESTRO (Modular Advisory Expert System for Test Rig Operator) has been designed to guide the operator of large experimental installation during start-up, steady state and shut down. The installation is located in the research reactor MARIA in the Institute of Atomic Energy in Swierk, Poland. The system acquires and analyses on line signals from installation and performs two tasks in real time: leading the operator and monitoring of the installation (including signal validation). Systems tasks, architecture and knowledge representation concepts are described. The system is based on expert systems techniques what makes in phases of continuous change of process parameters and it has been achieved by special knowledge representation allowing its dynamical modification. (author). 147 refs, 42 figs, 5 tab
One dominant aspect of improvement in safe nuclear power plant operation is the very high speed in the development and introduction of computer technologies. This development commenced recently when advanced control technology was incorporated into the nuclear industry. This led to an increasing implementation of information displays, annunciator windows and other devices inside the control room, eventually overburdening the control room operator with detailed information. Expert systems are a further step in this direction being designed to apply large knowledge bases to solve practical problems. These ''intelligent'' systems have to incorporate enough knowledge to reach expert levels of importance and represent a very advanced man-machine interface. The aims of the Technical Committee were addressed by the three Working Groups and summarized in Sections 2, 3 and 4 of this report. Section 2 summarizes the results and discussions on the current capabilities of expert systems and identifies features for the future development and use of Expert Systems in Nuclear Power Plants. Section 3 provides an overview of the discussions and investigations into the current status of Expert Systems in NPPs. This section develops a method for assessing the overall benefit of different applications and recommends a broad strategy for priority developments of Expert Systems in NPPs. Section 4 assesses the overall use of PSA type studies in Expert Systems in NPPs and identifies specific features to be adopted in the design of these systems in future applications. The conclusions of the three Working Groups are presented in Section 5. The 15 papers presented at the meeting formed the Annex of this document. A separate abstract was prepared for each of these papers. Refs, figs, tabs and pictures
A network of distributed expert systems is the heart of a prototype supervisory control architecture developed at the Oak Ridge National Laboratory (ORNL) for an advanced multimodular reactor. Eight expert systems encode knowledge on signal acquisition, diagnostics, safeguards, and control strategies in a hybrid rule-based, multiprocessing and object-oriented distributed computing environment. An interactive simulation of a power block consisting of three reactors and one turbine provides a realistic, testbed for performance analysis of the integrated control system in real-time. Implementation details and representative reactor transients are discussed
One of the largest area of applications of artificial intelligence is in expert systems, or knowledge based systems as they are often known. This type of system seeks to exploit the specialised skills or information held by group of people on specific areas. It can be thought of as a computerised consulting service. It can also be called an information guidance system. Such systems are used for prospecting medical diagnosis or as educational aids. They are also used in engineering and manufac...
Intelligent control is a very successful way to transform the expert's knowledge of the type 'if the velocity is big and the distance from the object is small, hit the brakes and decelerate as fast as possible' into an actual control. To apply this transformation, one must choose appropriate methods for reasoning with uncertainty, i.e., one must: (1) choose the representation for words like 'small', 'big'; (2) choose operations corresponding to 'and' and 'or'; (3) choose a method that transforms the resulting uncertain control recommendations into a precise control strategy. The wrong choice can drastically affect the quality of the resulting control, so the problem of choosing the right procedure is very important. From a mathematical viewpoint these choice problems correspond to non-linear optimization and are therefore extremely difficult. In this project, a new mathematical formalism (based on group theory) is developed that allows us to solve the problem of optimal choice and thus: (1) explain why the existing choices are really the best (in some situations); (2) explain a rather mysterious fact that fuzzy control (i.e., control based on the experts' knowledge) is often better than the control by these same experts; and (3) give choice recommendations for the cases when traditional choices do not work.
The idea of developing artificial intelligence (AI) systems to capture the knowledge of human experts is receiving much attention these days. The idea is even more attractive when important expertise resides within a single individual, especially one who is nearing retirement and who has not otherwise recorded or passed along his important knowledge and thought processes. The diesel generators at Pilgrim Nuclear Power Station have performed exceptionally well, primarily due to the care and attention of one man. Therefore, the authors are constructing an expert system for the diagnosis of diesel generator problems at Pilgrim. This paper includes a description of the expert system design and operation, examples from the knowledge base, and sample diagnoses, so the reader can observe the process in action
Full Text Available The inherent characteristics of fuzzy logic theory make it suitable for fault detection and diagnosis (FDI. Fault detection can benefit from nonlinear fuzzy modeling and fault diagnosis can profit from a transparent reasoning system, which can embed operator experience, but also learn from experimental and/or simulation data. Thus, fuzzy logic-based diagnostic is advantageous since it allows the incorporation of a-priori knowledge and lets the user understand the inference of the system. In this paper, the successful use of a fuzzy FDI based system, based on dynamic fuzzy models for fault detection and diagnosis of an industrial two tank system is presented. The plant data is used for the design and validation of the fuzzy FDI system. The validation results show the effectiveness of this approach.
Yekini Nureni Asafe; Adetoba Bolaji; Aigbokhan Edwin Enaholo; Olufemi Olubukola
The use of Information Technologies have played and currently playing prominent roles in many organizations, such as business, education, commerce. The tourism industry has witnessed the use and application of various computer-based systems in carrying out one or more activities or operation. But currently there is no computer-based system tourist destination to integrate the tourists (from outside Nigeria) and tourists center within Nigeria, so that tourists can make a pre destination plan a...
With a new way of knowledge representation and acquirement, inference, and building an expert system based on big-neurons composed of different field expert knowledge presented, the fundamental theory and architecture of expert system based upon big-neuron theory has thus been built. It is unnecessary to organize a large number of production rules when using big-neurons to build an expert system. The facts and rules of an expert system have already been hidden in big-neurons. And also, it is unnecessary to do a great quantity of tree searching when using this method to do logic reasoning. Machine can do self-organizing and self-learning.
Van Hecke, T.
Students wanting to succeed in higher education are required to adopt an adequate learning approach. By analyzing individual learning characteristics, teachers can give personal advice to help students identify their learning success factors. An expert system based on fuzzy logic can provide economically viable solutions to help students identify…
Healy, Michael J.
The generalization properties of a class of neural architectures can be modelled mathematically. The model is a parallel predicate calculus based on pattern recognition and self-organization of long-term memory in a neural network. It may provide the basis for adaptive expert systems capable of inductive learning and rapid processing in a highly complex and changing environment.
The general growth of expert, knowledge-based (KB) or rule based systems will significantly increase in the next three to five years. Improvements in computer hardware (speed, reduced size, power) and software (rule based, data based, user interfaces) in recent years are providing the foundations for the growth of expert systems. A byproduct of this growth will undoubtedly be the application of expert systems to various safeguards problems. Characteristics of these expert systems will involve 1) multiple rules governing an outcome, 2) confidence factors on individual variables and rule sets, 3) priority, cost, and risk based rule sets, and 4) the reasoning behind the advice or decision given by the expert system. This paper presents characteristics, structures, and examples of simple rule based systems. Potential application areas for these expert systems may include training, operations, management, designs, evaluations, and specific hardware operation
Full Text Available This is era of knowledge and information. One very major task that has been evolved now a day is to mine a knowledge base. On the other hand expert systems are used extensively in many domains. There are many applications of expert systems for predicting and finding a feasible solution for any particular problem. Various tools also have been evolves for upgrading and modifying the existing expert systems and making them more useful in their intended purposes. The current paper explains the expert systems that use cluster analysis as a tool and briefly discusses few such expert systems.
The Dempster-Shafer theory has been extended recently for its application to expert systems. However, implementing the extended D-S reasoning model in rule-based systems greatly complicates the task of generating informative explanations. By implementing GERTIS, a prototype system for diagnosing rheumatoid arthritis, we show that two kinds of knowledge are essential for explanation generation: (l) taxonomic class relationships between hypotheses and (2) pointers to the rules that significantl...
Artificial intelligence is an emerging technology in the field of computer application. Expert systems have been developed to imitate human intelligence and reasoning process. Expert systems have much scope of application in the decision making process in mineral exploration as such decisions are highly subjective and expert opinions are very helpful. This paper presents a small expert system to analyze the reasoning process in exploring for uranium deposits in sandstone
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ENGLISH ABSTRACT: Artificial intelligence techniques are rapidly emerging as important contributors to more effective management. One of the greatest growth areas probably lies in the use of Expert System methodology for supporting managerial decision processes.
Existing Decision Support Systems often attempt to apply analytical techniques in combination with traditional data access and retrieval functions. One of the problems usually encountered while developing such decision support systems is the need to transform an unstructured problem environment into a structured analytical model. Using an expert system approach to strategic decision making in such unstructured problem environments may provide significant advantages.
The financial Risk diagnostic EXpert System (REXS concentrates on Financial Risk Analysis. Based on a Forecasting Model the system will, with the support of several expert system knowledge bases, attempt to evaluate the financial risk of a business and provide guidelines for improvement.
AFRIKAANSE OPSOMMING: Tegnieke gebaseer op Kunsmatige Intelligensie toon tans die belofte om belangrike bydraes te maak tot meerBestaande Besluitsteunstelsels poog dikwels om analitiese tegnieke en lradisionele datatoegang- en onttrekkingsfunksies te kombineer. Een van die probleme wat gewoonlik ondervind word gedurende die ontwikkeling van '0 besluitsteunstelsel bestaan uit die behoefte om 'n ongestruktueerde probleemomgewing te transformeer na 'n gestruktueerde analitiese model. 'n Ekspertstelselbenadering lot strategiese besluitneming in 'n ongeSlruktureerde probleemomgewing mag betekenisvolle voordele inhou.
Die "financial Risk diagnostic EXpert System (REXS" konsentreer op fmansiele risiko-analise. Uitgaande vanaf 'n Vooruitskattingsmode~ en deur gebruik te maak van verskeie ekspertstelselkennisbasisse, poog die stelsel om die fmansiele risiko van 'n onderneming te evalueer en riglyne vir moontlike verbetering
Espinosa R, Alfredo; Quintero R, Agustin; Zambrano D, S Venecia [Instituto de Investigaciones Electricas, Cuernavaca, Morelos (Mexico)
This article presents the development of an Expert System based in the Reasoning Based on Cases methodology. Such system was performed with the purpose of creating an information system in charge of supervising and diagnosing the status of the main equipment of fossil fuel power plants for electricity generation. Here is presented the reasons why this methodology was used for the expert system and why Induce-It -the specialized tool that implements it- was also chosen, as well as the analysis made for the disposition of the operative architecture of the Expert System, the very development of this software architecture and, finally, the validation of the correct operation of this system by means of a simulator that simultaneously puts to the test the error handling of the Expert System. [Spanish] Este articulo presenta el procedimiento que siguio el desarrollo de un Sistema Experto asentado en la metodologia de Razonamiento Basado en Casos; realizado con el fin de crear un sistema de informacion encargado de supervisar y diagnosticar el estado de los equipos principales de centrales de generacion termoelectrica. Se expone justificadamente la seleccion de la metodologia del sistema experto y de la herramienta especializada que lo implementa (Induce-It), asi como el analisis realizado para la disposicion de la arquitectura operativa del Sistema Experto, el desarrollo mismo de esta arquitectura del software y, finalmente, la validacion del correcto funcionamiento de este sistema mediante un simulador que a la vez pone a prueba el manejo de errores del Sistema Experto.
Transuranic wastes are generated at the Savannah River Site (SRS) as a result of routine production of nuclear materials. These wastes contain Pu-238 and Pu-239 and are placed into lined 55-gallon waste drums. The drums are placed on monitored storage pads pending shipment to the Waste Isolation Pilot Plant in New Mexico. A passive-active neutron (PAN) assay system is used to determine the mass of the radioactive material within the waste drums. Assay results are used to classify the wastes as either low-level or transuranic (TRU). During assays, the PAN assay system communicates with an IBM-AT computer. A Fortran computer program, called NEUT, controls and performs all data analyses. Unassisted, the NEUT program cannot adequately interpret assay results. To eliminate this limitation, an expert system shell was used to write a new algorithm, called the Transuranic Expert System (TRUX), to drive the NEUT program and add decision making capabilities for analysis of the assay results. The TRUX knowledge base was formulated by consulting with human experts in the field of neutron assay, by direct experimentation on the PAN assay system, and by observing operations on a daily basis. TRUX, with its improved ability to interpret assay results, has eliminated the need for close supervision by a human expert, allowing skilled technicians to operate the PAN assay system. 4 refs., 1 fig., 4 tabs
李义兵; 何红波; 周继承; 李斌
Expert systems have been used widely in the predictions and design of alloy systems. But the expert systems are based on the macroscopic models that have no physical meanings. Microscopic molecular dynamics is also a standard computational technique used in materials science. An approach is presented to the design system of nonferrous alloy that integrates the molecular dynamical simulation together with an expert system. The knowledge base in the expert system is able to predict nonferrous alloy properties by using machine learning technology. The architecture of the system is presented.
Irena L. ATANASOVA
Full Text Available One of the most important challenges the European Union was facing at the beginning of the 21st century was to balance economic development with the improvement of quality of its citizens life. A new approach for assessing the quality of life using the ten-degree global scale is revealed in this article. The aptness of this approach to exploring the social area and determining the quality of life of people in different countries and regions are also discussed. There are being examined some practical aspects of setting up an expert system for social area.The article describes the implementation of such a system for evaluating the quality of life – QLIFEX. The expert system is an innovative research project based entirely on qualitative methods, which aims at helping in understanding of how in an era of great changes residents from different countries live and work in diverse economic organizations, and how they would rate their work and life.
Lefrançois, Maxime; Gandon, Fabien
We are interested in bridging the world of natural language and the world of the semantic web in particular to support multilingual access to the web of data, and multilingual management of interlingual knowledge bases. In this paper we introduce the ULiS project, that aims at designing a pivot-based NLP technique called Universal Linguistic System, 100% using the semantic web formalisms, and being compliant with the Meaning-Text theory. Through the ULiS, a user could interact with an Interli...
The Reactor Systems Section of Oak Ridge National Laboratory's Instrumentation and Controls Division has been developing expertise in the application of artificial intelligence (AI) tools and techniques to control complex systems. One of the applications developed demonstrates the capabilities of a rule-based expert system to monitor a nuclear reactor. Based on the experience acquired with the demonstration described in this paper, a 2-yr program was initiated during fiscal year 1985 for the development and implementation of an intelligent monitoring adviser to the operators of the HFIR facility. The intelligent monitoring system will act as an alert and cooperative expert to relieve the operators of routine tasks, request their attention when abnormalities are detected, and provide them with interactive diagnostic aid and project action/effects information as needed or on demand
This paper develops expert system called NPiES (nuclear piping integrity Expert System) for nuclear piping integrity. The structure and development strategies of NPiES system are described. NPiES system is consisted of 5 parts; database, knowledge base, inference engine, integrity evaluation and utilities. Nuclear piping material properties are stored in the database and various rules recommended by Code and Standard are stored in the knowledge base. Unavailable material properties are inferred in the inference engine using NEXPERT object through inferring the given material properties. In the integrity evaluation part, various evaluation methods such as LEFM, EPFM, limit load method and fatigue analysis are provided. (author). 5 refs., 4 figs., 2 tabs
Flandrois, J; Carret, G
Artificial intelligence is a part of computer science that deals with programs mimicking intelligence of man. Artificial intelligence is now used to check the quality of the determination of antibiotics susceptibility of bacteria. This application is useful because antibiotic susceptibility is subject to biological and technical variation that have to be detected. Three types of reasoning are used either by the biologist or by expert systems: low level quality checking dealing with individual results, microbiological interpretation of the whole set of results and medical interpretation of the results. The use of artificial intelligence in these fields is sustained by the structured nature of the knowledge. Two type of expert systems are already of routine use, either based on production rules (ATB plus EXPERT, bioMerieux, La Balme-les-Grottes, France and SIR, 12A, Montpellier, France), or on object-oriented representation of the knowledge (EXPRIM from our laboratory). The main problem is, as usually in artificial intelligence applications, to transfer human expertise into an adapted knowledge base. The advantage of experts systems over man are their reproducibility of answer and their availability. PMID:2064087
Trnka, Hjalte; Wu, Jian-Xiong; van de Weert, Marco;
biosimilarity concept complicate the development phase of safe and cost-effective drug products. To streamline the development phase and to make high-throughput formulation screening possible, efficient solutions for analyzing critical quality attributes such as cake quality with minimal material consumption...... are needed. The aim of this study was to develop a fuzzy logic system based on image analysis (IA) for analyzing cake quality. Freeze-dried samples with different visual quality attributes were prepared in well plates. Imaging solutions together with image analytical routines were developed for...... extracting critical visual features such as the degree of cake collapse, glassiness, and color uniformity. On the basis of the IA outputs, a fuzzy logic system for analysis of these freeze-dried cakes was constructed. After this development phase, the system was tested with a new screening well plate. The...
Suen, Ching Y
This book is part of a new series on operational expert systems worldwide. Expert systems are now widely used in different parts of the world for various applications. The past four years have witnessed a steady growth in the development and deployment of expert systems in Canada. Research in this field has also gained considerable momentum during the past few years. However, the field of expert systems is still young in Canada. This book contains 13 chapters contributed by 31 experts from both universities and industries across Canada covering a wide range of applications related to electric
A prototype version of Frequency-based On-line Expert System (FBOLES) for Fault Diagnoses in Nuclear Power Plants (NPP) has been developed under the framework of this CRP. This report will summarize the work done during the contract years. The basic concept of FBOLES approach for the on-line fault diagnosis of NPP is introduced, although it has been previously presented in our companion papers. The software developed, namely FBOLES, is an expert shell which can be used for different systems and/or different operating modes. The related work of software development has been documented in this report, which includes its features, functions, software structure, knowledge base, and man-machine interface. The real-time on-line experiment results show many positive features of FBOLES. The main steam and feedwater condensate system (MSFCS, namely the secondary loop) of a NPP (950 MW, three loops) simulated by the Tsinghua simulator has been selected as a target system. The knowledge bases for MSFCS have been constructed. Total 62 signals from the simulator have been selected as the on-line evidences for the diagnosis. 33 fault experiments were performed in which 21 were detected accurately (unique candidate) by FBOLES immediately after the first abnormal signal was received and the other 12 were detected accurately within half to three minutes as the development of abnormality. These experiments include not only the failures of pumps, valves, pipes, etc. of MSFC itself, but also the failures outside MSFCS. Three of them involve non-initiating events. (author). 3 refs, 6 figs, 2 tabs
Slawson, D. C.; Shaughnessy, A. F.
Clinicians rely heavily on expert based systems-consultation with colleagues, journal reviews and textbooks, and continuing education activities-to obtain new information. The usefulness of sources such as these depends on the relevance and validity of the information and the work it takes to obtain it. Useful information can be distinguished from the useless by asking three questions: Does the information focus on an outcome that my patients care about? Is the issue common to my practice, an...
In reference to the status quo of research and the application of the agricultural expert system, this paper analyzes problems existing in the current development, and puts forward the idea of research and development for agriculturespecific software. The agent application is discussed, and an agent-based Agricultural Expert System Inspection Tool is constructed. In addition, this paper addresses the outlook in application, potential problems and the development trend of multi-agent-based inspection software for the agricultural expert system.
Latha B. Kaimal
Full Text Available In a Power plant with a Distributed Control System ( DCS , process parameters are continuously stored in databases at discrete intervals. The data contained in these databases may not appear to contain valuable relational information but practically such a relation exists. The large number of process parameter values are changing with time in a Power Plant. These parameters are part of rules framed by domain experts for the expert system. With the changes in parameters there is a quite high possibility to form new rules using the dynamics of the process itself. We present an efficient algorithm that generates all significant rules based on the real data. The association based algorithms were compared and the best suited algorithm for this process application was selected. The application for the Learning system is studied in a Power Plant domain. The SCADA interface was developed to acquire online plant data.
Applying Artificial Intelligence technology to steam generator non-destructive examination (NDE) can help identify high risk locations in steam generators and can aid in preparing technical specification compliant eddy current test (ECT) programs. A steam Generator Inspection Planning Expert System has been developed which can assist NDE or utility personnel in planning ECT programs. This system represents and processes its information using an object oriented declarative knowledge base, heuristic rules, and symbolic information processing, three artificial intelligence based techniques incorporated in the design. The output of the system is an automated generation of ECT programs. Used in an outage inspection, this system significantly reduced planning time
A general description of expert systems is given. The operation of a fast reactor is reviewed. The expert system to the diagnosis of breakdowns limited to the reactor core. The structure of the system is described: specification of the diagnostics; structure of the data bank and evaluation of the rules; specification of the prediagnostics and evaluation; explanation of the diagnostics; time evolution of the system; comparison with other expert systems. Applications to some cases of faults are finally presented
Beksaç, M S; Eskiizmirliler, S; Cakar, A N; Erkmen, A M; Dağdeviren, A; Lundsteen, C
In this study, we introduce an expert system for intelligent chromosome recognition and classification based on artificial neural networks (ANN) and features obtained by automated image analysis techniques. A microscope equipped with a CCTV camera, integrated with an IBM-PC compatible computer environment including a frame grabber, is used for image data acquisition. Features of the chromosomes are obtained directly from the digital chromosome images. Two new algorithms for automated object detection and object skeletonizing constitute the basis of the feature extraction phase which constructs the components of the input vector to the ANN part of the system. This first version of our intelligent diagnostic system uses a trained unsupervised neural network structure and an original rule-based classification algorithm to find a karyotyped form of randomly distributed chromosomes over a complete metaphase. We investigate the effects of network parameters on the classification performance and discuss the adaptability and flexibility of the neural system in order to reach a structure giving an output including information about both structural and numerical abnormalities. Moreover, the classification performances of neural and rule-based system are compared for each class of chromosome. PMID:8705397
Full Text Available Performance Appraisal of employees plays a very critical role towards the growth of any organization. It has always been a tough task for any industry or organization as there is no unanimous scientific modus operandi for that. Performance Appraisal system is used to assess the capabilities and productiveness of the employees. In assessing employee performance, performance appraisal commonly includes assigning numerical values or linguistic labels to employees performance. However, the employee performance appraisal may include judgments which are based on imprecise data particularly when one employee tries to interpret another employee’s performance. Thus, the values assigned by the appraiser are only approximations and there is inherent vagueness in the evaluation. By fuzzy logic perspective, the performance of the appraisee includes the evaluation of his/her work ability, skills and adaptability which are absolutely fuzzy concepts that needs to be define in fuzzy terms. Hence, fuzzy approach can be used to examine these imprecise and uncertainty information. Consequently, the performance appraisal of employees can be accomplished by fuzzy logic approach and different defuzzification techniques are applied to rank the employees according to their performance, which shows inconsequential deviation in the rankings and hence proves the robustness of the system.
An expert system prototype has been developed to support system analysis activities at the Oak Ridge National Laboratory (ORNL) for waste management tasks. This expert system will aid in prioritizing radioactive waste streams for treatment and disposal by evaluating the severity and treatability of the problem as well as the final waste form. The objectives of the expert system development included: (1) collecting information on process treatment technologies for liquid low-level waste (LLLW) that can be incorporated in the knowledge base of the expert system, and (2) producing a prototype that suggests processes and disposal technologies for the ORNL LLLW system. The concept under which the expert system has been designed is integration of knowledge. There are many sources of knowledge (data bases, text files, simulation programs, etc.) that an expert would regularly consult in order to solve a problem of liquid waste management. The expert would normally know how to extract the information from these different sources of knowledge. The general scope of this project would be to include as much pertinent information as possible within the boundaries of the expert system. As a result, the user, who may not be an expert in every aspect of liquid waste management, may be able to apply the content of the information to a specific waste problem. This paper gives the methodological steps to develop the expert system under this general framework
Nondestructive assay waste characterization data generated for use in the National TRU Program must be of known and demonstrable quality. Each measurement is required to receive an independent technical review by a qualified expert. An expert system prototype has been developed to automate waste NDA data review of a passive/active neutron drum counter system. The expert system is designed to yield a confidence rating regarding measurement validity. Expert system rules are derived from data in a process involving data clustering, fuzzy logic, and genetic algorithms. Expert system performance is assessed against confidence assignments elicited from waste NDA domain experts. Performance levels varied for the active, passive shielded, and passive system assay modes of the drum counter system, ranging from 78% to 94% correct classifications
This paper describes the effort by Southern California Edison Company (SCE) and the Electric Power Research Institute (EPRI) to develop an expert systems work station designed to support the San Onofre Nuclear Generating Station (SONGS). The expert systems work station utilizes IntelliCorp KEE (Knowledge Engineering Environment) and EPRI-IntelliCorp PLEXSYS (PLant EXpert SYStem) technology, and SCE Piping and Instrumentation Diagrams (P and ID's) and host-based computer applications to assist plant operations and maintenance personnel in the development of safety tagout boundaries. Of significance in this venture is the merging of conventional computer applications technology with expert systems technology. The EPRI PLEXSYS work station will act as a front-end for the SONGS Tagout Administration and Generation System (TAGS), a conventional CICS/COBOL mainframe computer application
Zarri, Gian Piero
Operational Expert System Applications in Europe describes the representative case studies of the operational expert systems (ESs) that are used in Europe.This compilation provides examples of operational ES that are realized in 10 different European countries, including countries not usually examined in the standard reviews of the field.This book discusses the decision support system using several artificial intelligence tools; expert systems for fault diagnosis on computerized numerical control (CNC) machines; and expert consultation system for personal portfolio management. The failure prob
Full Text Available Aim of the study: Decision support systems for forest management (FMDSS have been developed world wide to account for a broad range of forest ecosystems, management goals and organizational frameworks (e.g. the wiki page of the FORSYS project reports 62 existing FMDSSs from 23 countries. The need to enhance the collaboration among this diverse community of developers and users fostered the rise of new group communication processes that could capture useful knowledge from past experiences in order to efficiently provide it to new FMDSS development efforts.Material and methods: This paper presents and tests an exploratory process aiming to identify the empirical guidelines assisting developers and users of FMDSS. This process encompasses aDelphi survey built upon the consolidation of the lessons-learned statements that summarize the past experiences of the experts involved in the FORSYS project. The experts come from 34 countries and have diverse interests, ranging from forest planners, IT developers, social scientists studying participatory planning, and researchers with interests in knowledge management and in quantitative models for forest planning.Main results: The proposed 37 empirical guidelines that group 102 lessons-learned cover a broad range of issues including the DSS development cycle, involvement of the stakeholders, methods, models and knowledge-based techniques in use.Research highlights: These results may be used for improving new FMDSS development processes, teaching and training and further suggest new features of FMDSS and future research topics. Furthermore, the guidelines may constitute a knowledge repository that may be continuously improved by a community of practice.Keywords: Forest management; guidelines; guidelines definition process; lessons learned; decision support systems; system architecture; knowledge management; participatory planning; Delphi.
Schwarz, A F
Handbook of VLSI Chip Design and Expert Systems provides information pertinent to the fundamental aspects of expert systems, which provides a knowledge-based approach to problem solving. This book discusses the use of expert systems in every possible subtask of VLSI chip design as well as in the interrelations between the subtasks.Organized into nine chapters, this book begins with an overview of design automation, which can be identified as Computer-Aided Design of Circuits and Systems (CADCAS). This text then presents the progress in artificial intelligence, with emphasis on expert systems.
O. O. Matusevych
Full Text Available The author proposed the numerous methods of solving the multi-criterion task – increasing of reliability of control system on the basis of expert information. The information, which allows choosing thoughtfully the method of reliability increasing for a control system of electric transport, is considered.
Rogers, J. L.
The expert system called EXADS was developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. Because of the general purpose nature of ADS, it is difficult for a nonexpert to select the best choice of strategy, optimizer, and one-dimensional search options from the one hundred or so combinations that are available. EXADS aids engineers in determining the best combination based on their knowledge of the problem and the expert knowledge previously stored by experts who developed ADS. EXADS is a customized application of the AESOP artificial intelligence program (the general version of AESOP is available separately from COSMIC. The ADS program is also available from COSMIC.) The expert system consists of two main components. The knowledge base contains about 200 rules and is divided into three categories: constrained, unconstrained, and constrained treated as unconstrained. The EXADS inference engine is rule-based and makes decisions about a particular situation using hypotheses (potential solutions), rules, and answers to questions drawn from the rule base. EXADS is backward-chaining, that is, it works from hypothesis to facts. The rule base was compiled from sources such as literature searches, ADS documentation, and engineer surveys. EXADS will accept answers such as yes, no, maybe, likely, and don't know, or a certainty factor ranging from 0 to 10. When any hypothesis reaches a confidence level of 90% or more, it is deemed as the best choice and displayed to the user. If no hypothesis is confirmed, the user can examine explanations of why the hypotheses failed to reach the 90% level. The IBM PC version of EXADS is written in IQ-LISP for execution under DOS 2.0 or higher with a central memory requirement of approximately 512K of 8 bit bytes. This program was developed in 1986.
Cui, Xiaopeng; Feng, Zhenjie; Jin, Yuan; Cao, Yiming; Deng, Dongmei; Chu, Hao; Cao, Shixun; Dong, Cheng; Zhang, Jincang
AutoFP, a highly automated software toolkit, has been developed to improve the extent of automation of the widely used Rietveld refinement program FullProf [Rodríguez-Carvajal (1993). Physica B, 192, 55-69]. An expert system algorithm is used as the control layer to simulate the manual process when FullProf is used to perform Rietveld refinement. This enables the program to complete the Rietveld refinement highly automatically. It is shown that the expert system algorithm is a good choice for...
Yogendra P. Dubey
The article explains the concept of expert systems and how they function. The components of an expert system: the knowledge base, the inference engine, user interface and the knowledge acquisition module are explained. The various activities in the LIS field where such systems can be put to use are also discussed.
Yogendra P. Dubey
The article explains the concept of expert systems and how they function. The components of an expert system: the knowledge base, the inference engine, user interface and the knowledge acquisition module are explained. The various activities in the LIS field where such systems can be put to use are also discussed.http://dx.doi.org/10.14429/dbit.16.4.3271
Yogendra P. Dubey
Full Text Available The article explains the concept of expert systems and how they function. The components of an expert system: the knowledge base, the inference engine, user interface and the knowledge acquisition module are explained. The various activities in the LIS field where such systems can be put to use are also discussed.
Hasselbring, Ted S.
The potential application of "expert systems" to the diagnosis and assessment of special-needs children is examined and existing prototype systems are reviewed. The future of this artificial intelligence technology is discussed in relation to emerging development tools designed for the creation of expert systems by the lay public. (Author)
The United States Department of Energy (DOE) is facing a large task in completing Remedial Investigations and Feasibility Studies (RI/FS) for hazardous waste sites across the nation. One of the primary objectives of an RI/FS is the specification of viable sequences of technology treatment trains which can provide implementable site solutions. We present a methodology which integrates expert system technology within an object-oriented framework to create a cooperative reasoning system designed to provide a comprehensive list of these implementable solutions. The system accomplishes its goal of specifying technology trains by utilizing a ''team'' of expert system objects. The system distributes the problem solving among the individual expert objects, and then coordinates the combination of individual decisions into a joint solution. Each expert object possesses the knowledge of an expert in a particular technology. An expert object can examine the parameters and characteristics of the waste site, seek information and support from other expert objects, and then make decisions concerning its own applicability. This methodology has at least two primary benefits. First, the creation of multiple expert objects provides a more direct mapping from the actual process to a software system, making the system easier to build. Second, the distribution of the inferencing among a number of loosely connected expert objects allows for a more robust and maintainable final product
Bohn, S.J.; Pennock, K.A.; Franklin, A.L.
The United States Department of Energy (DOE) is facing a large task in completing Remedial Investigations and Feasibility Studies (RI/FS) for hazardous waste sites across the nation. One of the primary objectives of an RI/FS is the specification of viable sequences of technology treatment trains which can provide implementable site solutions. We present a methodology which integrates expert system technology within an object-oriented framework to create a cooperative reasoning system designed to provide a comprehensive list of these implementable solutions. The system accomplishes its goal of specifying technology trains by utilizing a team'' of expert system objects. The system distributes the problem solving among the individual expert objects, and then coordinates the combination of individual decisions into a joint solution. Each expert object possesses the knowledge of an expert in a particular technology. An expert object can examine the parameters and characteristics of the waste site, seek information and support from other expert objects, and then make decisions concerning its own applicability. This methodology has at least two primary benefits. First, the creation of multiple expert objects provides a more direct mapping from the actual process to a software system, making the system easier to build. Second, the distribution of the inferencing among a number of loosely connected expert objects allows for a more robust and maintainable final product.
Bohn, S.J.; Pennock, K.A.; Franklin, A.L.
The United States Department of Energy (DOE) is facing a large task in completing Remedial Investigations and Feasibility Studies (RI/FS) for hazardous waste sites across the nation. One of the primary objectives of an RI/FS is the specification of viable sequences of technology treatment trains which can provide implementable site solutions. We present a methodology which integrates expert system technology within an object-oriented framework to create a cooperative reasoning system designed to provide a comprehensive list of these implementable solutions. The system accomplishes its goal of specifying technology trains by utilizing a ``team`` of expert system objects. The system distributes the problem solving among the individual expert objects, and then coordinates the combination of individual decisions into a joint solution. Each expert object possesses the knowledge of an expert in a particular technology. An expert object can examine the parameters and characteristics of the waste site, seek information and support from other expert objects, and then make decisions concerning its own applicability. This methodology has at least two primary benefits. First, the creation of multiple expert objects provides a more direct mapping from the actual process to a software system, making the system easier to build. Second, the distribution of the inferencing among a number of loosely connected expert objects allows for a more robust and maintainable final product.
Full Text Available In the recent years, the quality of human life is improved by artificial intelligencetechniques. In artificial intelligence, an expert system is a computer system that emulates thedecision-making ability of a human expert. Expert systems are designed to solve complexproblems by reasoning about knowledge, like an expert. In this paper, we propose an expertsystem with the aim of designing the garden with considering the different taste of thepeople. The proposed system can help people to design their garden themselves. Indeed, it isable to use by architectures to provide decision support system, interactive training tool andexpert advice. The system constitutes part of intelligent system of designing the garden. Aninitial evaluation of the expert system was carried out and a positive feedback was receivedfrom the users.
Full Text Available Several experimental studies revealed that expert systems have been successfully applied in real world domains such as medical diagnoses, traffic control, and many others. However, one of the major drawbacks of classic expert systems is their reliance on human domain experts which require time, care, experience and accuracy. This shortcoming also may result in building knowledge bases that may contain inconsistent rules or contradicting rules. To treat the abovementioned we intend to propose and develop automated methods based on data mining called Associative Classification (AC that can be easily integrated into an expert system to produce the knowledge base according to hidden correlations in the input database. The methodology employed in the proposed expert system is based on learning the rules from the database rather than inputting the rules by the knowledge engineer from the domain expert and therefore, care and accuracy as well as processing time are improved. The proposed automated expert system contains a novel learning method based on AC mining that has been evaluated on Islamic textual data according to several evaluation measures including recall, precision and classification accuracy. Furthermore, five different classification approaches: Decision trees (C4.5, KNN, SVM, MCAR and NB and the proposed automated expert system have been tested on the Islamic data set to determine the suitable method in classifying Arabic texts.
Hossein, Shahadat; Zander, Par-Ola; Kamal, Md.; Chowdhury, Linkon
Little knowledge exists on the impact and results associated with e-government projects in many specific use domains. Therefore it is necessary to evaluate the efficiency and effectiveness of e-government systems. Since the development of e-government is a continuous process of improvement, it requires continuous evaluation of the overall e-government system as well as evaluation of its various dimensions such as determinants, characteristics and results. E-government development is often com...
This dissertation presents a novel effort to develop ITS technologies that adapt by observing student behavior. In particular, we define an evolving expert knowledge base (EEKB) that structures a domain's information as a set of nodes and the relationships that exist between those nodes. The structure of this model is not the particularly novel…
Marques, A. F.; Ficko, A.; Kangas, A.; Rosset, C.; Ferreti, F.; Rasinmaki, J.; Packalen, T.; Gordom, S.
Aim of the study: Decision support systems for forest management (FMDSS) have been developed world wide to account for a broad range of forest ecosystems, management goals and organizational frameworks (e.g. the wiki page of the FORSYS project reports 62 existing FMDSSs from 23 countries). The need to enhance the collaboration among this diverse community of developers and users fostered the rise of new group communication processes that could capture useful knowledge from past experiences in order to efficiently provide it to new FMDSS development efforts. Material and methods: This paper presents and tests an exploratory process aiming to identify the empirical guidelines assisting developers and users of FMDSS. This process encompasses a Delphi survey built upon the consolidation of the lessons-learned statements that summarize the past experiences of the experts involved in the FORSYS project. The experts come from 34 countries and have diverse interests, ranging from forest planners, IT developers, social scientists studying participatory planning, and researchers with interests in knowledge management and in quantitative models for forest planning. Main results: The proposed 37 empirical guidelines that group 102 lessons-learned cover a broad range of issues including the DSS development cycle, involvement of the stakeholders, methods, models and knowledge based techniques in use. Research highlights: These results may be used for improving new FMDSS development processes, teaching and training and further suggest new features of FMDSS and future research topics. Furthermore, the guidelines may constitute a knowledge repository that may be continuously improved by a community of practice. (Author)
de Boer, Thomas W.; Klingenberg, Warse
This paper describes a proposal for a hybrid architecture for monitoring and Condition-based Maintenance (CBM) of punching/blanking of sheet metal. Previous work shows that it is possible for certain applications (in which process parameters are sufficiently stable) to detect tool wear and other imp
Shiva, S. G.; Klon, Peter F.
A novel representational scheme for design object descriptions is presented. An abstract notion of modules and signals is developed as a conceptual foundation for the scheme. This abstraction relates the objects to the meaning of system descriptions. Anchored on this abstraction, a representational model which incorporates dynamic semantics for these objects is presented. This representational model is called a hologram scheme since it represents dual level information, namely, structural and semantic. The benefits of this scheme are presented.
SAZGAR, Farzaneh; GANJI KHEIBARI, Mehran; FASIHFAR, Zohreh
Abstract. Economic growth and development is the most important factor in the development of a country, and infrastructure projects such as water and sewage systems, airports, power plants, etc. are the most important factors for economic growth and development.One of the best methods is the use of BOT (Build Operate Transfer) contracts. Since the BOT projects are usually large, and they took relatively long time, risk management is highly important in these projects. In order to solve such p...
Gicquel, Quentin; Tvardik, Nastassia; Bouvry, Côme; Kergourlay, Ivan; Bittar, André; Segond, Frédérique; Darmoni, Stefan; Metzger, Marie-Hélène
The objective of the SYNODOS collaborative project was to develop a generic IT solution, combining a medical terminology server, a semantic analyser and a knowledge base. The goal of the project was to generate meaningful epidemiological data for various medical domains from the textual content of French medical records. In the context of this project, we built a care pathway oriented conceptual model and corresponding annotation method to develop and evaluate an expert system's knowledge base. The annotation method is based on a semi-automatic process, using a software application (MedIndex). This application exchanges with a cross-lingual multi-termino-ontology portal. The annotator selects the most appropriate medical code proposed for the medical concept in question by the multi-termino-ontology portal and temporally labels the medical concept according to the course of the medical event. This choice of conceptual model and annotation method aims to create a generic database of facts for the secondary use of electronic health records data. PMID:26262366
This paper is concerned with the applications of expert systems to complex military problems. A brief description of needs for expert systems in the military arena is given. A short tutorial on some of the elements of an expert system is found in Appendix I. An important aspect of expert systems concerns using uncertain information and ill-defined procedures. Many of the general techniques of dealing with uncertainty are described in Appendix II. These techniques include Bayesian certainty factors, Dempster-Shafer theory of uncertainty, and Zadeh's fuzzy set theory. The major portion of the paper addresses specific expert system examples such as resource allocation, identification of radar images, maintenance and troubleshooting of electronic equipment, and the interpretation and understanding of radar images. Extensions of expert systems to incorporate learning are examined in the context of military intelligence to determine the disposition, location, and intention of the adversary. The final application involves the use of distributed communicating cooperating expert systems for battle management. Finally, the future of expert systems and their evolving capabilities are discussed
Reliability centered maintenance (RCM) is a new maintenance concept which aims to minimise failure consequences. This paper discusses an expert system approach for RCM as applied to pumping equipment using VP Expert Shell. RCM procedure is based on RCM Decision Diagram which identifies a given failure mode in terms of the failure consequences and suggests a suitable maintenance strategy. A sample consultation of the expert system is also included in the paper. The expert system developed is useful not only to the practicing engineers but also serves as a better tool at the design stages of the equipment. (author). 7 refs., 1 fig
It is a major advantage to those that must make decisions about the implementation of an emergency plan following an accident at a nuclear power plant if the likely release of activity is predicted before it occurs. To this end, a software module, which provides a rapid estimate of the source term to the environment, has been developed by NNC Ltd. Termed the RODOS STM, the software has been developed such that it can be used with the RODOS system. Operating outside of RODOS, the software remains a useful source term prediction tool. The software employs Bayesian analysis techniques, and the results of level 1 and level 2 probabilistic safety analysis, to calculate the probability of the possible releases of activity into the environment and the potential magnitude of those releases, given a set of observations about the status of the NPP. The software has been developed using the Sizewell 'B' PWR design. (author)
Meléndez i Frigola, Joaquim; Colomer Llinàs, Joan; Rosa, Josep Lluís de la
The paper focuses on taking advantage of large amounts of data that are systematically stored in plants (by means of SCADA systems), but not exploited enough in order to achieve supervisory goals (fault detection, diagnosis and reconfiguration). The methodology of case base reasoning (CBR) is proposed to perform supervisory tasks in industrial processes by re-using the stored data. The goal is to take advantage of experiences, registered in a suitable structure as cam, avoiding the tedious ta...
An expert system program is developed by using C++ language. In the system, fuzzy knowledge expression and inference based on the production rule are realized, which provides convenience for building various expert system by adopting C++ language for the future.%文中采用C++语言开发了基于MYCIN的专家系统程序，实现了基于规则的模糊知识表达与推理，为今后采用C++建造各种实用专家系统提供了方便。
An expert system developed to identify input items to INIS database with a high probability of containing errors is described. The system employs a Knowledge Base constructed by the interpretation of a large number of intellectual choices or expert decisions made by human indexers and incorporated in the INIS database. On the basis of the descriptor indexing, the system checks the correctness of the categorization. A notable feature of the system is its capability of self improvement by the continuous updating of the Knowledge Base. The expert system has also been found to be extremely useful in identifying documents with poor indexing. 3 refs, 9 figs
The gas resources assessment expert system is one of the advanced methods for appraising oil and gas resources. The establishment of a knowledge base is the focal task in developing the expert system. This paper presents a summary of the mechanism and the major controlling factors in the formation of gas pools in the southeast uplift of the Songliao basin. Then an appropriate assessment model is established for trapping the gas resources and a knowledge base built in the expert system to realize the model. By using the expert system to appraise the gas-bearing probability of 25 major traps of the Quantou and Denglouku Formations in the Shiwu-Dehui area, the authors have proved that the expert system is suitable for appraising traps in the Songliao basin and similar basins.
Millwater, H.; Palmer, K.; Fink, P.
An expert system (NESSUS/EXPERT) is presented which provides assistance in using probabilistic structural analysis methods. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator. NESSUS/EXPERT was developed with a combination of FORTRAN and CLIPS, a C language expert system tool, to exploit the strengths of each language.
Ebtehaj, Isa; Bonakdari, Hossein; Zaji, Amir Hossein
In this study, an expert system with a radial basis function neural network (RBF-NN) based on decision trees (DT) is designed to predict sediment transport in sewer pipes at the limit of deposition. First, sensitivity analysis is carried out to investigate the effect of each parameter on predicting the densimetric Froude number (Fr). The results indicate that utilizing the ratio of the median particle diameter to pipe diameter (d/D), ratio of median particle diameter to hydraulic radius (d/R) and volumetric sediment concentration (C(V)) as the input combination leads to the best Fr prediction. Subsequently, the new hybrid DT-RBF method is presented. The results of DT-RBF are compared with RBF and RBF-particle swarm optimization (PSO), which uses PSO for RBF training. It appears that DT-RBF is more accurate (R(2) = 0.934, MARE = 0.103, RMSE = 0.527, SI = 0.13, BIAS = -0.071) than the two other RBF methods. Moreover, the proposed DT-RBF model offers explicit expressions for use by practicing engineers. PMID:27386995
Avci, Derya; Dogantekin, Akif
Parkinson disease is a major public health problem all around the world. This paper proposes an expert disease diagnosis system for Parkinson disease based on genetic algorithm- (GA-) wavelet kernel- (WK-) Extreme Learning Machines (ELM). The classifier used in this paper is single layer neural network (SLNN) and it is trained by the ELM learning method. The Parkinson disease datasets are obtained from the UCI machine learning database. In wavelet kernel-Extreme Learning Machine (WK-ELM) structure, there are three adjustable parameters of wavelet kernel. These parameters and the numbers of hidden neurons play a major role in the performance of ELM. In this study, the optimum values of these parameters and the numbers of hidden neurons of ELM were obtained by using a genetic algorithm (GA). The performance of the proposed GA-WK-ELM method is evaluated using statical methods such as classification accuracy, sensitivity and specificity analysis, and ROC curves. The calculated highest classification accuracy of the proposed GA-WK-ELM method is found as 96.81%. PMID:27274882
Increased frequency of prothrombin time testing, facilitated by patient self-testing (PST) of the International Normalized Ratio (INR) can improve the clinical outcomes of oral anticoagulation therapy (OAT). However, oversight of this type of management is often difficult and time-consuming for healthcare professionals. This study reports the first randomized controlled trial of an automated direct-to-patient expert system, enabling remote and effective management of patients on OAT.
Many US Department of Energy sites and facilities will be environmentally remediated during the next several decades. A number of the restoration activities (e.g., decontamination and decommissioning of inactive nuclear facilities) can only be carried out by remote means and will be manipulation-intensive tasks. Experience has shown that manipulation tasks are especially slow and fatiguing for the human operator of a remote manipulator. In this paper, the authors present a rule-based expert system for automated, dextrous robotic grasping. This system interprets the features of an object to generate hand shaping and wrist orientation for a robot hand and arm. The system can be used in several different ways to lessen the demands on the human operator of a remote manipulation system - either as a fully autonomous grasping system or one that generates grasping options for a human operator and then automatically carries out the selected option
Mullins, Barry E.
Expert Missile Maintenance Aid (EMMA) is a first attempt to enhance maintenance of the tactical munition at the field and depot level by using artificial intelligence (AI) techniques. The ultimate goal of EMMA is to help a novice maintenance technician isolate and diagnose electronic, electromechanical, and mechanical equipment faults to the board/chassis level more quickly and consistently than the best human expert using the best currently available automatic test equipment (ATE). To this end, EMMA augments existing ATE with an expert system that captures the knowledge of design and maintenance experts. The EMMA program is described, including the evaluation of field-level expert system prototypes, the description of several study tasks performed during EMMA, and future plans for a follow-on program. This paper will briefly address several study tasks performed during EMMA. The paper concludes with a discussion of future plans for a follow-on program and other areas of concern.
The fundamental principles of industrial hygiene are based upon the recognition, evaluation, and control of workplace hazards. Occupational safety and health professionals (e.g., industrial hygienists) perform this task by assessing numerous complex factors. In many situations industrial hygienists are not available; therefore, an expert system has been developed to assist the performance of workplace exposure assessments (WEAs). The Workplace Exposure Assessment Expert System (WORKSPERT) evaluates various hazardous substances, workplace conditions, and worker exposures for designated homogeneous exposure groups (HEGs). The three major components of WORKSPERT (i.e., substance, workplace, and exposure factors) are described by 27 multiple attribute variables. An air monitoring program (AMP) may be recommended for each HEG based upon the WEA. The AMP provides recommendations for an appropriate sampling strategy, sampling duration, multiple substance exposures, and number of samples to be obtained in the future. The use of WORKSPERT or other expert systems should never supersede the judgment of occupational safety and health professionals. However, WORKSPERT can be a valuable tool when used by knowledgeable, qualified technical professionals (e.g., safety and health specialists, chemists, engineers, and toxicologists) who understand the specific substance, workplace, and exposure factors for designated HEGs. WORKSPERT allows these people to benefit from the expertise of an industrial hygienist by performing systematic evaluations and obtaining recommendations for corrective actions or an AMP. The use of WORKSPERT to perform WEAs promotes the protection of workers from hazardous substances and assists compliance with occupational safety and health regulations. It also facilitates the communication of substance hazards, workplace controls, and worker exposures in a succinct manner. PMID:1543134
Shikhar Kr. Sarma
Full Text Available This paper presents an architectural framework of an Expert System in the area of agriculture and describes the design and development of the rule based expert system, using the shell ESTA (Expert System for Text Animation. The designed system is intended for the diagnosis of common diseases occurring in the rice plant. An Expert System is a computer program normally composed of a knowledge base, inference engine and user-interface. The proposed expert system facilitates different components including decision support module with interactive user interfaces for diagnosis on the basis of response(s of the user made against the queries related to particular disease symptoms. ESTA programming is based on logic programming approach. The system integrates a structured knowledge base that contains knowledge about symptoms and remedies of diseases in the rice plant appearing during their life span. An image database is also integrated with the system for making the decision support more interactive. The pictures related to disease symptoms are stored in the picture database and the intelligent system module prompts these with the interface based on rule based decision making algorithms. The system has been tested with domain dataset, and results given by the system have been validated with domain experts.
Lavallee, David B.
The purpose is to investigate the feasibility of using Ada for rule-based expert systems with real-time performance requirements. This includes exploring the Ada features which give improved performance to expert systems as well as optimizing the tradeoffs or workarounds that the use of Ada may require. A prototype inference engine was built using Ada, and rule firing rates in excess of 500 per second were demonstrated on a single MC68000 processor. The knowledge base uses a directed acyclic graph to represent production lines. The graph allows the use of AND, OR, and NOT logical operators. The inference engine uses a combination of both forward and backward chaining in order to reach goals as quickly as possible. Future efforts will include additional investigation of multiprocessing to improve performance and creating a user interface allowing rule input in an Ada-like syntax. Investigation of multitasking and alternate knowledge base representations will help to analyze some of the performance issues as they relate to larger problems.
Allen, Cheryl L.
The topics are presented in viewgraph form and include: software requirements; design layout of the automated assembly system; menu display for automated composite command; expert system features; complete robot arm state diagram and logic; and expert system benefits.
Full Text Available Several rule-based expert systems were developed for diagnostics of high voltage (HV insulation systems, especially for the evaluation of partial discharge (PD activity. Several rule-based expert systems were developed in the cooperation of top diagnostic workplaces of the Czech Republic for this purpose. The IZOLEX expert system evaluates diagnostic measurement data from commonly used off-line diagnostic methods for the diagnostics of HV insulation of rotating machines, non-rotating machines and insulating oils. The CVEX expert system evaluates the PD activity on HV electrical machines and equipment by means of an off-line measurement. The CVEXON expert system is for the evaluation of the discharge activity by on-line measurement and the ALTONEX expert system is the system for on-line monitoring of rotating machines. The complex project for the evaluation of a PD measurement on HV insulation systems has also been made. This complex evaluating system includes two parallel expert systems for the evaluation of a PD activity on HV electrical machines.
M. Sarath Kumar
Full Text Available Modern rotating machines such as turbomachines, either produce or absorb huge amount of power. Some of the common applications are: steam turbine-generator and gas turbine-compressor-generator trains produce power and machines, such as pumps, centrifugal compressors, motors, generators, machine tool spindles, etc., are being used in industrial applications. Condition-based maintenance of rotating machinery is a common practice where the machine's condition is monitored constantly, so that timely maintenance can be done. Since modern machines are complex and the amount of data to be interpreted is huge, we need precise and fast methods in order to arrive at the best recommendations to prevent catastrophic failure and to prolong the life of the equipment. In the present work using vibration characteristics of a rotor-bearing system, the condition of a rotating machinery (electrical rotor is predicted using an off-line expert system. The analysis of the problem is carried out in an Object Oriented Programming (OOP framework using the finite element method. The expert system which is also developed in an OOP paradigm gives the type of the malfunctions, suggestions and recommendations. The system is implemented in C++.