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Sample records for fuzzy expert systems

  1. Fuzzy expert systems using CLIPS

    Science.gov (United States)

    Le, Thach C.

    1994-01-01

    This paper describes a CLIPS-based fuzzy expert system development environment called FCLIPS and illustrates its application to the simulated cart-pole balancing problem. FCLIPS is a straightforward extension of CLIPS without any alteration to the CLIPS internal structures. It makes use of the object-oriented and module features in CLIPS version 6.0 for the implementation of fuzzy logic concepts. Systems of varying degrees of mixed Boolean and fuzzy rules can be implemented in CLIPS. Design and implementation issues of FCLIPS will also be discussed.

  2. A fuzzy expert system based on relations

    International Nuclear Information System (INIS)

    Hall, L.O.; Kandel, A.

    1986-01-01

    The Fuzzy Expert System (FESS) is an expert system which makes use of the theory of fuzzy relations to perform inference. Relations are very general and can be used for any application, which only requires different types of relations be implemented and used. The incorporation of fuzzy reasoning techniques enables the expert system to deal with imprecision in a well-founded manner. The knowledge is represented in relational frames. FESS may operate in either a forward chaining or backward chaining manner. It uses primarily implication and factual relations. A unique methodology for combination of evidence has been developed. It makes uses of a blackboard for communication between the various knowledge sources which may operate in parallel. The expert system has been designed in such a manner that it may be used for diverse applications

  3. Fuzzy Expert System to Characterize Students

    Science.gov (United States)

    Van Hecke, T.

    2011-01-01

    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…

  4. Fuzzy Expert System for Heart Attack Diagnosis

    Science.gov (United States)

    Hassan, Norlida; Arbaiy, Nureize; Shah, Noor Aziyan Ahmad; Afizah Afif@Afip, Zehan

    2017-08-01

    Heart attack is one of the serious illnesses and reported as the main killer disease. Early prevention is significant to reduce the risk of having the disease. The prevention efforts can be strengthen through awareness and education about risk factor and healthy lifestyle. Therefore the knowledge dissemination is needed to play role in order to distribute and educate public in health care management and disease prevention. Since the knowledge dissemination in medical is important, there is a need to develop a knowledge based system that can emulate human intelligence to assist decision making process. Thereby, this study utilized hybrid artificial intelligence (AI) techniques to develop a Fuzzy Expert System for Diagnosing Heart Attack Disease (HAD). This system integrates fuzzy logic with expert system, which helps the medical practitioner and people to predict the risk and as well as diagnosing heart attack based on given symptom. The development of HAD is expected not only providing expert knowledge but potentially become one of learning resources to help citizens to develop awareness about heart-healthy lifestyle.

  5. Fuzzy expert systems models for operations research and management science

    Science.gov (United States)

    Turksen, I. B.

    1993-12-01

    Fuzzy expert systems can be developed for the effective use of management within the domains of concern associated with Operations Research and Management Science. These models are designed with: (1) expressive powers of representation embedded in linguistic variables and their linguistic values in natural language expressions, and (2) improved methods of interference based on fuzzy logic which is a generalization of multi-valued logic with fuzzy quantifiers. The results of these fuzzy expert system models are either (1) approximately good in comparison with their classical counterparts, or (2) much better than their counterparts. Moreover, for fuzzy expert systems models, it is only necessary to obtain ordinal scale data. Whereas for their classical counterparts, it is generally required that data be at least on ratio and absolute scale in order to guarantee the additivity and multiplicativity assumptions.

  6. PERFORMANCE EVALUATION OF PENSION FUNDS WITH FUZZY EXPERT SYSTEM

    Directory of Open Access Journals (Sweden)

    SERDAR KORUKOĞLU

    2013-06-01

    Full Text Available Financial rating and ranking firms often use linguistic instead of numerical values. When input data are mostly qualitative and are based on subjective knowledge of experts, the Fuzzy Set Theory provides a solid mathematical model to represent and handle these data. The aim of this study is developing a fuzzy expert model to evaluate the performance of the pension funds by using their risk and return values. The method is used for evaluating the performance of the randomly selected of twenty seven Turkish pension funds. The obtained results proved that the fuzzy expert system is appropriate and consistent for performance evaluation.

  7. Expert system driven fuzzy control application to power reactors

    International Nuclear Information System (INIS)

    Tsoukalas, L.H.; Berkan, R.C.; Upadhyaya, B.R.; Uhrig, R.E.

    1990-01-01

    For the purpose of nonlinear control and uncertainty/imprecision handling, fuzzy controllers have recently reached acclaim and increasing commercial application. The fuzzy control algorithms often require a ''supervisory'' routine that provides necessary heuristics for interface, adaptation, mode selection and other implementation issues. Performance characteristics of an on-line fuzzy controller depend strictly on the ability of such supervisory routines to manipulate the fuzzy control algorithm and enhance its control capabilities. This paper describes an expert system driven fuzzy control design application to nuclear reactor control, for the automated start-up control of the Experimental Breeder Reactor-II. The methodology is verified through computer simulations using a valid nonlinear model. The necessary heuristic decisions are identified that are vitally important for the implemention of fuzzy control in the actual plant. An expert system structure incorporating the necessary supervisory routines is discussed. The discussion also includes the possibility of synthesizing the fuzzy, exact and combined reasoning to include both inexact concepts, uncertainty and fuzziness, within the same environment

  8. Towards a Fuzzy Expert System on Toxicological Data Quality Assessment.

    Science.gov (United States)

    Yang, Longzhi; Neagu, Daniel; Cronin, Mark T D; Hewitt, Mark; Enoch, Steven J; Madden, Judith C; Przybylak, Katarzyna

    2013-01-01

    Quality assessment (QA) requires high levels of domain-specific experience and knowledge. QA tasks for toxicological data are usually performed by human experts manually, although a number of quality evaluation schemes have been proposed in the literature. For instance, the most widely utilised Klimisch scheme1 defines four data quality categories in order to tag data instances with respect to their qualities; ToxRTool2 is an extension of the Klimisch approach aiming to increase the transparency and harmonisation of the approach. Note that the processes of QA in many other areas have been automatised by employing expert systems. Briefly, an expert system is a computer program that uses a knowledge base built upon human expertise, and an inference engine that mimics the reasoning processes of human experts to infer new statements from incoming data. In particular, expert systems have been extended to deal with the uncertainty of information by representing uncertain information (such as linguistic terms) as fuzzy sets under the framework of fuzzy set theory and performing inferences upon fuzzy sets according to fuzzy arithmetic. This paper presents an experimental fuzzy expert system for toxicological data QA which is developed on the basis of the Klimisch approach and the ToxRTool in an effort to illustrate the power of expert systems to toxicologists, and to examine if fuzzy expert systems are a viable solution for QA of toxicological data. Such direction still faces great difficulties due to the well-known common challenge of toxicological data QA that "five toxicologists may have six opinions". In the meantime, this challenge may offer an opportunity for expert systems because the construction and refinement of the knowledge base could be a converging process of different opinions which is of significant importance for regulatory policy making under the regulation of REACH, though a consensus may never be reached. Also, in order to facilitate the implementation

  9. Expert System Diagnosis of Cataract Eyes Using Fuzzy Mamdani Method

    Science.gov (United States)

    Santosa, I.; Romla, L.; Herawati, S.

    2018-01-01

    Cataracts are eye diseases characterized by cloudy or opacity of the lens of the eye by changing the colour of black into grey-white which slowly continues to grow and develop without feeling pain and pain that can cause blindness in human vision. Therefore, researchers make an expert system of cataract eye disease diagnosis by using Fuzzy Mamdani and how to care. The fuzzy method can convert the crisp value to linguistic value by fuzzification and includes in the rule. So this system produces an application program that can help the public in knowing cataract eye disease and how to care based on the symptoms suffered. From the results of the design implementation and testing of expert system applications to diagnose eye disease cataracts, it can be concluded that from a trial of 50 cases of data, obtained test results accuracy between system predictions with expert predictions obtained a value of 78% truth.

  10. Designing Fuzzy Rule Based Expert System for Cyber Security

    OpenAIRE

    Goztepe, Kerim

    2016-01-01

    The state of cyber security has begun to attract more attention and interest outside the community of computer security experts. Cyber security is not a single problem, but rather a group of highly different problems involving different sets of threats. Fuzzy Rule based system for cyber security is a system consists of a rule depository and a mechanism for accessing and running the rules. The depository is usually constructed with a collection of related rule sets. The aim of this study is to...

  11. A Fuzzy Rule-Based Expert System for Evaluating Intellectual Capital

    Directory of Open Access Journals (Sweden)

    Mohammad Hossein Fazel Zarandi

    2012-01-01

    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.

  12. Application of fuzzy expert system on LILW performance assessment

    International Nuclear Information System (INIS)

    Lemos, F.L. de; Sullivan, T.

    2002-01-01

    A complete LILW repository performance assessment requires the involvement between several experts in many fields of science. Many sources of uncertainties arise due to complexity of interaction of environmental parameters, lack of data and ignorance, this makes predictive analysis and interpretation difficult. This difficulty in understanding the impact of the ambiguities is even higher when it comes to public and decision makers involvement. Traditional methods of data analysis, while having strong mathematical basis, many times are not adequate to deal with ambiguous data. These ambiguities can be an obstacle to make the results easier to understand and defensible. A methodology of decision making, based on fuzzy logic, can help the interaction between experts, decision makers and the public. This method is the basis of an expert system which can help the analysis of very complex and ambiguous processes. (author)

  13. Contribution of a fuzzy expert system to regulatory impact analysis

    Directory of Open Access Journals (Sweden)

    Marco Antônio da Cunha

    2015-09-01

    Full Text Available Regulatory Impact Analysis (RIA has been consolidating in Brazilian regulatory agencies throughout the last decades. The RIA methodology aims to examine the regulatory process, measure the costs and benefits generated, as well as other effects of social, political or economic nature caused by a new or an existing regulation. By analysing each regulatory option, the expert or regulator faces a myriad of variables, usually of qualitative nature, that are difficult to measure and with a high degree of uncertainty. This research complements the existing literature, given the scarcity of decision support models in RIA that – regardless of the problem treated – incorporate the tacit knowledge of the regulation expert. This paper proposes an exploratory approach using a Fuzzy Expert System, which therefore helps to enrich the decision process in the final stage of comparison of the regulatory options.

  14. Parkinson's disease Assessment using Fuzzy Expert System and Nonlinear Dynamics

    Directory of Open Access Journals (Sweden)

    GEMAN, O.

    2013-02-01

    Full Text Available This paper proposes a new screening system for quantitative evaluation and analysis, designed for the early stage detection of Parkinson disease. This has been carried out in the view of improving the diagnosis currently established upon a basis of subjective scores. Parkinson?s disease (PD appears as a result of dopamine loss, a chemical mediator that is responsible for the body?s ability to control movements. The symptoms reflect the loss of nerve cells, due to an unknown. The input parameters of the system are represented by amplitude, frequency, the spectral characteristic and trembling localization. The main symptoms include trembling of hand, arms, movement difficulties, postural instability, disturbance of coordination and equilibrium, sleep disturbance, difficulties in speaking, reducing of voice volume. The medical knowledge in PD field is characterized by imprecision, uncertainty and vagueness. The proposed system (fuzzy expert systems is non-invasive and, easy to use by both physicians and patients at home.

  15. Designing a fuzzy expert system for selecting knowledge management strategy

    Directory of Open Access Journals (Sweden)

    Ameneh Khadivar

    2014-12-01

    Full Text Available knowledge management strategy is mentioned as one of the most important success factors for implementing knowledge management. The KM strategy selection is a complex decision that requires consideration of several factors. For evaluation and selection of an appropriate knowledge management strategy in organizations, many factors must be considered. The identified factors and their impact on knowledge management strategy are inherently ambiguous. In this study, an overview of theoretical foundations of research regarding the different knowledge management strategies has been done And factors influencing the knowledge management strategy selection have been extracted from conceptual frameworks and models. How these factors influence the knowledge management strategy selection is extracted through the fuzzy Delphi. Next a fuzzy expert system for the selection of appropriate knowledge management strategy is designed with respect to factors that have an impact on knowledge management strategy. The factors which influence the selection of knowledge management strategy include: general business strategy, organizational structure, cultural factors, IT strategy, strategic human resource management, social level, the types of knowledge creation processes and release it. The factors which influence the knowledge management strategy selection include: business strategy general, organizational structure, cultural factors, IT strategy, human resource management strategies, socialization level, knowledge types and its creation and diffusion processes. According to identified factors which affect the knowledge management strategy, the final strategy is recommended based on the range of human-oriented and system-oriented by keep the balance of explicit and implicit knowledge. The Designed system performance is tested and evaluated by the information related to three Iranian organization.

  16. Design of a Fuzzy Rule Base Expert System to Predict and Classify ...

    African Journals Online (AJOL)

    The main objective of design of a rule base expert system using fuzzy logic approach is to predict and forecast the risk level of cardiac patients to avoid sudden death. In this proposed system, uncertainty is captured using rule base and classification using fuzzy c-means clustering is discussed to overcome the risk level, ...

  17. Fuzzy logics acquisition and simulation modules for expert systems to assist operator's decision for nuclear power stations

    International Nuclear Information System (INIS)

    Averkin, A.A.

    1994-01-01

    A new type of fuzzy expert system for assisting the operator's decisions in nuclear power plant system in non-standard situations is proposed. This expert system is based on new approaches to fuzzy logics acquisition and to fuzzy logics testing. Fuzzy logics can be generated by a T-norms axiomatic system to choose the most suitable to operator's way of thinking. Then the chosen fuzzy logic is tested by simulation of inference process in expert system. The designed logic is the input of inference module of expert system

  18. WISENT: A fuzzy expert system for the allocation of inspection times in power station blocks

    International Nuclear Information System (INIS)

    Verweyen-Frank, H.; Schenck, K.

    1993-01-01

    The WISENT expert system does not only work according to the if-then rules typical of expert systems, but uses fuzzy methods in order to optimise the total allocation. This means that, for the first time, weighting factors can also be brought to bear for every optimisation criterion, in addition to a strict yes-no logic. (orig./DG) [de

  19. Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

    Science.gov (United States)

    Ibrahim, Wael Refaat Anis

    The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

  20. Insulation diagnosis of rotating machines for elevators by an expert system based on fuzzy inference. Fuzzy suiron wo donyushita expert system ni yoru shokokiyo kaitenki no zetsuen shindan

    Energy Technology Data Exchange (ETDEWEB)

    Kaneko, K.; Oshima, H. (Tokai Univ., Tokyo (Japan)); Yamada, N.; Iijima, T. (Mitsubishi Electric Building Techno-Service Co. Ltd., Tokyo (Japan))

    1992-11-20

    Using the data measured with the insulation deterioration diagnostic system for rotating machines for elevators, which is newly developed utilizing the past experience, an expert system which enables insulation deterioration diagnosis even by field maintenance engineers to some extent. In this system, the knowledge and experience of specialists are loaded in a personal computer as the rule for insulation deterioration diagnosis to perform insulation deterioration diagnosis by fuzzy inference and 'hypothesis-verification' type backward reasoning inference. The structured expert system is outlined. The result of insulation diagnosis by this system s compared with that made by specialists to evaluate the effectiveness of the diagnosed result of this system, and shows 84% agreement with the results obtained by specialists. It is, therefore, considered to be a highly practical expert system. 10 refs., 7 figs., 1 tab.

  1. A fuzzy expert system for predicting the performance of switched reluctance motor

    International Nuclear Information System (INIS)

    Mirzaeian, B.; Moallem, M.; Lucas, Caro

    2001-01-01

    In this paper a fuzzy expert system for predicting the performance of a switched reluctance motor has been developed. The design vector consists of design parameters, and output performance variables are efficiency and torque ripple. An accurate analysis program based on Improved Magnetic Equivalent Circuit method has been used to generate the input-output data. These input-output data is used to produce the initial fuzzy rules for predicting the performance of Switched Reluctance Motor. The initial set of fuzzy rules with triangular membership functions has been devised using a table look-up scheme. The initial fuzzy rules have been optimized to a set of fuzzy rules with Gaussian membership functions using gradient descent training scheme. The performance prediction results for a 6/8, 4 kw, Switched Reluctance Motor shows good agreement with the results obtained from Improved Magnetic Equivalent Circuit method or Finite Element analysis. The developed fuzzy expert system can be used for fast prediction of motor performance in the optimal design process or on-line control schemes of Switched Reluctance motor

  2. Designing fuzzy expert system for creating and ranking of tourism scenarios using fuzzy AHP method

    Directory of Open Access Journals (Sweden)

    Zohre Nikkhah

    2011-01-01

    Full Text Available One of the most important activities of tour and travel agencies is to select the appropriate tour configuration. There are normally two primary objectives of season and time period to set a group of cities called designing tour scenarios. The success of tour scenarios is deeply related to the experiments and wisdom of the experts and planners in travel agencies. This paper presents a fuzzy rule decision making to find the suitable set of cities where different possible criteria are ranked using analytical hierarchy procedure. The proposed model of this paper is applied for a real-world case study of Iranian tour agency and the results are analyzed under different circumstances.

  3. Expert Systems

    OpenAIRE

    Lucas, P.J.F.

    2005-01-01

    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...

  4. Fuzzy Expert System For The Selection Of Tourist Hotels

    OpenAIRE

    GOPAL SINGH

    2015-01-01

    In the present work a simple and very effective mathematical model is designed for tourist hotels of LEVEL 2. Location of hotels building structure of hotels quality of hotels feedback of hotels and advertisement of hotels are as input factors. Trapezoidal membership function and triangular membership function are used for fuzzification process and defuzzification is done by COG technique. The fuzzy logic has been utilized in several different approaches to modeling the selection of tourist h...

  5. Fuzzy Expert System For The Selection Of Tourist Hotels

    Directory of Open Access Journals (Sweden)

    GOPAL SINGH

    2015-08-01

    Full Text Available In the present work a simple and very effective mathematical model is designed for tourist hotels of LEVEL 2. Location of hotels building structure of hotels quality of hotels feedback of hotels and advertisement of hotels are as input factors. Trapezoidal membership function and triangular membership function are used for fuzzification process and defuzzification is done by COG technique. The fuzzy logic has been utilized in several different approaches to modeling the selection of tourist hotels process. This model addressed the hotel of LEVEL2 and this model concludes that the hotel is LEVEL 2 with degree of precision 52.15 .

  6. A fuzzy expert system to Trust-Based Access Control in crowdsourcing environments

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    Olusegun Folorunso

    2015-07-01

    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.

  7. Incorporating fuzzy data and logical relations in the design of expert systems for nuclear reactors

    International Nuclear Information System (INIS)

    Guth, M.A.S.

    1987-01-01

    This paper applies the method of assigning probability in Dempster-Shafer Theory (DST) to the components of rule-based expert systems used in the control of nuclear reactors. Probabilities are assigned to premises, consequences, and rules themselves. This paper considers how uncertainty can propagate through a system of Boolean equations, such as fault trees or expert systems. The probability masses assigned to primary initiating events in the expert system can be derived from observing a nuclear reactor in operation or based on engineering knowledge of the reactor parts. Use of DST mass assignments offers greater flexibility to the construction of expert systems in two important respects. First, DST mass assignments have the advantage over classical probability methods of accommodating when necessary uncommitted probability assignments. Thus the DST probability framework can incorporate expert system inputs from imprecise or fuzzy data. Second, DST applied to the Boolean rules themselves leads to a probabilistic logic, where a given rule may be valid with probability less than unity: fuzzy logical rules

  8. Application of Fuzzy Sets in an Expert System For Technological Process Management

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    Filip Tošenovský

    2011-12-01

    Full Text Available The paper is preoccupied with application of an expert system in the management of a process with one input and one output, using the fuzzy set theory. It resolves the problem of formalization of a verbal description of the process management coupled with the use of process operator’s experience. The procedure that calculates regulatory intervention in the process is presented and accompanied by graphical illustrations.

  9. An expert system design incorporating fuzzy logic for diagnosing heat imbalances in a nuclear power plant

    International Nuclear Information System (INIS)

    Guth, M.A.S.

    1987-01-01

    This paper presents an expert system for diagnosing problems in the interface between the heat exchanger and the core of a nuclear power plant for a hypothetical pressurized water reactor (PWR). The expert system has a production rule backward-chaining-based architecture, and the knowledge base incorporates four kinds of information. First, the structural relationship between causes and consequences is given by nuclear engineering experts. Second, numerical values for the initiating events can be taken from observed performance of the reactor under normal conditions. Third, the causes of particular events are ranked in order of their likelihood based on a combination of a priori knowledge about the reactor design and actual data on the incidence of component failures. Fourth, Bellman-Zadeh Fuzzy Logic is introduced to maintain truth values for expert system rules that hold with varying degrees of certainty

  10. The use of Fuzzy expert system in robots decision-making

    International Nuclear Information System (INIS)

    Jamaseb, Mehdi; Jafari, Shahram; Montaseri, Farshid; Dadgar, Masoud

    2014-01-01

    The main issue that is investigated in this paper, is a method for decision making of mobile robots in different conditions for this purpose, we have used expert system. In this way, that the conditions of the robot are analyzed by on expert person a special issue (like following a ball) using knowledge base and suitable decisions will be mode. Then, using this information fuzzy rules well be built, and using its rules, robots decisions can be implemented like an expert person. In this study, we have used delta3d base for implementing expert systems and CLIPS and also we have used NAO for simulation rcssserver3d robot and 3d football simulation have been used for implementing operation program

  11. Using Fuzzy Logic to Increase the Accuracy of E-Commerce Risk Assessment Based on an Expert System

    Directory of Open Access Journals (Sweden)

    H. Beheshti

    2017-12-01

    Full Text Available Strong adaptive control can be exercised even without access to accurate data inputs. Such control is possible through fuzzy mathematics, which is a meta-collection of Boolean logic principles that imply relative accuracy. Fuzzy mathematics find applications in e-commerce, where different risk analysis methods are available for risk assessment and estimation. Such approaches can be quantitative or qualitative, depending on the type of examined data. Quantitative methods are grounded in statistics, whereas qualitative methods are based on expert judgments and fuzzy set theory. Given that qualitative methods are very subjective and deal with vague or inaccurate data, fuzzy logic can be used to extract useful information from data inaccuracies. In this study, a model based on the opinions of e-commerce security experts was designed and implemented by using fuzzy expert systems and MATLAB. A case study was conducted to validate the effectiveness of the Model.

  12. An Expert System for Diagnosis of Sleep Disorder Using Fuzzy Rule-Based Classification Systems

    Science.gov (United States)

    Septem Riza, Lala; Pradini, Mila; Fitrajaya Rahman, Eka; Rasim

    2017-03-01

    Sleep disorder is an anomaly that could cause problems for someone’ sleeping pattern. Nowadays, it becomes an issue since people are getting busy with their own business and have no time to visit the doctors. Therefore, this research aims to develop a system used for diagnosis of sleep disorder using Fuzzy Rule-Based Classification System (FRBCS). FRBCS is a method based on the fuzzy set concepts. It consists of two steps: (i) constructing a model/knowledge involving rulebase and database, and (ii) prediction over new data. In this case, the knowledge is obtained from experts whereas in the prediction stage, we perform fuzzification, inference, and classification. Then, a platform implementing the method is built with a combination between PHP and the R programming language using the “Shiny” package. To validate the system that has been made, some experiments have been done using data from a psychiatric hospital in West Java, Indonesia. Accuracy of the result and computation time are 84.85% and 0.0133 seconds, respectively.

  13. Expert system for fault diagnosis in process control valves using fuzzy-logic

    International Nuclear Information System (INIS)

    Carneiro, Alvaro L.G.; Porto Junior, Almir C.S.

    2013-01-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a rule base

  14. Expert system for fault diagnosis in process control valves using fuzzy-logic

    Energy Technology Data Exchange (ETDEWEB)

    Carneiro, Alvaro L.G., E-mail: carneiro@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Porto Junior, Almir C.S., E-mail: almir@ctmsp.mar.mil.br [Centro Tecnologico da Marinha em Sao Paulo (CIANA/CTMSP), Ipero, SP (Brazil). Centro de Instrucao e Adestramento Nuclear de ARAMAR

    2013-07-01

    The models of asset maintenance of a process plant basically are classified in corrective maintenance, preventive, predictive and proactive (online). The corrective maintenance is the elementary and most obvious way of the maintenance models. The preventive maintenance consists in a fault prevention work, based on statistical studies that can lead to low efficiency or even an unexpected shutdown of the plant. Predictive maintenance aims to prevent equipment or systems failures through monitoring and tracking of parameters, allowing continuous operation as long as possible. The proactive maintenance usually includes predictive maintenance, emphasizing the root cause analysis of the failure. The maintenance predictive/proactive planning frequently uses software that integrates data from different systems, which facilitates a quick and effective decision- making. In nuclear plants this model has an important role regarding the reliability of equipment and systems. The main focus of this work is to study the development of a model of non-intrusive monitoring and diagnosis applied to process control valves using artificial intelligence by fuzzy logic technique, contributing in the development of predictive methodologies identifying faults in incipient state. The control valve analyzed belongs to a steam plant which simulates the secondary circuit of a PWR nuclear reactor - Pressurized Water Reactor. This study makes use of MATLAB language through the fuzzy logic toolbox which uses the method of inference Mamdani, acting by fuzzy conjunction, through Triangular Norms (t-norm) and Triangular Conorms (t-conorm). As input variables are used air pressure and displacement of the valve stem. Input data coming into the fuzzy system by graph of the automation system Delta V ® available in the plant, which receives a signal of electric current from an 'intelligent' positioned installed on the valve. The output variable is the 'status' of the valve. Through a

  15. Development of an evolutionary fuzzy expert system for estimating future behavior of stock price

    Science.gov (United States)

    Mehmanpazir, Farhad; Asadi, Shahrokh

    2017-03-01

    The stock market has always been an attractive area for researchers since no method has been found yet to predict the stock price behavior precisely. Due to its high rate of uncertainty and volatility, it carries a higher risk than any other investment area, thus the stock price behavior is difficult to simulation. This paper presents a "data mining-based evolutionary fuzzy expert system" (DEFES) approach to estimate the behavior of stock price. This tool is developed in seven-stage architecture. Data mining is used in three stages to reduce the complexity of the whole data space. The first stage, noise filtering, is used to make our raw data clean and smooth. Variable selection is second stage; we use stepwise regression analysis to choose the key variables been considered in the model. In the third stage, K-means is used to divide the data into sub-populations to decrease the effects of noise and rebate complexity of the patterns. At next stage, extraction of Mamdani type fuzzy rule-based system will be carried out for each cluster by means of genetic algorithm and evolutionary strategy. In the fifth stage, we use binary genetic algorithm to rule filtering to remove the redundant rules in order to solve over learning phenomenon. In the sixth stage, we utilize the genetic tuning process to slightly adjust the shape of the membership functions. Last stage is the testing performance of tool and adjusts parameters. This is the first study on using an approximate fuzzy rule base system and evolutionary strategy with the ability of extracting the whole knowledge base of fuzzy expert system for stock price forecasting problems. The superiority and applicability of DEFES are shown for International Business Machines Corporation and compared the outcome with the results of the other methods. Results with MAPE metric and Wilcoxon signed ranks test indicate that DEFES provides more accuracy and outperforms all previous methods, so it can be considered as a superior tool for

  16. A Simple and Effective Remedial Learning System with a Fuzzy Expert System

    Science.gov (United States)

    Lin, C.-C.; Guo, K.-H.; Lin, Y.-C.

    2016-01-01

    This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…

  17. Expert System for Competences Evaluation 360° Feedback Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Alberto Alfonso Aguilar Lasserre

    2014-01-01

    Full Text Available Performance evaluation (PE is a process that estimates the employee overall performance during a given period, and it is a common function carried out inside modern companies. PE is important because it is an instrument that encourages employees, organizational areas, and the whole company to have an appropriate behavior and continuous improvement. In addition, PE is useful in decision making about personnel allocation, productivity bonuses, incentives, promotions, disciplinary measures, and dismissals. There are many performance evaluation methods; however, none is universal and common to all companies. This paper proposes an expert performance evaluation system based on a fuzzy logic model, with competences 360° feedback oriented to human behavior. This model uses linguistic labels and adjustable numerical values to represent ambiguous concepts, such as imprecision and subjectivity. The model was validated in the administrative department of a real Mexican manufacturing company, where final results and conclusions show the fuzzy logic method advantages in comparison with traditional 360° performance evaluation methodologies.

  18. Selected Aircraft Throttle Controller With Support Of Fuzzy Expert Inference System

    Directory of Open Access Journals (Sweden)

    Żurek Józef

    2014-12-01

    Full Text Available The paper describes Zlin 143Lsi aircraft engine work parameters control support method – hourly fuel flow as a main factor under consideration. The method concerns project of aircraft throttle control support system with use of fuzzy logic (fuzzy inference. The primary purpose of the system is aircraft performance optimization, reducing flight cost at the same time and support proper aircraft engine maintenance. Matlab Software and Fuzzy Logic Toolbox were used in the project. Work of the system is presented with use of twenty test samples, five of them are presented graphically. In addition, system control surface, included in the paper, supports system all work range analysis.

  19. Use of an on-line Fuzzy-logic expert system for water chemistry

    International Nuclear Information System (INIS)

    Fandrich, J.; Metzner, W.

    1998-01-01

    The requirements for availability and operating economy of power plants have become steadily more stringent over the last few years. In addition to technological advances (e.g. in the form of new design measures, processes and materials), manufacturers have also increasingly applied secondary measures to enhance the safety and operating economy of power plant units. These include ever more sophisticated process monitoring and analytical systems and, (in recent times) diagnostic systems which perform continuous assessment of the plant condition to allow imminent changes that cam lead to damage and faults to be detected at the earliest possible time. The following paper presents an expert system, based on Fuzzy logic, which is used to perform a wide variety of tasks in the field of NPP water chemistry diagnostics. Thanks to the general nature of the approach selected, the system kernel is identical for all solutions which were implemented despite the wide variety of tasks and their diverse needs. This would not have been possible without the development and application of powerful and flexible engineering tools which can provide solutions to different types of problems at no extra effort. It will be shown in which way the system builds up diagnoses from the collected on-line data via a system -specific and easy- to-learn language and several tools. The presented module DIWA (Diagnostic System of Water Chemistry) was directly derived from the DIGEST system (diagnostic expert system for turbomachinery), which was developed over the last few years at the Power Generation Group (KWU) of the Siemens AG. (author)

  20. Expert evaluation of innovation projects of mining enterprises on the basis of methods of system analysis and fuzzy logics

    Directory of Open Access Journals (Sweden)

    Pimonov Alexander

    2017-01-01

    Full Text Available This paper presents the multipurpose approach to evaluation of research and innovation projects based on the method of analysis of hierarchies and fuzzy logics for the mining industry. The approach, implemented as part of a decision support system, can reduce the degree of subjectivity during examinations by taking into account both quantitative and qualitative characteristics of the compared innovative alternatives; it does not depend on specific conditions of examination and allows engagement of experts of various fields of knowledge. The system includes the mechanism of coordination of several experts’ views. Using of fuzzy logics allows evaluating the qualitative characteristics of innovations in the form of formalized logical conclusions.

  1. Fuzzy Concurrent Object Oriented Expert System for Fault Diagnosis in 8085 Microprocessor Based System Board

    OpenAIRE

    Mr.D. V. Kodavade; Dr. Mrs.S.D.Apte

    2014-01-01

    With the acceptance of artificial intelligence paradigm, a number of successful artificial intelligence systems were created. Fault diagnosis in microprocessor based boards needs lot of empirical knowledge and expertise and is a true artificial intelligence problem. Research on fault diagnosis in microprocessor based system boards using new fuzzy-object oriented approach is presented in this paper. There are many uncertain situations observed during fault diagnosis. These uncertain situations...

  2. Incorporation of expert variability into breast cancer treatment recommendation in designing clinical protocol guided fuzzy rule system models.

    Science.gov (United States)

    Garibaldi, Jonathan M; Zhou, Shang-Ming; Wang, Xiao-Ying; John, Robert I; Ellis, Ian O

    2012-06-01

    It has been often demonstrated that clinicians exhibit both inter-expert and intra-expert variability when making difficult decisions. In contrast, the vast majority of computerized models that aim to provide automated support for such decisions do not explicitly recognize or replicate this variability. Furthermore, the perfect consistency of computerized models is often presented as a de facto benefit. In this paper, we describe a novel approach to incorporate variability within a fuzzy inference system using non-stationary fuzzy sets in order to replicate human variability. We apply our approach to a decision problem concerning the recommendation of post-operative breast cancer treatment; specifically, whether or not to administer chemotherapy based on assessment of five clinical variables: NPI (the Nottingham Prognostic Index), estrogen receptor status, vascular invasion, age and lymph node status. In doing so, we explore whether such explicit modeling of variability provides any performance advantage over a more conventional fuzzy approach, when tested on a set of 1310 unselected cases collected over a fourteen year period at the Nottingham University Hospitals NHS Trust, UK. The experimental results show that the standard fuzzy inference system (that does not model variability) achieves overall agreement to clinical practice around 84.6% (95% CI: 84.1-84.9%), while the non-stationary fuzzy model can significantly increase performance to around 88.1% (95% CI: 88.0-88.2%), psystems in any application domain. Copyright © 2012 Elsevier Inc. All rights reserved.

  3. A fuzzy logic expert system for evaluating policy progress towards sustainability goals.

    Science.gov (United States)

    Cisneros-Montemayor, Andrés M; Singh, Gerald G; Cheung, William W L

    2017-12-16

    Evaluating progress towards environmental sustainability goals can be difficult due to a lack of measurable benchmarks and insufficient or uncertain data. Marine settings are particularly challenging, as stakeholders and objectives tend to be less well defined and ecosystem components have high natural variability and are difficult to observe directly. Fuzzy logic expert systems are useful analytical frameworks to evaluate such systems, and we develop such a model here to formally evaluate progress towards sustainability targets based on diverse sets of indicators. Evaluation criteria include recent (since policy enactment) and historical (from earliest known state) change, type of indicators (state, benefit, pressure, response), time span and spatial scope, and the suitability of an indicator in reflecting progress toward a specific objective. A key aspect of the framework is that all assumptions are transparent and modifiable to fit different social and ecological contexts. We test the method by evaluating progress towards four Aichi Biodiversity Targets in Canadian oceans, including quantitative progress scores, information gaps, and the sensitivity of results to model and data assumptions. For Canadian marine systems, national protection plans and biodiversity awareness show good progress, but species and ecosystem states overall do not show strong improvement. Well-defined goals are vital for successful policy implementation, as ambiguity allows for conflicting potential indicators, which in natural systems increases uncertainty in progress evaluations. Importantly, our framework can be easily adapted to assess progress towards policy goals with different themes, globally or in specific regions.

  4. A New Similarity Measure of Interval-Valued Intuitionistic Fuzzy Sets Considering Its Hesitancy Degree and Applications in Expert Systems

    Directory of Open Access Journals (Sweden)

    Chong Wu

    2014-01-01

    Full Text Available As an important content in fuzzy mathematics, similarity measure is used to measure the similarity degree between two fuzzy sets. Considering the existing similarity measures, most of them do not consider the hesitancy degree and some methods considering the hesitancy degree are based on the intuitionistic fuzzy sets, intuitionistic fuzzy values. It may cause some counterintuitive results in some cases. In order to make up for the drawback, we present a new approach to construct the similarity measure between two interval-valued intuitionistic fuzzy sets using the entropy measure and considering the hesitancy degree. In particular, the proposed measure was demonstrated to yield a similarity measure. Besides, some examples are given to prove the practicality and effectiveness of the new measure. We also apply the similarity measure to expert system to solve the problems on pattern recognition and the multicriteria group decision making. In these examples, we also compare it with existing methods such as other similarity measures and the ideal point method.

  5. Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application

    International Nuclear Information System (INIS)

    Baraldi, Piero; Podofillini, Luca; Mkrtchyan, Lusine; Zio, Enrico; Dang, Vinh N.

    2015-01-01

    The use of expert systems can be helpful to improve the transparency and repeatability of assessments in areas of risk analysis with limited data available. In this field, human reliability analysis (HRA) is no exception, and, in particular, dependence analysis is an HRA task strongly based on analyst judgement. The analysis of dependence among Human Failure Events refers to the assessment of the effect of an earlier human failure on the probability of the subsequent ones. This paper analyses and compares two expert systems, based on Bayesian Belief Networks and Fuzzy Logic (a Fuzzy Expert System, FES), respectively. The comparison shows that a BBN approach should be preferred in all the cases characterized by quantifiable uncertainty in the input (i.e. when probability distributions can be assigned to describe the input parameters uncertainty), since it provides a satisfactory representation of the uncertainty and its output is directly interpretable for use within PSA. On the other hand, in cases characterized by very limited knowledge, an analyst may feel constrained by the probabilistic framework, which requires assigning probability distributions for describing uncertainty. In these cases, the FES seems to lead to a more transparent representation of the input and output uncertainty. - Highlights: • We analyse treatment of uncertainty in two expert systems. • We compare a Bayesian Belief Network (BBN) and a Fuzzy Expert System (FES). • We focus on the input assessment, inference engines and output assessment. • We focus on an application problem of interest for human reliability analysis. • We emphasize the application rather than math to reach non-BBN or FES specialists

  6. Genetic Learning of Fuzzy Expert Systems for Decision Support in the Automated Process of Wooden Boards Cutting

    Directory of Open Access Journals (Sweden)

    Yaroslav MATSYSHYN

    2014-03-01

    Full Text Available Sawing solid wood (lumber, wooden boards into blanks is an important technological operation, which has significant influence on the efficiency of the woodworking industry as a whole. Selecting a rational variant of lumber cutting is a complex multicriteria problem with many stochastic factors, characterized by incomplete information and fuzzy attributes. About this property by currently used automatic optimizing cross-cut saw is not always rational use of wood raw material. And since the optimization algorithms of these saw functions as a “black box”, their improvement is not possible. Therefore topical the task of developing a new approach to the optimal cross-cutting that takes into account stochastic properties of wood as a material from biological origin. Here we propose a new approach to the problem of lumber optimal cutting in the conditions of uncertainty of lumber quantity and fuzziness lengths of defect-free areas. To account for these conditions, we applied the methods of fuzzy sets theory and used a genetic algorithm to simulate the process of human learning in the implementation the technological operation. Thus, the rules of behavior with yet another defect-free area is defined in fuzzy expert system that can be configured to perform specific production tasks using genetic algorithm. The author's implementation of the genetic algorithm is used to set up the parameters of fuzzy expert system. Working capacity of the developed system verified on simulated and real-world data. Implementation of this approach will make it suitable for the control of automated or fully automatic optimizing cross cutting of solid wood.

  7. Fuzzy Expert System based on a Novel Hybrid Stem Cell (HSC) Algorithm for Classification of Micro Array Data.

    Science.gov (United States)

    Vijay, S Arul Antran; GaneshKumar, P

    2018-02-21

    In the growing scenario, microarray data is extensively used since it provides a more comprehensive understanding of genetic variants among diseases. As the gene expression samples have high dimensionality it becomes tedious to analyze the samples manually. Hence an automated system is needed to analyze these samples. The fuzzy expert system offers a clear classification when compared to the machine learning and statistical methodologies. In fuzzy classification, knowledge acquisition would be a major concern. Despite several existing approaches for knowledge acquisition much effort is necessary to enhance the learning process. This paper proposes an innovative Hybrid Stem Cell (HSC) algorithm that utilizes Ant Colony optimization and Stem Cell algorithm for designing fuzzy classification system to extract the informative rules to form the membership functions from the microarray dataset. The HSC algorithm uses a novel Adaptive Stem Cell Optimization (ASCO) to improve the points of membership function and Ant Colony Optimization to produce the near optimum rule set. In order to extract the most informative genes from the large microarray dataset a method called Mutual Information is used. The performance results of the proposed technique evaluated using the five microarray datasets are simulated. These results prove that the proposed Hybrid Stem Cell (HSC) algorithm produces a precise fuzzy system than the existing methodologies.

  8. Optimal operating rules definition in complex water resource systems combining fuzzy logic, expert criteria and stochastic programming

    Science.gov (United States)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2016-04-01

    This contribution presents a methodology for defining optimal seasonal operating rules in multireservoir systems coupling expert criteria and stochastic optimization. Both sources of information are combined using fuzzy logic. The structure of the operating rules is defined based on expert criteria, via a joint expert-technician framework consisting in a series of meetings, workshops and surveys carried out between reservoir managers and modelers. As a result, the decision-making process used by managers can be assessed and expressed using fuzzy logic: fuzzy rule-based systems are employed to represent the operating rules and fuzzy regression procedures are used for forecasting future inflows. Once done that, a stochastic optimization algorithm can be used to define optimal decisions and transform them into fuzzy rules. Finally, the optimal fuzzy rules and the inflow prediction scheme are combined into a Decision Support System for making seasonal forecasts and simulate the effect of different alternatives in response to the initial system state and the foreseen inflows. The approach presented has been applied to the Jucar River Basin (Spain). Reservoir managers explained how the system is operated, taking into account the reservoirs' states at the beginning of the irrigation season and the inflows previewed during that season. According to the information given by them, the Jucar River Basin operating policies were expressed via two fuzzy rule-based (FRB) systems that estimate the amount of water to be allocated to the users and how the reservoir storages should be balanced to guarantee those deliveries. A stochastic optimization model using Stochastic Dual Dynamic Programming (SDDP) was developed to define optimal decisions, which are transformed into optimal operating rules embedding them into the two FRBs previously created. As a benchmark, historical records are used to develop alternative operating rules. A fuzzy linear regression procedure was employed to

  9. Incorporating ''fuzzy'' data and logical relations in the design of expert systems for nuclear reactors

    International Nuclear Information System (INIS)

    Guth, M.A.S.

    1987-01-01

    This paper applies the method of assigning probability in Dempster-Shafer Theory (DST) to the components of rule-based expert systems used in the control of nuclear reactors. Probabilities are assigned to premises, consequences, and rules themselves. This paper considers how uncertainty can propagate through a system of Boolean equations, such as fault trees or expert systems. The probability masses assigned to primary initiating events in the expert system can be derived from observing a nuclear reactor in operation or based on engineering knowledge of the reactor parts. Use of DST mass assignments offers greater flexibility to the construction of expert systems

  10. Assessing the risk of pesticide environmental impact in several Argentinian cropping systems with a fuzzy expert indicator.

    Science.gov (United States)

    Arregui, María C; Sánchez, Daniel; Althaus, Rafael; Scotta, Roberto R; Bertolaccini, Isabel

    2010-07-01

    The introduction of transgenic soybean (Glycine max, L.) varieties resistant to glyphosate (GR soybeans) has rapidly expanded in Argentina, increasing pesticide use where only grasslands were previously cultivated. The authors compared an estimate of environmental risk for different crops and active ingredients using the IPEST index, which is based on a fuzzy-logic expert system. For IPEST calculations, four modules are defined, one reflecting the rate of application, the other three reflecting the risk for groundwater, surface water and air. The input variables are pesticide properties, site-specific conditions and characteristics of the pesticide application. The expert system calculates the value of modules according to the degree of membership of the input variables to the fuzzy subsets F (favourable) and U (unfavourable), and they can be aggregated following sets of decision rules. IPEST integrated values of >or= 7 reflect low environmental risk, and values of environmental contamination, and they are mainly used in maize. Groundwater was the most affected compartment. Fuzzy logic provided an easy tool combining different environmental components with pesticide properties to give a simple and accessible risk assessment. These findings provide information about active ingredients that should be replaced in order to protect water and air from pesticide contamination. Copyright (c) 2010 Society of Chemical Industry.

  11. Expert systems with fuzzy logic for intelligent diagnosis and control of nuclear power plants

    International Nuclear Information System (INIS)

    Abdelhai, M.I.; Upadhyaya, B.R.

    1990-01-01

    A model-based production-rule analysis system was developed for the tracking and diagnosis of the condition of a reactor coolant system (RCS) using a fuzzy logic algorithm. Since nuclear power plants are large and complex systems, it is natural that vagueness, uncertainty, and imprecision are introduced to such systems. Even in fully automated power plants, the critical diagnostic and control changes must be made by operators who usually express their diagnostic and control strategies linguistically as sets of heuristic decision rules. Therefore, additional imprecisions are introduced into the systems because of the imprecise nature of such qualitative strategies when they are converted into quantitative rules. Such problems, in which the source of imprecision is the absence of sharply defined criteria of class membership, could be dealt with using fuzzy set theory. Hence, a fuzzy logic algorithm could be initiated to implement a known heuristic whenever the given information is vague and qualitative, and it will allow operators to introduce certain linguistic assertions and commands to diagnose and control the system

  12. Fuzzy Logic-based expert system for evaluating cake quality of freeze-dried formulations.

    Science.gov (United States)

    Trnka, Hjalte; Wu, Jian X; Van De Weert, Marco; Grohganz, Holger; Rantanen, Jukka

    2013-12-01

    Freeze-drying of peptide and protein-based pharmaceuticals is an increasingly important field of research. The diverse nature of these compounds, limited understanding of excipient functionality, and difficult-to-analyze quality attributes together with the increasing importance of the 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 developed fuzzy logic-based system was found to give comparable quality scores with visual evaluation, making high-throughput classification of cake quality possible. © 2013 Wiley Periodicals, Inc. and the American Pharmacists Association.

  13. A Fuzzy Expert System for Distinguishing between Bacterial and Aseptic Meningitis

    Directory of Open Access Journals (Sweden)

    Mostafa Langarizadeh

    2015-05-01

    Full Text Available Introduction Bacterial meningitis is a known infectious disease which occurs at early ages and should be promptly diagnosed and treated. Bacterial and aseptic meningitis are hard to be distinguished. Therefore, physicians should be highly informed and experienced in this area. The main aim of this study was to suggest a system for distinguishing between bacterial and aseptic meningitis, using fuzzy logic.    Materials and Methods In the first step, proper attributes were selected using Weka 3.6.7 software. Six attributes were selected using Attribute Evaluator, InfoGainAttributeEval, and Ranker search method items. Then, a fuzzy inference engine was designed using MATLAB software, based on Mamdani’s fuzzy logic method with max-min composition, prod-probor, and centroid defuzzification. The rule base consisted of eight rules, based on the experience of three specialists and information extracted from textbooks. Results Data were extracted from 106 records of patients with meningitis (42 cases with bacterial meningitis in order to evaluate the proposed system. The system accuracy, specificity, and sensitivity were 89%, 92 %, and 97%, respectively. The area under the ROC curve was 0.93, and Kappa test revealed a good level of agreement (k=0.84, P

  14. Fuzzy Logic-based expert system for evaluating cake quality of freeze-dried formulations

    DEFF Research Database (Denmark)

    Trnka, Hjalte; Wu, Jian-Xiong; van de Weert, Marco

    2013-01-01

    Freeze-drying of peptide and protein-based pharmaceuticals is an increasingly important field of research. The diverse nature of these compounds, limited understanding of excipient functionality, and difficult-to-analyze quality attributes together with the increasing importance of the biosimilar......Freeze-drying of peptide and protein-based pharmaceuticals is an increasingly important field of research. The diverse nature of these compounds, limited understanding of excipient functionality, and difficult-to-analyze quality attributes together with the increasing importance...... 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 developed...

  15. Design of operating rules in complex water resources systems using historical records, expert criteria and fuzzy logic

    Science.gov (United States)

    Pulido-Velazquez, Manuel; Macian-Sorribes, Hector; María Benlliure-Moreno, Jose; Fullana-Montoro, Juan

    2015-04-01

    Water resources systems in areas with a strong tradition in water use are complex to manage by the high amount of constraints that overlap in time and space, creating a complicated framework in which past, present and future collide between them. In addition, it is usual to find "hidden constraints" in system operations, which condition operation decisions being unnoticed by anyone but the river managers and users. Being aware of those hidden constraints requires usually years of experience and a degree of involvement in that system's management operations normally beyond the possibilities of technicians. However, their impact in the management decisions is strongly imprinted in the historical data records available. The purpose of this contribution is to present a methodology capable of assessing operating rules in complex water resources systems combining historical records and expert criteria. Both sources are coupled using fuzzy logic. The procedure stages are: 1) organize expert-technicians preliminary meetings to let the first explain how they manage the system; 2) set up a fuzzy rule-based system (FRB) structure according to the way the system is managed; 3) use the historical records available to estimate the inputs' fuzzy numbers, to assign preliminary output values to the FRB rules and to train and validate these rules; 4) organize expert-technician meetings to discuss the rule structure and the input's quantification, returning if required to the second stage; 5) once the FRB structure is accepted, its output values must be refined and completed with the aid of the experts by using meetings, workshops or surveys; 6) combine the FRB with a Decision Support System (DSS) to simulate the effect of those management decisions; 7) compare its results with the ones offered by the historical records and/or simulation or optimization models; and 8) discuss with the stakeholders the model performance returning, if it's required, to the fifth or the second stage

  16. Breast cancer risk assessment and diagnosis model using fuzzy support vector machine based expert system

    Science.gov (United States)

    Dheeba, J.; Jaya, T.; Singh, N. Albert

    2017-09-01

    Classification of cancerous masses is a challenging task in many computerised detection systems. Cancerous masses are difficult to detect because these masses are obscured and subtle in mammograms. This paper investigates an intelligent classifier - fuzzy support vector machine (FSVM) applied to classify the tissues containing masses on mammograms for breast cancer diagnosis. The algorithm utilises texture features extracted using Laws texture energy measures and a FSVM to classify the suspicious masses. The new FSVM treats every feature as both normal and abnormal samples, but with different membership. By this way, the new FSVM have more generalisation ability to classify the masses in mammograms. The classifier analysed 219 clinical mammograms collected from breast cancer screening laboratory. The tests made on the real clinical mammograms shows that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and Laws texture features, the area under the Receiver operating characteristic curve reached .95, which corresponds to a sensitivity of 93.27% with a specificity of 87.17%. The results suggest that detecting masses using FSVM contribute to computer-aided detection of breast cancer and as a decision support system for radiologists.

  17. Expert systems

    International Nuclear Information System (INIS)

    Haldy, P.A.

    1988-01-01

    The definitions of the terms 'artificial intelligence' and 'expert systems', the methodology, areas of employment and limits of expert systems are discussed. The operation of an expert system is described, especially the presentation and organization of knowledge as well as interference and control. Methods and tools for expert system development are presented and their application in nuclear energy are briefly addressed. 7 figs., 2 tabs., 6 refs

  18. GIS Fuzzy Expert System for the assessment of ecosystems vulnerability to fire in managing Mediterranean natural protected areas.

    Science.gov (United States)

    Semeraro, Teodoro; Mastroleo, Giovanni; Aretano, Roberta; Facchinetti, Gisella; Zurlini, Giovanni; Petrosillo, Irene

    2016-03-01

    A significant threat to the natural and cultural heritage of Mediterranean natural protected areas (NPAs) is related to uncontrolled fires that can cause potential damages related to the loss or a reduction of ecosystems. The assessment and mapping of the vulnerability to fire can be useful to reduce landscape damages and to establish priority areas where it is necessary to plan measures to reduce the fire vulnerability. To this aim, a methodology based on an interactive computer-based system has been proposed in order to support NPA's management authority for the identification of vulnerable hotspots to fire through the selection of suitable indicators that allow discriminating different levels of sensitivity (e.g. Habitat relevance, Fragmentation, Fire behavior, Ecosystem Services, Vegetation recovery after fire) and stresses (agriculture, tourism, urbanization). In particular, a multi-criteria analysis based on Fuzzy Expert System (FES) integrated in a GIS environment has been developed in order to identify and map potential "hotspots" of fire vulnerability, where fire protection measures can be undertaken in advance. In order to test the effectiveness of this approach, this approach has been applied to the NPA of Torre Guaceto (Apulia Region, southern Italy). The most fire vulnerable areas are the patch of century-old forest characterized by high sensitivity and stress, and the wetlands and century-old olive groves due to their high sensitivity. The GIS fuzzy expert system provides evidence of its potential usefulness for the effective management of natural protected areas and can help conservation managers to plan and intervene in order to mitigate the fire vulnerability in accordance with conservation goals. Copyright © 2015 Elsevier Ltd. All rights reserved.

  19. EXPERT SYSTEMS

    OpenAIRE

    Georgiana Marin; Mihai Catalin Andrei

    2011-01-01

    In recent decades IT and computer systems have evolved rapidly in economic informatics field. The goal is to create user friendly information systems that respond promptly and accurately to requests. Informatics systems evolved into decision assisted systems, and such systems are converted, based on gained experience, in expert systems for creative problem solving that an organization is facing. Expert systems are aimed at rebuilding human reasoning on the expertise obtained from experts, sto...

  20. Expert System

    DEFF Research Database (Denmark)

    Hildebrandt, Thomas Troels; Cattani, Gian Luca

    2016-01-01

    An expert system is a computer system for inferring knowledge from a knowledge base, typically by using a set of inference rules. When the concept of expert systems was introduced at Stanford University in the early 1970s, the knowledge base was an unstructured set of facts. Today the knowledge b...... for the application of expert systems, but also raises issues regarding privacy and legal liability....

  1. Sugeno-Fuzzy Expert System Modeling for Quality Prediction of Non-Contact Machining Process

    Science.gov (United States)

    Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

    2018-03-01

    Modeling can be categorised into four main domains: prediction, optimisation, estimation and calibration. In this paper, the Takagi-Sugeno-Kang (TSK) fuzzy logic method is examined as a prediction modelling method to investigate the taper quality of laser lathing, which seeks to replace traditional lathe machines with 3D laser lathing in order to achieve the desired cylindrical shape of stock materials. Three design parameters were selected: feed rate, cutting speed and depth of cut. A total of twenty-four experiments were conducted with eight sequential runs and replicated three times. The results were found to be 99% of accuracy rate of the TSK fuzzy predictive model, which suggests that the model is a suitable and practical method for non-linear laser lathing process.

  2. Expert Opinion Elicitation Using Fuzzy Set Theory and Distempers-Shaker's Theory

    International Nuclear Information System (INIS)

    Yu, Donghan

    1993-01-01

    This study presents a new approach for expert opinion elicitation. The need to work with rare events and limited data is severe accident have led analysts to use expert opinions extensively. Unlike the conventional approaches using point-valued probabilities, the study proposes the concept of fuzzy probability to represent expert opinion. The use of fuzzy probability has an advantage over the conventional approach when an expert's judgment is used under limited data and imprecise knowledge. The study demonstrates a method of combining fuzzy probabilities in a manner consistent with the Distempers-Shaper's Theory (DDT). The propagation of fuzzy probabilities through a system is also introduced

  3. Introduction to fuzzy systems

    CERN Document Server

    Chen, Guanrong

    2005-01-01

    Introduction to Fuzzy Systems provides students with a self-contained introduction that requires no preliminary knowledge of fuzzy mathematics and fuzzy control systems theory. Simplified and readily accessible, it encourages both classroom and self-directed learners to build a solid foundation in fuzzy systems. After introducing the subject, the authors move directly into presenting real-world applications of fuzzy logic, revealing its practical flavor. This practicality is then followed by basic fuzzy systems theory. The book also offers a tutorial on fuzzy control theory, based mainly on th

  4. Design of interpretable fuzzy systems

    CERN Document Server

    Cpałka, Krzysztof

    2017-01-01

    This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.

  5. A Fuzzy Expert System for Distinguishing between Bacterial and Aseptic Meningitis

    Directory of Open Access Journals (Sweden)

    Mostafa Langarizadeh

    2015-05-01

    Data were extracted from 106 records of patients with meningitis (42 cases with bacterial meningitis in order to evaluate the proposed system. The system accuracy, specificity, and sensitivity were 89%, 92 %, and 97%, respectively. The area under the ROC curve was 0.93, and Kappa test revealed a good level of agreement (k=0.84, P

  6. Hemodynamic behavior modeling of a Virtual Surgical Patient based on a Fuzzy Expert System.

    Directory of Open Access Journals (Sweden)

    Paulo Farias Paiva

    2016-07-01

    Full Text Available The Virtual Reality (VR allows its users to experience a sense of being immersed in synthetic 3D scenarios generated by computer graphics. The so-called Virtual Environments (VEs based on RV can be applied to medical education, enabling: repetitive training and the development of psychomotor skills in surgical procedures without compromising real patients. Surgical simulators that feature Dynamic Virtual Patients (VPs, that is, reacts physiologically to interventions and medical decisions made during the training. These systems present more realism while it offers the possibility of varying clinical cases. This work has as main objective to discuss important issues of modeling the hemodynamic performance of a VP, specifically to simulate blood pressure values (both sistolic and diastolic variables. The model of a VP is presented as result as well as is presented an architecture for its integration to simulators based on VR.

  7. Probabilistic fuzzy systems as additive fuzzy systems

    NARCIS (Netherlands)

    Almeida, R.J.; Verbeek, N.; Kaymak, U.; Costa Sousa, da J.M.; Laurent, A.; Strauss, O.; Bouchon-Meunier, B.; Yager, R.

    2014-01-01

    Probabilistic fuzzy systems combine a linguistic description of the system behaviour with statistical properties of data. It was originally derived based on Zadeh’s concept of probability of a fuzzy event. Two possible and equivalent additive reasoning schemes were proposed, that lead to the

  8. Development of an Expert System as a Diagnostic Support of Cervical Cancer in Atypical Glandular Cells, Based on Fuzzy Logics and Image Interpretation

    Directory of Open Access Journals (Sweden)

    Karem R. Domínguez Hernández

    2013-01-01

    Full Text Available Cervical cancer is the second largest cause of death among women worldwide. Nowadays, this disease is preventable and curable at low cost and low risk when an accurate diagnosis is done in due time, since it is the neoplasm with the highest prevention potential. This work describes the development of an expert system able to provide a diagnosis to cervical neoplasia (CN precursor injuries through the integration of fuzzy logics and image interpretation techniques. The key contribution of this research focuses on atypical cases, specifically on atypical glandular cells (AGC. The expert system consists of 3 phases: (1 risk diagnosis which consists of the interpretation of a patient’s clinical background and the risks for contracting CN according to specialists; (2 cytology images detection which consists of image interpretation (IM and the Bethesda system for cytology interpretation, and (3 determination of cancer precursor injuries which consists of in retrieving the information from the prior phases and integrating the expert system by means of a fuzzy logics (FL model. During the validation stage of the system, 21 already diagnosed cases were tested with a positive correlation in which 100% effectiveness was obtained. The main contribution of this work relies on the reduction of false positives and false negatives by providing a more accurate diagnosis for CN.

  9. Expert Systems: What Is an Expert System?

    Science.gov (United States)

    Duval, Beverly K.; Main, Linda

    1994-01-01

    Describes expert systems and discusses their use in libraries. Highlights include parts of an expert system; expert system shells; an example of how to build an expert system; a bibliography of 34 sources of information on expert systems in libraries; and a list of 10 expert system shells used in libraries. (Contains five references.) (LRW)

  10. A study on the development of the on-line operator aid system using rule based expert system and fuzzy logic for nuclear power plants

    International Nuclear Information System (INIS)

    Kang, Ki Sig

    1995-02-01

    The on - line Operator Aid SYStem (OASYS) has been developed to support operator's decision making process and to ensure the safety of nuclear power plants (NPPs) by timely providing operators with proper guidelines according to the plant operation mode. The OASYS consists of four systems such as the signal validation and management system (SVMS), the plant monitoring system (PMS), the alarm filtering and diagnostic system (AFDS), and the dynamic emergency procedure tracking system (DEPTS). The SVMS and the PMS help operators to maintain a plant as a normal operation condition. The AFDS covers the abnormal events until they result in exceeding the limit range of reactor trip signals, while after a reactor trip, the DEPTS aids operators with proper guidelines so as to shutdown safely. The OASYS uses a rule based expert system and a fuzzy logic. The rule based expert system is used to classify the pre-defined events and track the emergency operating procedures (EOPs) through data processing. The fuzzy logic is used to generate the conceptual high level alarms for the prognostic diagnosis and to evaluate the qualitative fuzzy criteria used in EOPs. Performance assessment of the OASYS demonstrates that it is capable of diagnosing plant abnormal conditions and providing operators appropriate guidelines with fast response time and consistency. The developed technology for OASYS will be used to design the Integrated Advanced Control Room in which a plant can be operated by one operator during normal operation. The advanced EOP for emergency operation has been developed by focusing attention on the importance of the operators' role in emergency conditions. To overcome the complexity of current EOPs and maintain the consistency of operators' action according to plant emergency conditions, operator's tasks were allocated according to their duties in the advanced EOP and the computerized operator aid system (COAS) has been developed as an alternative to reduce operator

  11. Hybrid expert system

    International Nuclear Information System (INIS)

    Tsoukalas, L.; Ikonomopoulos, A.; Uhrig, R.E.

    1991-01-01

    This paper presents a methodology that couples rule-based expert systems using fuzzy logic, to pre-trained artificial neutral networks (ANN) for the purpose of transient identification in Nuclear Power Plants (NPP). In order to provide timely concise, and task-specific information about the may aspects of the transient and to determine the state of the system based on the interpretation of potentially noisy data a model-referenced approach is utilized. In it, the expert system performs the basic interpretation and processing of the model data, and pre-trained ANNs provide the model. having access to a set of neural networks that typify general categories of transients, the rule based system is able to perform identification functions. Membership functions - condensing information about a transient in a form convenient for a rule-based identification system characterizing a transient - are the output of neural computations. This allows the identification function to be performed with a speed comparable to or faster than that of the temporal evolution of the system. Simulator data form major secondary system pipe rupture is used to demonstrate the methodology. The results indicate excellent noise-tolerance for ANN's and suggest a new method for transient identification within the framework of Fuzzy Logic

  12. RISK REDUCTION WITH A FUZZY EXPERT EXPLORATION TOOL

    Energy Technology Data Exchange (ETDEWEB)

    Robert S. Balch; Ron Broadhead

    2005-03-01

    Incomplete or sparse data such as geologic or formation characteristics introduce a high level of risk for oil exploration and development projects. ''Expert'' systems developed and used in several disciplines and industries have demonstrated beneficial results when working with sparse data. State-of-the-art expert exploration tools, relying on a database, and computer maps generated by neural networks and user inputs, have been developed through the use of ''fuzzy'' logic, a mathematical treatment of imprecise or non-explicit parameters and values. Oil prospecting risk has been reduced with the use of these properly verified and validated ''Fuzzy Expert Exploration (FEE) Tools.'' Through the course of this project, FEE Tools and supporting software were developed for two producing formations in southeast New Mexico. Tools of this type can be beneficial in many regions of the U.S. by enabling risk reduction in oil and gas prospecting as well as decreased prospecting and development costs. In today's oil industry environment, many smaller exploration companies lack the resources of a pool of expert exploration personnel. Downsizing, volatile oil prices, and scarcity of domestic exploration funds have also affected larger companies, and will, with time, affect the end users of oil industry products in the U.S. as reserves are depleted. The FEE Tools benefit a diverse group in the U.S., allowing a more efficient use of scarce funds, and potentially reducing dependence on foreign oil and providing lower product prices for consumers.

  13. Approximations of Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Vinai K. Singh

    2013-03-01

    Full Text Available A fuzzy system can uniformly approximate any real continuous function on a compact domain to any degree of accuracy. Such results can be viewed as an existence of optimal fuzzy systems. Li-Xin Wang discussed a similar problem using Gaussian membership function and Stone-Weierstrass Theorem. He established that fuzzy systems, with product inference, centroid defuzzification and Gaussian functions are capable of approximating any real continuous function on a compact set to arbitrary accuracy. In this paper we study a similar approximation problem by using exponential membership functions

  14. RISK REDUCTION WITH A FUZZY EXPERT EXPLORATION TOOL

    Energy Technology Data Exchange (ETDEWEB)

    William W. Weiss

    2000-06-30

    Incomplete or sparse information on geologic or formation characteristics introduces a high level of risk for oil exploration and development projects. Expert systems have been developed and used in several disciplines and industries, including medical diagnostics, with favorable results. A state-of-the-art exploration ''expert'' tool, relying on a computerized data base and computer maps generated by neural networks, is proposed through the use of ''fuzzy'' logic, a relatively new mathematical treatment of imprecise or non-explicit parameters and values. This project will develop an Artificial Intelligence system that will draw upon a wide variety of information to provide realistic estimates of risk. ''Fuzzy logic,'' a system of integrating large amounts of inexact, incomplete information with modern computational methods to derive usable conclusions, has been demonstrated as a cost-effective computational technology in many industrial applications. During project year 1, 90% of geologic, geophysical, production and price data were assimilated for installation into the database. Logs provided geologic data consisting of formation tops of the Brushy Canyon, Lower Brushy Canyon, and Bone Springs zones of 700 wells used to construct regional cross sections. Regional structure and isopach maps were constructed using kriging to interpolate between the measured points. One of the structure derivative maps (azimuth of curvature) visually correlates with Brushy Canyon fields on the maximum change contours. Derivatives of the regional geophysical data also visually correlate with the location of the fields. The azimuth of maximum dip approximately locates fields on the maximum change contours. In a similar manner the second derivative in the x-direction of the gravity map visually correlates with the alignment of the known fields. The visual correlations strongly suggest that neural network architectures will be

  15. CAWRES: A Waveform Retracking Fuzzy Expert System for Optimizing Coastal Sea Levels from Jason-1 and Jason-2 Satellite Altimetry Data

    Directory of Open Access Journals (Sweden)

    Nurul Hazrina Idris

    2017-06-01

    Full Text Available This paper presents the Coastal Altimetry Waveform Retracking Expert System (CAWRES, a novel method to optimise the Jason satellite altimetric sea levels from multiple retracking solutions. CAWRES’ aim is to achieve the highest possible accuracy of coastal sea levels, thus bringing measurement of radar altimetry data closer to the coast. The principles of CAWRES are twofold. The first is to reprocess altimeter waveforms using the optimal retracker, which is sought based on the analysis from a fuzzy expert system. The second is to minimise the relative offset in the retrieved sea levels caused by switching from one retracker to another using a neural network. The innovative system is validated against geoid height and tide gauges in the Great Barrier Reef, Australia for Jason-1 and Jason-2 satellite missions. The regional investigations have demonstrated that the CAWRES can effectively enhance the quality of 20 Hz sea level data and recover up to 16% more data than the standard MLE4 retracker over the tested region. Comparison against tide gauge indicates that the CAWRES sea levels are more reliable than those of Sensor Geophysical Data Records (SGDR products, because the former has a higher (≥0.77 temporal correlation and smaller (≤19 cm root mean square errors. The results demonstrate that the CAWRES can be applied to coastal regions elsewhere as well as other satellite altimeter missions.

  16. A semi-linguistic approach based on fuzzy set theory: application to expert judgments aggregation

    International Nuclear Information System (INIS)

    Ghyym, Seong Ho

    1998-01-01

    In the present work, a semi-linguistic fuzzy algorithm is proposed to obtain the fuzzy weighting values for multi-criterion, multi-alternative performance evaluation problem, with application to the aggregated estimate in the aggregation process of multi-expert judgments. The algorithm framework proposed is composed of the hierarchical structure, the semi-linguistic approach, the fuzzy R-L type integral value, and the total risk attitude index. In this work, extending the Chang/Chen method for triangular fuzzy numbers, the total risk attitude index is devised for a trapezoidal fuzzy number system. To illustrate the application of the algorithm proposed, a case problem available in literature is studied in connection to the weighting value evaluation of three-alternative (i.e., the aggregation of three-expert judgments) under seven-criterion. The evaluation results such as overall utility value, aggregation weighting value, and aggregated estimate obtained using the present fuzzy model are compared with those for other fuzzy models based on the Kim/Park method, the Liou/Wang method, and the Chang/Chen method

  17. A semi-linguistic approach based on fuzzy set theory: application to expert judgments aggregation

    Energy Technology Data Exchange (ETDEWEB)

    Ghyym, Seong Ho [KEPRI, Taejon (Korea, Republic of)

    1998-10-01

    In the present work, a semi-linguistic fuzzy algorithm is proposed to obtain the fuzzy weighting values for multi-criterion, multi-alternative performance evaluation problem, with application to the aggregated estimate in the aggregation process of multi-expert judgments. The algorithm framework proposed is composed of the hierarchical structure, the semi-linguistic approach, the fuzzy R-L type integral value, and the total risk attitude index. In this work, extending the Chang/Chen method for triangular fuzzy numbers, the total risk attitude index is devised for a trapezoidal fuzzy number system. To illustrate the application of the algorithm proposed, a case problem available in literature is studied in connection to the weighting value evaluation of three-alternative (i.e., the aggregation of three-expert judgments) under seven-criterion. The evaluation results such as overall utility value, aggregation weighting value, and aggregated estimate obtained using the present fuzzy model are compared with those for other fuzzy models based on the Kim/Park method, the Liou/Wang method, and the Chang/Chen method.

  18. Medical Expert Systems Survey

    OpenAIRE

    Abu-Nasser, Bassem S.

    2017-01-01

    International audience; There is an increased interest in the area of Artificial Intelligence in general and expert systems in particular. Expert systems are rapidly growing technology. Expert systems are a branch of Artificial Intelligence which is having a great impact on many fields of human life. Expert systems use human expert knowledge to solve complex problems in many fields such as Health, science, engineering, business, and weather forecasting. Organizations employing the technology ...

  19. Expert systems to assist plant operation

    International Nuclear Information System (INIS)

    Matsumoto, Yoshihiro; Mori, Nobuyuki; Wada, Norio

    1985-01-01

    Large-scale real-time process control systems, such as those for electric power dispatching, large thermal and nuclear power stations, steel mill plants and manufacturing automation systems, need expert systems to assist operator's decision. The expert systems newly developed to fulfill the requirement are founded on OKBS (object oriented knowledge based system). OKBS provides various object types: fuzzy logic type, production rule type, frame type, state transition type, abstract data type and input/output transformation type. (author)

  20. Classification of jet fuel properties by near-infrared spectroscopy using fuzzy rule-building expert systems and support vector machines.

    Science.gov (United States)

    Xu, Zhanfeng; Bunker, Christopher E; Harrington, Peter de B

    2010-11-01

    Monitoring the changes of jet fuel physical properties is important because fuel used in high-performance aircraft must meet rigorous specifications. Near-infrared (NIR) spectroscopy is a fast method to characterize fuels. Because of the complexity of NIR spectral data, chemometric techniques are used to extract relevant information from spectral data to accurately classify physical properties of complex fuel samples. In this work, discrimination of fuel types and classification of flash point, freezing point, boiling point (10%, v/v), boiling point (50%, v/v), and boiling point (90%, v/v) of jet fuels (JP-5, JP-8, Jet A, and Jet A1) were investigated. Each physical property was divided into three classes, low, medium, and high ranges, using two evaluations with different class boundary definitions. The class boundaries function as the threshold to alarm when the fuel properties change. Optimal partial least squares discriminant analysis (oPLS-DA), fuzzy rule-building expert system (FuRES), and support vector machines (SVM) were used to build the calibration models between the NIR spectra and classes of physical property of jet fuels. OPLS-DA, FuRES, and SVM were compared with respect to prediction accuracy. The validation of the calibration model was conducted by applying bootstrap Latin partition (BLP), which gives a measure of precision. Prediction accuracy of 97 ± 2% of the flash point, 94 ± 2% of freezing point, 99 ± 1% of the boiling point (10%, v/v), 98 ± 2% of the boiling point (50%, v/v), and 96 ± 1% of the boiling point (90%, v/v) were obtained by FuRES in one boundaries definition. Both FuRES and SVM obtained statistically better prediction accuracy over those obtained by oPLS-DA. The results indicate that combined with chemometric classifiers NIR spectroscopy could be a fast method to monitor the changes of jet fuel physical properties.

  1. How to Fully Represent Expert Information about Imprecise Properties in a Computer System – Random Sets, Fuzzy Sets, and Beyond: An Overview

    Science.gov (United States)

    Nguyen, Hung T.; Kreinovich, Vladik

    2014-01-01

    To help computers make better decisions, it is desirable to describe all our knowledge in computer-understandable terms. This is easy for knowledge described in terms on numerical values: we simply store the corresponding numbers in the computer. This is also easy for knowledge about precise (well-defined) properties which are either true or false for each object: we simply store the corresponding “true” and “false” values in the computer. The challenge is how to store information about imprecise properties. In this paper, we overview different ways to fully store the expert information about imprecise properties. We show that in the simplest case, when the only source of imprecision is disagreement between different experts, a natural way to store all the expert information is to use random sets; we also show how fuzzy sets naturally appear in such random-set representation. We then show how the random-set representation can be extended to the general (“fuzzy”) case when, in addition to disagreements, experts are also unsure whether some objects satisfy certain properties or not. PMID:25386045

  2. Radial Fuzzy Systems

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2017-01-01

    Roč. 319, 15 July (2017), s. 1-27 ISSN 0165-0114 R&D Projects: GA MŠk(CZ) LD13002 Institutional support: RVO:67985807 Keywords : fuzzy systems * radial functions * coherence Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.718, year: 2016

  3. Risk Reduction with a Fuzzy Expert Exploration Tool

    Energy Technology Data Exchange (ETDEWEB)

    Weiss, William W.; Broadhead, Ron; Sung, Andrew

    2000-10-24

    This project developed an Artificial Intelligence system that drew up on a wide variety of information in providing realistic estimates of risk. ''Fuzzy logic,'' a system of integrating large amounts of inexact, incomplete information with modern computational methods derived usable conclusions, were demonstrated as a cost-effective computational technology in many industrial applications.

  4. Expert system technology for nondestructive waste assay

    International Nuclear Information System (INIS)

    Becker, G.K.; Determan, J.C.

    1998-01-01

    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

  5. ASSESSMENT OF POWER QUALITY DISTURBANCE USING EXPERT SYSTEM

    OpenAIRE

    A.N.MALLESWARA RAO,; Dr. K.RAMESH REDDY,; Dr. B.V.SANKER RAM

    2011-01-01

    This paper describes a fuzzy expert system in order to understand and deal with power quality problems encountered in distribution systems in a better way. Because of the technology and software now available this monitoring is highly effective, the fuzzy expert system not only can provide information about the quality of the power and the causes of power system disturbances, but it can identify problem conditions throughout the system before they cause widespread customer complains and equip...

  6. Expert system in PNC, 2

    International Nuclear Information System (INIS)

    Iijima, Takashi; Takahashi, Hidetaka; Nakajima, Yoshiaki

    1990-01-01

    The fuzzy logic control system for steam drum water level control of Fugen NPS was developed by PNC. The system consists of process interface device, fuzzy inference calculating device and engineering work station (EWS). Some qualitative characteristics on the steam drum water level control and flexible and heuristic control strategy employed by humans can be described by fuzzy linguistic rules using some linguistic valuables defined by membership functions. The EWS has some useful functions for development of fuzzy logic control method, such as on-line setting up or change the control rules, data logging, verification of the fuzzy inference calculating device, etc. And all incoming process signals, a process of fuzzy inference calculation and its result are on-line displayed every 1 second. This paper describes outline of the feed water control system of Fugen and the functions of the fuzzy logic control system. (author)

  7. A polythematic real-time synergistic hybrid data telecommunication system for scientific research with bidirectional fuzzy feedback peer review by expert referees

    Directory of Open Access Journals (Sweden)

    Panagiotis Petratos

    2003-02-01

    Full Text Available Heterogeneous research environments, interests and locations do not necessarily coincide, thus hitherto the primary method of communication amongst researchers has been email. In this article a novel unified polythematic, real-time, synergistic, data telecommunication system is proposed with peer-reviewed, bidirectional fuzzy feedback for research scientists, to facilitate scientific information exchange via the extensible markup language (XML on multiple scientific topics, e.g. in mathematics, physics, biology and chemistry.

  8. Application of expert systems

    Energy Technology Data Exchange (ETDEWEB)

    Basden, A

    1983-11-01

    This article seeks to bring together a number of issues relevant to the application of expert systems by discussing their advantages and limitations, their roles and benefits, and the influence that real-life applications might have on the design of expert systems software. Part of the expert systems strategy of one major chemical company is outlined. Because it was in constructing one particular expert system that many of these issues became important this system is described briefly at the start of the paper and used to illustrate much of the later discussion. It is of the plausible-inference type and has application in the field of materials engineering. 22 references.

  9. Real time expert systems

    International Nuclear Information System (INIS)

    Asami, Tohru; Hashimoto, Kazuo; Yamamoto, Seiichi

    1992-01-01

    Recently, aiming at the application to the plant control for nuclear reactors and traffic and communication control, the research and the practical use of the expert system suitable to real time processing have become conspicuous. In this report, the condition for the required function to control the object that dynamically changes within a limited time is presented, and the technical difference between the real time expert system developed so as to satisfy it and the expert system of conventional type is explained with the actual examples and from theoretical aspect. The expert system of conventional type has the technical base in the problem-solving equipment originating in STRIPS. The real time expert system is applied to the fields accompanied by surveillance and control, to which conventional expert system is hard to be applied. The requirement for the real time expert system, the example of the real time expert system, and as the techniques of realizing real time processing, the realization of interruption processing, dispersion processing, and the mechanism of maintaining the consistency of knowledge are explained. (K.I.)

  10. Expert systems: An overview

    International Nuclear Information System (INIS)

    Verdejo, F.

    1985-01-01

    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.)

  11. Computer Based Expert Systems.

    Science.gov (United States)

    Parry, James D.; Ferrara, Joseph M.

    1985-01-01

    Claims knowledge-based expert computer systems can meet needs of rural schools for affordable expert advice and support and will play an important role in the future of rural education. Describes potential applications in prediction, interpretation, diagnosis, remediation, planning, monitoring, and instruction. (NEC)

  12. BWR recirculation pump diagnostic expert system

    International Nuclear Information System (INIS)

    Chiang, S.C.; Morimoto, C.N.; Torres, M.R.

    2004-01-01

    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)

  13. Expert methods in control systems of deep oil and gas holes building

    Energy Technology Data Exchange (ETDEWEB)

    Sementsov, G.; Fadeeva, I.; Chigur, I. [State Technical Univ. of Oil and Gas, Ivano-Frankivsk (Ukraine)

    2000-07-01

    Attempts to provide self-control of process of long holing on oil and gas have not given due effect owing to complication of object, it fuzzy and equivocation of the information. In this connection it is offered to use for management of drilling expert systems, which one use fuzzy models and methods of the theory of fuzzy control systems. (orig.)

  14. Neuro-fuzzy system modeling based on automatic fuzzy clustering

    Institute of Scientific and Technical Information of China (English)

    Yuangang TANG; Fuchun SUN; Zengqi SUN

    2005-01-01

    A neuro-fuzzy system model based on automatic fuzzy clustering is proposed.A hybrid model identification algorithm is also developed to decide the model structure and model parameters.The algorithm mainly includes three parts:1) Automatic fuzzy C-means (AFCM),which is applied to generate fuzzy rules automatically,and then fix on the size of the neuro-fuzzy network,by which the complexity of system design is reducesd greatly at the price of the fitting capability;2) Recursive least square estimation (RLSE).It is used to update the parameters of Takagi-Sugeno model,which is employed to describe the behavior of the system;3) Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network.Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.

  15. Expert system technology for the military

    International Nuclear Information System (INIS)

    Franklin, J.E.; Carmody, C.L.; Buteau, B.L.; Keller, K.; Levitt, T.S.

    1988-01-01

    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

  16. Fuzzy fault diagnosis system of MCFC

    Institute of Scientific and Technical Information of China (English)

    Wang Zhenlei; Qian Feng; Cao Guangyi

    2005-01-01

    A kind of fault diagnosis system of molten carbonate fuel cell (MCFC) stack is proposed in this paper. It is composed of a fuzzy neural network (FNN) and a fault diagnosis element. FNN is able to deal with the information of the expert knowledge and the experiment data efficiently. It also has the ability to approximate any smooth system. FNN is used to identify the fault diagnosis model of MCFC stack. The fuzzy fault decision element can diagnose the state of the MCFC generating system, normal or fault, and can decide the type of the fault based on the outputs of FNN model and the MCFC system. Some simulation experiment results are demonstrated in this paper.

  17. Expert Systems Research.

    Science.gov (United States)

    Duda, Richard O.; Shortliffe, Edward H.

    1983-01-01

    Discusses a class of artificial intelligence computer programs (often called "expert systems" because they address problems normally thought to require human specialists for their solution) intended to serve as consultants for decision making. Also discusses accomplishments (including information systematization in medical diagnosis and…

  18. Design of an expert system based on neuro-fuzzy inference analyzer for on-line microstructural characterization using magnetic NDT method

    International Nuclear Information System (INIS)

    Ghanei, S.; Vafaeenezhad, H.; Kashefi, M.; Eivani, A.R.; Mazinani, M.

    2015-01-01

    Tracing microstructural evolution has a significant importance and priority in manufacturing lines of dual-phase steels. In this paper, an artificial intelligence method is presented for on-line microstructural characterization of dual-phase steels. A new method for microstructure characterization based on the theory of magnetic Barkhausen noise nondestructive testing method is introduced using adaptive neuro-fuzzy inference system (ANFIS). In order to predict the accurate martensite volume fraction of dual-phase steels while eliminating the effect and interference of frequency on the magnetic Barkhausen noise outputs, the magnetic responses were fed into the ANFIS structure in terms of position, height and width of the Barkhausen profiles. The results showed that ANFIS approach has the potential to detect and characterize microstructural evolution while the considerable effect of the frequency on magnetic outputs is overlooked. In fact implementing multiple outputs simultaneously enables ANFIS to approach to the accurate results using only height, position and width of the magnetic Barkhausen noise peaks without knowing the value of the used frequency. - Highlights: • New NDT system for microstructural evaluation based on MBN using ANFIS modeling. • Sensitivity of magnetic Barkhausen noise to microstructure changes of the DP steels. • Accurate prediction of martensite by feeding multiple MBN outputs simultaneously. • Obtaining the modeled output without knowing the amount of the used frequency

  19. Design of an expert system based on neuro-fuzzy inference analyzer for on-line microstructural characterization using magnetic NDT method

    Energy Technology Data Exchange (ETDEWEB)

    Ghanei, S., E-mail: Sadegh.Ghanei@yahoo.com [Department of Materials Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Azadi Square, Mashhad (Iran, Islamic Republic of); Vafaeenezhad, H. [Centre of Excellence for High Strength Alloys Technology (CEHSAT), School of Metallurgical and Materials Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran (Iran, Islamic Republic of); Kashefi, M. [Department of Materials Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Azadi Square, Mashhad (Iran, Islamic Republic of); Eivani, A.R. [Centre of Excellence for High Strength Alloys Technology (CEHSAT), School of Metallurgical and Materials Engineering, Iran University of Science and Technology (IUST), Narmak, Tehran (Iran, Islamic Republic of); Mazinani, M. [Department of Materials Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Azadi Square, Mashhad (Iran, Islamic Republic of)

    2015-04-01

    Tracing microstructural evolution has a significant importance and priority in manufacturing lines of dual-phase steels. In this paper, an artificial intelligence method is presented for on-line microstructural characterization of dual-phase steels. A new method for microstructure characterization based on the theory of magnetic Barkhausen noise nondestructive testing method is introduced using adaptive neuro-fuzzy inference system (ANFIS). In order to predict the accurate martensite volume fraction of dual-phase steels while eliminating the effect and interference of frequency on the magnetic Barkhausen noise outputs, the magnetic responses were fed into the ANFIS structure in terms of position, height and width of the Barkhausen profiles. The results showed that ANFIS approach has the potential to detect and characterize microstructural evolution while the considerable effect of the frequency on magnetic outputs is overlooked. In fact implementing multiple outputs simultaneously enables ANFIS to approach to the accurate results using only height, position and width of the magnetic Barkhausen noise peaks without knowing the value of the used frequency. - Highlights: • New NDT system for microstructural evaluation based on MBN using ANFIS modeling. • Sensitivity of magnetic Barkhausen noise to microstructure changes of the DP steels. • Accurate prediction of martensite by feeding multiple MBN outputs simultaneously. • Obtaining the modeled output without knowing the amount of the used frequency.

  20. ALICE Expert System

    CERN Document Server

    Ionita, C

    2014-01-01

    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...

  1. ALICE Expert System

    International Nuclear Information System (INIS)

    Ionita, C; Carena, F

    2014-01-01

    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 different 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 regular shifters during the next data taking period

  2. Designing of fuzzy expert heuristic models with cost management ...

    Indian Academy of Sciences (India)

    In genuine industrial case, problems are inescapable and pose enormous challenges to incorporate accurate sustainability factors into supplier selection. In this present study, three different primarily based multicriteria decision making fuzzy models have been compared with their deterministic version so as to resolve fuzzy ...

  3. Hierarchical fuzzy control of low-energy building systems

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Zhen; Dexter, Arthur [Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ (United Kingdom)

    2010-04-15

    A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profile can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort. (author)

  4. Use of fuzzy set theory in the aggregation of expert judgments

    International Nuclear Information System (INIS)

    Moon, Joo Hyun; Kang, Chang Sun

    1999-01-01

    It is sometimes impossible to make a correct decision in a certain engineering task without the help from professional expert judgments. Even though there are different expert opinions available, however, they should be appropriately aggregated to a useful form for making an acceptable engineering decision. This paper proposes a technique which utilizes the fuzzy set theory in the aggregation of expert judgments. In the technique, two main key concepts are employed: linguistic variables and fuzzy numbers. Linguistic variables first represent the relative importance of evaluation criteria under consideration and the degree of confidence on each expert perceived by the decision maker, and then are replaced by suitable triangular fuzzy numbers for arithmetic manipulation. As a benchmark problem, the pressure increment in the containment of Sequoyah nuclear power plant due to reactor vessel breach was estimated to verify and validate the proposed technique

  5. A brief history and technical review of the expert system research

    Science.gov (United States)

    Tan, Haocheng

    2017-09-01

    The expert system is a computer system that emulates the decision-making ability of a human expert, which aims to solve complex problems by reasoning knowledge. It is an important branch of artificial intelligence. In this paper, firstly, we briefly introduce the development and basic structure of the expert system. Then, from the perspective of the enabling technology, we classify the current expert systems and elaborate four expert systems: The Rule-Based Expert System, the Framework-Based Expert System, the Fuzzy Logic-Based Expert System and the Expert System Based on Neural Network.

  6. Efficient fuzzy Bayesian inference algorithms for incorporating expert knowledge in parameter estimation

    Science.gov (United States)

    Rajabi, Mohammad Mahdi; Ataie-Ashtiani, Behzad

    2016-05-01

    Bayesian inference has traditionally been conceived as the proper framework for the formal incorporation of expert knowledge in parameter estimation of groundwater models. However, conventional Bayesian inference is incapable of taking into account the imprecision essentially embedded in expert provided information. In order to solve this problem, a number of extensions to conventional Bayesian inference have been introduced in recent years. One of these extensions is 'fuzzy Bayesian inference' which is the result of integrating fuzzy techniques into Bayesian statistics. Fuzzy Bayesian inference has a number of desirable features which makes it an attractive approach for incorporating expert knowledge in the parameter estimation process of groundwater models: (1) it is well adapted to the nature of expert provided information, (2) it allows to distinguishably model both uncertainty and imprecision, and (3) it presents a framework for fusing expert provided information regarding the various inputs of the Bayesian inference algorithm. However an important obstacle in employing fuzzy Bayesian inference in groundwater numerical modeling applications is the computational burden, as the required number of numerical model simulations often becomes extremely exhaustive and often computationally infeasible. In this paper, a novel approach of accelerating the fuzzy Bayesian inference algorithm is proposed which is based on using approximate posterior distributions derived from surrogate modeling, as a screening tool in the computations. The proposed approach is first applied to a synthetic test case of seawater intrusion (SWI) in a coastal aquifer. It is shown that for this synthetic test case, the proposed approach decreases the number of required numerical simulations by an order of magnitude. Then the proposed approach is applied to a real-world test case involving three-dimensional numerical modeling of SWI in Kish Island, located in the Persian Gulf. An expert

  7. Expert System for Diagnosis of Hepatitis B Ibrahim Mailafiya, Fatima ...

    African Journals Online (AJOL)

    the rice plant appearing during their life span. [1]. ... use of intelligent systems such as fuzzy logic, artificial neural network and genetic algorithm have been developed [5]. ... The liver being the ..... doctors but to assist them in the quality ... P.Santosh Kumar Patra, An Expert System for Diagnosis of Human diseases, 2010.

  8. Expert system in PNC, 5

    International Nuclear Information System (INIS)

    Tobita, Yoshimasa; Yamaguchi, Takashi; Matsumoto, Mitsuo; Ono, Kiyoshi.

    1990-01-01

    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)

  9. Expert Systems in Reference Services.

    Science.gov (United States)

    Roysdon, Christine, Ed.; White, Howard D., Ed.

    1989-01-01

    Eleven articles introduce expert systems applications in library and information science, and present design and implementation issues of system development for reference services. Topics covered include knowledge based systems, prototype development, the use of artificial intelligence to remedy current system inadequacies, and an expert system to…

  10. The First Expert CAI System

    Science.gov (United States)

    Feurzeig, Wallace

    1984-01-01

    The first expert instructional system, the Socratic System, was developed in 1964. One of the earliest applications of this system was in the area of differential diagnosis in clinical medicine. The power of the underlying instructional paradigm was demonstrated and the potential of the approach for valuably supplementing medical instruction was recognized. Twenty years later, despite further educationally significant advances in expert systems technology and enormous reductions in the cost of computers, expert instructional methods have found very little application in medical schools.

  11. The Methodology of Expert Audit in the Cloud Computing System

    Directory of Open Access Journals (Sweden)

    Irina Vladimirovna Mashkina

    2013-12-01

    Full Text Available The problem of information security audit in the cloud computing system is discussed. The methodology of the expert audit is described, it allows to estimate not only the value of information security risk level, but also operative value of information security risk level. The fuzzy cognitive maps and artificial neural network are used for solution of this problem.

  12. Fuzzy logic control for camera tracking system

    Science.gov (United States)

    Lea, Robert N.; Fritz, R. H.; Giarratano, J.; Jani, Yashvant

    1992-01-01

    A concept utilizing fuzzy theory has been developed for a camera tracking system to provide support for proximity operations and traffic management around the Space Station Freedom. Fuzzy sets and fuzzy logic based reasoning are used in a control system which utilizes images from a camera and generates required pan and tilt commands to track and maintain a moving target in the camera's field of view. This control system can be implemented on a fuzzy chip to provide an intelligent sensor for autonomous operations. Capabilities of the control system can be expanded to include approach, handover to other sensors, caution and warning messages.

  13. Fuzzy logic control and optimization system

    Science.gov (United States)

    Lou, Xinsheng [West Hartford, CT

    2012-04-17

    A control system (300) for optimizing a power plant includes a chemical loop having an input for receiving an input signal (369) and an output for outputting an output signal (367), and a hierarchical fuzzy control system (400) operably connected to the chemical loop. The hierarchical fuzzy control system (400) includes a plurality of fuzzy controllers (330). The hierarchical fuzzy control system (400) receives the output signal (367), optimizes the input signal (369) based on the received output signal (367), and outputs an optimized input signal (369) to the input of the chemical loop to control a process of the chemical loop in an optimized manner.

  14. A GA-fuzzy automatic generation controller for interconnected power system

    CSIR Research Space (South Africa)

    Boesack, CD

    2011-10-01

    Full Text Available This paper presents a GA-Fuzzy Automatic Generation Controller for large interconnected power systems. The design of Fuzzy Logic Controllers by means of expert knowledge have typically been the traditional design norm, however, this may not yield...

  15. Intelligent micro blood typing system using a fuzzy algorithm

    International Nuclear Information System (INIS)

    Kang, Taeyun; Cho, Dong-Woo; Lee, Seung-Jae; Kim, Yonggoo; Lee, Gyoo-Whung

    2010-01-01

    ABO typing is the first analysis performed on blood when it is tested for transfusion purposes. The automated machines used in hospitals for this purpose are typically very large and the process is complicated. In this paper, we present a new micro blood typing system that is an improved version of our previous system (Kang et al 2004 Trans. ASME, J. Manuf. Sci. Eng. 126 766, Lee et al 2005 Sensors Mater. 17 113). This system, fabricated using microstereolithography, has a passive valve for controlling the flow of blood and antibodies. The intelligent micro blood typing system has two parts: a single-line micro blood typing device and a fuzzy expert system for grading the strength of agglutination. The passive valve in the single-line micro blood typing device makes the blood stop at the entrance of a micro mixer and lets it flow again after the blood encounters antibodies. Blood and antibodies are mixed in the micro mixer and agglutination occurs in the chamber. The fuzzy expert system then determines the degree of agglutination from images of the agglutinated blood. Blood typing experiments using this device were successful, and the fuzzy expert system produces a grading decision comparable to that produced by an expert conducting a manual analysis

  16. Fuzzy systems for process identification and control

    International Nuclear Information System (INIS)

    Gorrini, V.; Bersini, H.

    1994-01-01

    Various issues related to the automatic construction and on-line adaptation of fuzzy controllers are addressed. A Direct Adaptive Fuzzy Control (this is an adaptive control methodology requiring a minimal knowledge of the processes to be coupled with) derived in a way reminiscent of neurocontrol methods, is presented. A classical fuzzy controller and a fuzzy realization of a PID controller is discussed. These systems implement a highly non-linear control law, and provide to be quite robust, even in the case of noisy inputs. In order to identify dynamic processes of order superior to one, we introduce a more complex architecture, called Recurrent Fuzzy System, that use some fuzzy internal variables to perform an inferential chaining.I

  17. Expert Systems for the Analytical Laboratory.

    Science.gov (United States)

    de Monchy, Allan R.; And Others

    1988-01-01

    Discusses two computer problem solving programs: rule-based expert systems and decision analysis expert systems. Explores the application of expert systems to automated chemical analyses. Presents six factors to consider before using expert systems. (MVL)

  18. Expert Systems as Tools for Technical Communicators.

    Science.gov (United States)

    Grider, Daryl A.

    1994-01-01

    Discusses expertise, what an expert system is, what an expert system shell is, what expert systems can and cannot do, knowledge engineering and technical communicators, and planning and managing expert system projects. (SR)

  19. Stability Analysis of Interconnected Fuzzy Systems Using the Fuzzy Lyapunov Method

    Directory of Open Access Journals (Sweden)

    Ken Yeh

    2010-01-01

    Full Text Available The fuzzy Lyapunov method is investigated for use with a class of interconnected fuzzy systems. The interconnected fuzzy systems consist of J interconnected fuzzy subsystems, and the stability analysis is based on Lyapunov functions. Based on traditional Lyapunov stability theory, we further propose a fuzzy Lyapunov method for the stability analysis of interconnected fuzzy systems. The fuzzy Lyapunov function is defined in fuzzy blending quadratic Lyapunov functions. Some stability conditions are derived through the use of fuzzy Lyapunov functions to ensure that the interconnected fuzzy systems are asymptotically stable. Common solutions can be obtained by solving a set of linear matrix inequalities (LMIs that are numerically feasible. Finally, simulations are performed in order to verify the effectiveness of the proposed stability conditions in this paper.

  20. Expert systems in clinical microbiology.

    Science.gov (United States)

    Winstanley, Trevor; Courvalin, Patrice

    2011-07-01

    This review aims to discuss expert systems in general and how they may be used in medicine as a whole and clinical microbiology in particular (with the aid of interpretive reading). It considers rule-based systems, pattern-based systems, and data mining and introduces neural nets. A variety of noncommercial systems is described, and the central role played by the EUCAST is stressed. The need for expert rules in the environment of reset EUCAST breakpoints is also questioned. Commercial automated systems with on-board expert systems are considered, with emphasis being placed on the "big three": Vitek 2, BD Phoenix, and MicroScan. By necessity and in places, the review becomes a general review of automated system performances for the detection of specific resistance mechanisms rather than focusing solely on expert systems. Published performance evaluations of each system are drawn together and commented on critically.

  1. Combined heuristic with fuzzy system to transmission system expansion planning

    Energy Technology Data Exchange (ETDEWEB)

    Silva Sousa, Aldir; Asada, Eduardo N. [University of Sao Paulo, Sao Carlos School of Engineering, Department of Electrical Engineering Av. Trabalhador Sao-carlense, 400, 13566-590 Sao Carlos, SP (Brazil)

    2011-01-15

    A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (author)

  2. Expert Systems: An Introduction -46 ...

    Indian Academy of Sciences (India)

    Research Scientist in the. Knowledge Based. Computer Systems Group at NeST. He is one of the ... Expert systems encode human expertise in limited domains ... answers questions the user has and provides an explanation of its reasoning.

  3. Cornell Mixing Zone Expert System

    Science.gov (United States)

    This page provides an overview Cornell Mixing Zone Expert System water quality modeling and decision support system designed for environmental impact assessment of mixing zones resulting from wastewater discharge from point sources

  4. Intelligent programs-expert systems

    Energy Technology Data Exchange (ETDEWEB)

    Gledhill, V X

    1982-01-01

    In recent years, computer scientists have developed what are called expert systems. These programs have three fundamental components: a knowledge base, which changes with experience; an inference engine which enables the program to make decisions; and an interface that allows the program to communicate with the person using the system. Expert systems have been developed successfully in areas such as medical diagnosis, geology, and computer maintenance. This paper describes the evolution and basic principles of expert systems and give some examples of their use.

  5. Preserving experience through expert systems

    International Nuclear Information System (INIS)

    Jelinek, J.B.; Weidman, S.H.

    1989-01-01

    Expert systems technology, one of the branches in the field of computerized artificial intelligence, has existed for >30 yr but only recently has been made available on commercially standard hardware and software platforms. An expert system can be defined as any method of encoding knowledge by representing that knowledge as a collection of facts or objects. Decisions are made by the expert program by obtaining data about the problem or situation and correlating encoded facts (knowledge) to the data until a conclusion can be reached. Such conclusions can be relayed to the end user as expert advice. Realizing the potential of this technology, General Electric (GE) Nuclear Energy (GENE) has initiated a development program in expert systems applications; this technology offers the potential for packaging, distributing, and preserving nuclear experience in a software form. The paper discusses application fields, effective applications, and knowledge acquisition and knowledge verification

  6. Expert system in PNC, 6

    International Nuclear Information System (INIS)

    Tsubota, Koji

    1990-01-01

    The application of Artificial Intelligence (AI) as a tool for mineral exploration started only a decade ago. The systems that have been reported are in the most cases the expert systems that can simulate the decision of the experts or help numerical calculation for more reasonable and/or fast decision making. PNC started the development of the expert system for uranium exploration in 1983. Since then, KOGITO, a expert system to find the favorability of the target area, has been developed. Two years ago, the second generation development, Intelligent Research Environment and Support System, IRESS was initiated aiming at the establishment of a total support system for a project evaluation. We will review our effort for development of our system and introduce the application of the Data directed Numerical method as a new tool to Ahnemland area in Australia. (author)

  7. Uzawa method for fuzzy linear system

    OpenAIRE

    Ke Wang

    2013-01-01

    An Uzawa method is presented for solving fuzzy linear systems whose coefficient matrix is crisp and the right-hand side column is arbitrary fuzzy number vector. The explicit iterative scheme is given. The convergence is analyzed with convergence theorems and the optimal parameter is obtained. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.

  8. Fuzzy stability and synchronization of hyperchaos systems

    International Nuclear Information System (INIS)

    Wang Junwei; Xiong Xiaohua; Zhao Meichun; Zhang Yanbin

    2008-01-01

    This paper studies stability and synchronization of hyperchaos systems via a fuzzy-model-based control design methodology. First, we utilize a Takagi-Sugeno fuzzy model to represent a hyperchaos system. Second, we design fuzzy-model-based controllers for stability and synchronization of the system, based on so-called 'parallel distributed compensation (PDC)'. Third, we reduce a question of stabilizing and synchronizing hyperchaos systems to linear matrix inequalities (LMI) so that convex programming techniques can solve these LMIs efficiently. Finally, the generalized Lorenz hyperchaos system is employed to illustrate the effectiveness of our designing controller

  9. GIS Supported Landslide Susceptibility Modeling at Regional Scale: An Expert-Based Fuzzy Weighting Method

    Directory of Open Access Journals (Sweden)

    Christos Chalkias

    2014-04-01

    Full Text Available The main aim of this paper is landslide susceptibility assessment using fuzzy expert-based modeling. Factors that influence landslide occurrence, such as elevation, slope, aspect, lithology, land cover, precipitation and seismicity were considered. Expert-based fuzzy weighting (EFW approach was used to combine these factors for landslide susceptibility mapping (Peloponnese, Greece. This method produced a landslide susceptibility map of the investigated area. The landslides under investigation have more or less same characteristics: lateral based and downslope shallow movement of soils or rocks. The validation of the model reveals, that predicted susceptibility levels are found to be in good agreement with the past landslide occurrences. Hence, the obtained landslide susceptibility map could be acceptable, for landslide hazard prevention and mitigation at regional scale.

  10. Expert systems in process control systems

    International Nuclear Information System (INIS)

    Wittig, T.

    1987-01-01

    To illustrate where the fundamental difference between expert systems in classical diagnosis and in industrial control lie, the work of process control instrumentation is used as an example for the job of expert systems. Starting from the general process of problem-solving, two classes of expert systems can be defined accordingly. (orig.) [de

  11. Expert Systems for auditing management information systems

    Directory of Open Access Journals (Sweden)

    Gheroghe Popescu

    2007-05-01

    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.

  12. Introducing Managers to Expert Systems.

    Science.gov (United States)

    Finlay, Paul N.; And Others

    1991-01-01

    Describes a short course to expose managers to expert systems, consisting of (1) introductory lecture; (2) supervised computer tutorial; (3) lecture and discussion about knowledge structuring and modeling; and (4) small group work on a case study using computers. (SK)

  13. Artificial Intelligence and Expert Systems.

    Science.gov (United States)

    Wilson, Harold O.; Burford, Anna Marie

    1990-01-01

    Delineates artificial intelligence/expert systems (AI/ES) concepts; provides an exposition of some business application areas; relates progress; and creates an awareness of the benefits, limitations, and reservations of AI/ES. (Author)

  14. Nickel Hydrogen Battery Expert System

    Science.gov (United States)

    Johnson, Yvette B.; Mccall, Kurt E.

    1992-01-01

    The Nickel Cadmium Battery Expert System-2, or 'NICBES-2', which was used by the NASA HST six-battery testbed, was subsequently converted into the Nickel Hydrogen Battery Expert System, or 'NICHES'. Accounts are presently given of this conversion process and future uses being contemplated for NICHES. NICHES will calculate orbital summary data at the end of each orbit, and store these files for trend analyses and rules-generation.

  15. System reliability analysis with natural language and expert's subjectivity

    International Nuclear Information System (INIS)

    Onisawa, T.

    1996-01-01

    This paper introduces natural language expressions and expert's subjectivity to system reliability analysis. To this end, this paper defines a subjective measure of reliability and presents the method of the system reliability analysis using the measure. The subjective measure of reliability corresponds to natural language expressions of reliability estimation, which is represented by a fuzzy set defined on [0,1]. The presented method deals with the dependence among subsystems and employs parametrized operations of subjective measures of reliability which can reflect expert 's subjectivity towards the analyzed system. The analysis results are also expressed by linguistic terms. Finally this paper gives an example of the system reliability analysis by the presented method

  16. New approach to solve symmetric fully fuzzy linear systems

    Indian Academy of Sciences (India)

    concepts of fuzzy set theory and then define a fully fuzzy linear system of equations. .... To represent the above problem as fully fuzzy linear system, we represent x .... Fully fuzzy linear systems can be solved by Linear programming approach, ...

  17. The application of expert system : a review of research and applications

    NARCIS (Netherlands)

    Tan, C.F.; Wahidin, L.S.; Khalil, S.N.; Tamaldin, N.; Hu, J.; Rauterberg, G.W.M.

    2016-01-01

    The development of Artificial Intelligent (AI) technology system can be a wide scope; for an instant, there are rule-based expert system, frame-based expert system, fuzzy logic, neural network, genetic algorithm, etc. The remarkable achievement applications of AI has been reported in different

  18. An expert system for pressurized water reactor load maneuvers

    International Nuclear Information System (INIS)

    Chaung Lin; Jungping Chen; Yihjiunn Lin; Lianshin Lin

    1993-01-01

    Restartup after reactor shutdown and load-follow operations are the important tasks in operating pressurized water reactors. Generally, the most efficient method is to apply constant axial offset control (CAOC) strategy during load maneuvers. An expert system using CAOC strategy, fuzzy reasoning, a two-node core model, and operational constraints has been developed. The computation time is so short that this system, which leads to an approximate closed-loop control, could be useful for on-site calculation

  19. Design of fuzzy systems using neurofuzzy networks.

    Science.gov (United States)

    Figueiredo, M; Gomide, F

    1999-01-01

    This paper introduces a systematic approach for fuzzy system design based on a class of neural fuzzy networks built upon a general neuron model. The network structure is such that it encodes the knowledge learned in the form of if-then fuzzy rules and processes data following fuzzy reasoning principles. The technique provides a mechanism to obtain rules covering the whole input/output space as well as the membership functions (including their shapes) for each input variable. Such characteristics are of utmost importance in fuzzy systems design and application. In addition, after learning, it is very simple to extract fuzzy rules in the linguistic form. The network has universal approximation capability, a property very useful in, e.g., modeling and control applications. Here we focus on function approximation problems as a vehicle to illustrate its usefulness and to evaluate its performance. Comparisons with alternative approaches are also included. Both, nonnoisy and noisy data have been studied and considered in the computational experiments. The neural fuzzy network developed here and, consequently, the underlying approach, has shown to provide good results from the accuracy, complexity, and system design points of view.

  20. PENERAPAN FUZZY INFERENCE SYSTEM TAKAGI-SUGENO-KANG PADA SISTEM PAKAR DIAGNOSA PENYAKIT GIGI

    Directory of Open Access Journals (Sweden)

    Lutfi Salisa Setiawati

    2016-04-01

    Full Text Available Generally, expert system only show types of disease after user choose symptoms. In the study is done the addition of disease severity level. The method applied in the calculation of the severity is a method of Fuzzy Inference System Takagi-Sugeno-Kang (Method of Sugeno. This study attempts to know whether method Fuzzy Inference System Takagi-Sugeno-Kang can work for expert system in giving the diagnosis diseases of the teeth. The result of this research or severity for diseases of pulpitis reversible 38,53%, pulpitis irreversible 59,64%, periodontitis 69,62%, acute periodontitis 51,43%, gingivitis 45.5%, acute pericoronitis 53,93%, sub acute pericoronitis 52,14%, chronic pericoronitis 46,05%, caries dentist an early stage 37,61%, caries dentist toward an advanced stage 43,89%, caries dentist an advanced stage 51,76%, gangrene pulpa 42,5%, polyps pulpa 56,43%, and periostitis 58,55%. A conclusion that was obtained from the study that is a method of Fuzzy Inference System Takagi-Sugeno-Kang could be applied to expert system of the teeth. Key Word: Teeth , Expert System , Expert System Teeth , Fuzzy Logic , Fuzzy Inference System , Takagi-Sugeno-Kang , Fuzzy Sugeno Pada umumnya, istem pakar hanya menampilkan jenis penyakit setelah user memilih gejala-gejala. Pada penelitian ini dilakukan penambahan tingkat keparahan penyakit. Metode yang diterapkan dalam perhitungan tingkat keparahan ini yaitu Metode Fuzzy Inference System Takagi-Sugeno-Kang (Metode Sugeno. Penelitian ini bertujuan untuk mengetahui apakah metode Fuzzy Inference System Takagi-Sugeno-Kang dapat diterapkan pada sistem pakar dalam memberikan diagnosa penyakit gigi. Hasil dari penelitian ini didapatkan tingkat keparahan untuk penyakit Pulpitis Reversibel 38,53%, Pulpitis Irreversibel 59,64%, Periodontitis 69,62%, Periodontitis Akut 51,43%, Gingivitis 45,5%, Perikoronitis Akut 53,93%, Perikoronitis Sub Akut 52,14%, Perikoronitis Kronis 46,05%, Karies Denties Tahap Awal 37,61%, Karies

  1. Expert systems as decision tools

    International Nuclear Information System (INIS)

    Scott, C.K.

    1989-01-01

    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

  2. Aircraft Maintenance Expert Systems.

    Science.gov (United States)

    1983-11-01

    PARA 2 -104)) 44: (( JETCAL ANALYSIS SHOWS SYSTEM READS CORRECT) (REPLACE FAULTY PARTS)) 45: ((OVERTEMP EXCEEDED SERVICE LIMITS) 46: I(ENGINE CONTROL...CIRCUITS WITHIN LIMITS ON JETCAL ) (REPLACE FAULTY PARTS)) 47: (ADJUST EST AT AMPLIFIER AND CHECK TENP)) (SEND ENGINE TO HIGHER LEVEL MAINTENANCE)) 48: 2

  3. Expert systems and nuclear safety

    International Nuclear Information System (INIS)

    Beltracchi, L.

    1990-01-01

    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

  4. Fuzzy logic for structural system control

    Directory of Open Access Journals (Sweden)

    Herbert Martins Gomes

    Full Text Available This paper provides some information and numerical tests that aims to investigate the use of a Fuzzy Controller applied to control systems. Some advantages are reported regarding the use of this controller, such as the characteristic ease of implementation due to its semantic feature in the statement of the control rules. On the other hand, it is also hypothesized that these systems have a lower performance loss when the system to be controlled is nonlinear or has time varying parameters. Numerical tests are performed using modal LQR optimal control and Fuzzy control of non-collocated systems with full state feedback in a two-dimensional structure. The paper proposes a way of designing a controller that may be a supervisory Fuzzy controller for a traditional controller or even a fuzzy controller independent from the traditional control, consisting on individual mode controllers. Some comments are drawn regarding the performance of these proposals in a number of arrangements.

  5. Classification of jet fuels by fuzzy rule-building expert systems applied to three-way data by fast gas chromatography--fast scanning quadrupole ion trap mass spectrometry.

    Science.gov (United States)

    Sun, Xiaobo; Zimmermann, Carolyn M; Jackson, Glen P; Bunker, Christopher E; Harrington, Peter B

    2011-01-30

    A fast method that can be used to classify unknown jet fuel types or detect possible property changes in jet fuel physical properties is of paramount interest to national defense and the airline industries. While fast gas chromatography (GC) has been used with conventional mass spectrometry (MS) to study jet fuels, fast GC was combined with fast scanning MS and used to classify jet fuels into lot numbers or origin for the first time by using fuzzy rule-building expert system (FuRES) classifiers. In the process of building classifiers, the data were pretreated with and without wavelet transformation and evaluated with respect to performance. Principal component transformation was used to compress the two-way data images prior to classification. Jet fuel samples were successfully classified with 99.8 ± 0.5% accuracy for both with and without wavelet compression. Ten bootstrapped Latin partitions were used to validate the generalized prediction accuracy. Optimized partial least squares (o-PLS) regression results were used as positively biased references for comparing the FuRES prediction results. The prediction results for the jet fuel samples obtained with these two methods were compared statistically. The projected difference resolution (PDR) method was also used to evaluate the fast GC and fast MS data. Two batches of aliquots of ten new samples were prepared and run independently 4 days apart to evaluate the robustness of the method. The only change in classification parameters was the use of polynomial retention time alignment to correct for drift that occurred during the 4-day span of the two collections. FuRES achieved perfect classifications for four models of uncompressed three-way data. This fast GC/fast MS method furnishes characteristics of high speed, accuracy, and robustness. This mode of measurement may be useful as a monitoring tool to track changes in the chemical composition of fuels that may also lead to property changes. Copyright © 2010

  6. Expert system application education project

    Science.gov (United States)

    Gonzelez, Avelino J.; Ragusa, James M.

    1988-01-01

    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.

  7. A statistical view of uncertainty in expert systems

    International Nuclear Information System (INIS)

    Spiegelhalter, D.J.

    1986-01-01

    The constructors of expert systems interpret ''uncertainty'' in a wide sense and have suggested a variety of qualitative and quantitative techniques for handling the concept, such as the theory of ''endorsements,'' fuzzy reasoning, and belief functions. After a brief selective review of procedures that do not adhere to the laws of probability, it is argued that a subjectivist Bayesian view of uncertainty, if flexibly applied, can provide many of the features demanded by expert systems. This claim is illustrated with a number of examples of probabilistic reasoning, and a connection drawn with statistical work on the graphical representation of multivariate distributions. Possible areas of future research are outlined

  8. Expert systems in clinical practice

    International Nuclear Information System (INIS)

    Renaud-Salis, J.L.

    1987-01-01

    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 [fr

  9. Expert systems: an alternative paradigm

    Energy Technology Data Exchange (ETDEWEB)

    Coombs, M.; Alty, J.

    1984-01-01

    There has recently been a significant effort by the AI community to interest industry in the potential of expert systems. However, this has resulted in far fewer substantial applications projects than might be expected. This article argues that this is because human experts are rarely required to perform the role that computer-based experts are programmed to adopt. Instead of being called in to answer well-defined problems, they are more often asked to assist other experts to extend and refine their understanding of a problem area at the junction of their two domains of knowledge. This more properly involves educational rather than problem-solving skills. An alternative approach to expert system design is proposed based upon guided discovery learning. The user is provided with a supportive environment for a particular class of problem, the system predominantly acting as an adviser rather than directing the interaction. The environment includes a database of domain knowledge, a set of procedures for its application to a concrete problem, and an intelligent machine-based adviser to judge the user's effectiveness and advise on strategy. The procedures focus upon the use of user generated explanations both to promote the application of domain knowledge and to expose understanding difficulties. Simple database PROLOG is being used as the subject material for the prototype system which is known as MINDPAD. 30 references.

  10. Counselor Expert System | Debretsion | Zede Journal

    African Journals Online (AJOL)

    An expert system plays an important role on alleviating primarily shortage of experts in a specific area of interest. With the help of an expert system, personnel with little expertise can solve problems that require expert knowledge. In this paper all major aspects of an expert system development have been presented.

  11. QUEST: Quality of Expert Systems

    NARCIS (Netherlands)

    Perre, M.

    1991-01-01

    TNO Physics and Electronics laboratory, in collaboration with the University of Limburg and the Research Institute for Knowledge Systems, worked on a technology project named 'QUEST: Quality of Expert Systems' [FEL90]. QUEST was carried out under commision of the Dutch Ministry of Defence. A strong

  12. On-line tuning of a fuzzy-logic power system stabilizer

    International Nuclear Information System (INIS)

    Hossein-Zadeh, N.; Kalam, A.

    2002-01-01

    A scheme for on-line tuning of a fuzzy-logic power system stabilizer is presented. firstly, a fuzzy-logic power system stabilizer is developed using speed deviation and accelerating power as the controller input variables. The inference mechanism of fuzzy-logic controller is represented by a decision table, constructed of linguistic IF-THEN rules. The Linguistic rules are available from experts and the design procedure is based on these rules. It assumed that an exact model of the plant is not available and it is difficult to extract the exact parameters of the power plant. Thus, the design procedure can not be based on an exact model. This is an advantage of fuzzy logic that makes the design of a controller possible without knowing the exact model of the plant. Secondly, two scaling parameters are introduced to tune the fuzzy-logic power system stabilizer. These scaling parameters are the outputs of another fuzzy-logic system, which gets the operating conditions of power system as inputs. These mechanism of tuning the fuzzy-logic power system stabilizer makes the fuzzy-logic power system stabilizer adaptive to changes in the operating conditions. Therefore, the degradation of the system response, under a wide range of operating conditions, is less compared to the system response with a fixed-parameter fuzzy-logic power system stabilizer and a conventional (linear) power system stabilizer. The tuned stabilizer has been tested by performing nonlinear simulations using a synchronous machine-infinite bus model. The responses are compared with a fixed parameters fuzzy-logic power system stabilizer and a conventional (linear) power system stabilizer. It is shown that the tuned fuzzy-logic power system stabilizer is superior to both of them

  13. Designing PID-Fuzzy Controller for Pendubot System

    Directory of Open Access Journals (Sweden)

    Ho Trong Nguyen

    2017-12-01

    Full Text Available In the paper, authors analize dynamic equation of a pendubot system. Familiar kinds of controller – PID, fuzzy controllers – are concerned. Then, a structure of PID-FUZZY is presented. The comparison of three kinds of controllers – PID, fuzzy and PID-FUZZY shows the better response of system under PID-FUZZY controller. Then, the experiments on the real model also prove the better stabilization of the hybrid controller which is combined between linear and intelligent controller.

  14. On Modeling the Behavior of Comparators for Complex Fuzzy Objects in a Fuzzy Object-Relational Database Management System

    Directory of Open Access Journals (Sweden)

    JuanM. Medina

    2012-08-01

    Full Text Available This paper proposes a parameterized definition for fuzzy comparators on complex fuzzy datatypes like fuzzy collections with conjunctive semantics and fuzzy objects. This definition and its implementation on a Fuzzy Object-Relational Database Management System (FORDBMS provides the designer with a powerful tool to adapt the behavior of these operators to the semantics of the considered application.

  15. Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

    Directory of Open Access Journals (Sweden)

    Nazario Garcia

    2018-01-01

    Full Text Available This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM and a fuzzy inference system (FIS. By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method’s superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process.

  16. Expert systems for superalloy studies

    Science.gov (United States)

    Workman, Gary L.; Kaukler, William F.

    1990-01-01

    There are many areas in science and engineering which require knowledge of an extremely complex foundation of experimental results in order to design methodologies for developing new materials or products. Superalloys are an area which fit well into this discussion in the sense that they are complex combinations of elements which exhibit certain characteristics. Obviously the use of superalloys in high performance, high temperature systems such as the Space Shuttle Main Engine is of interest to NASA. The superalloy manufacturing process is complex and the implementation of an expert system within the design process requires some thought as to how and where it should be implemented. A major motivation is to develop a methodology to assist metallurgists in the design of superalloy materials using current expert systems technology. Hydrogen embrittlement is disasterous to rocket engines and the heuristics can be very complex. Attacking this problem as one module in the overall design process represents a significant step forward. In order to describe the objectives of the first phase implementation, the expert system was designated Hydrogen Environment Embrittlement Expert System (HEEES).

  17. Expert Systems in Government Administration

    OpenAIRE

    Weintraub, Joseph

    1989-01-01

    Artificial Intelligence is solving more and more real world problems, but penetration into the complexities of government administration has been minimal. The author suggests that combining expert system technology with conventional procedural computer systems can lead to substantial efficiencies. Business rules can be removed from business-oriented computer systems and stored in a separate but integrated knowledge base, where maintenance will be centralized. Fourteen specific practical appli...

  18. A study of fuzzy control in nuclear scale system

    International Nuclear Information System (INIS)

    Wang Yu; Zhang Yongming; Wu Ruisheng; Du Xianbin; Liu Shixing

    2001-01-01

    The new development of the nuclear scale system which uses fuzzy control strategy is presented. Good results have been obtained in using fuzzy control to solve the problems, such as un-linearities, instabilities, time delays, which are difficultly described by formula, etc. The fuzzy variance, membership function and fuzzy rules are given, and the noise disturbances of fuzzy control and PID control are also given

  19. Quantitative modeling of gene networks of biological systems using fuzzy Petri nets and fuzzy sets

    Directory of Open Access Journals (Sweden)

    Raed I. Hamed

    2018-01-01

    Full Text Available Quantitative demonstrating of organic frameworks has turned into an essential computational methodology in the configuration of novel and investigation of existing natural frameworks. Be that as it may, active information that portrays the framework's elements should be known keeping in mind the end goal to get pertinent results with the routine displaying strategies. This information is frequently robust or even difficult to get. Here, we exhibit a model of quantitative fuzzy rational demonstrating approach that can adapt to obscure motor information and hence deliver applicable results despite the fact that dynamic information is fragmented or just dubiously characterized. Besides, the methodology can be utilized as a part of the blend with the current cutting edge quantitative demonstrating strategies just in specific parts of the framework, i.e., where the data are absent. The contextual analysis of the methodology suggested in this paper is performed on the model of nine-quality genes. We propose a kind of FPN model in light of fuzzy sets to manage the quantitative modeling of biological systems. The tests of our model appear that the model is practical and entirely powerful for information impersonation and thinking of fuzzy expert frameworks.

  20. PSG-EXPERT. An expert system for the diagnosis of sleep disorders.

    Science.gov (United States)

    Fred, A; Filipe, J; Partinen, M; Paiva, T

    2000-01-01

    This paper describes PSG-EXPERT, an expert system in the domain of sleep disorders exploring polysomnographic data. The developed software tool is addressed from two points of view: (1)--as an integrated environment for the development of diagnosis-oriented expert systems; (2)--as an auxiliary diagnosis tool in the particular domain of sleep disorders. Developed over a Windows platform, this software tool extends one of the most popular shells--CLIPS (C Language Integrated Production System) with the following features: backward chaining engine; graph-based explanation facilities; knowledge editor including a fuzzy fact editor and a rules editor, with facts-rules integrity checking; belief revision mechanism; built-in case generator and validation module. It therefore provides graphical support for knowledge acquisition, edition, explanation and validation. From an application domain point of view, PSG-Expert is an auxiliary diagnosis system for sleep disorders based on polysomnographic data, that aims at assisting the medical expert in his diagnosis task by providing automatic analysis of polysomnographic data, summarising the results of this analysis in terms of a report of major findings and possible diagnosis consistent with the polysomnographic data. Sleep disorders classification follows the International Classification of Sleep Disorders. Major features of the system include: browsing on patients data records; structured navigation on Sleep Disorders descriptions according to ASDA definitions; internet links to related pages; diagnosis consistent with polysomnographic data; graphical user-interface including graph-based explanatory facilities; uncertainty modelling and belief revision; production of reports; connection to remote databases.

  1. Fuzzy Logic Based Autonomous Traffic Control System

    Directory of Open Access Journals (Sweden)

    Muhammad ABBAS

    2012-01-01

    Full Text Available The aim of this paper is to design and implement fuzzy logic based traffic light Control system to solve the traffic congestion issues. In this system four input parameters: Arrival, Queue, Pedestrian and Emergency Vehicle and two output parameters: Extension in Green and Pedestrian Signals are used. Using Fuzzy Rule Base, the system extends or terminates the Green Signal according to the Traffic situation at the junction. On the presence of emergency vehicle, the system decides which signal(s should be red and how much an extension should be given to Green Signal for Emergency Vehicle. The system also monitors the density of people and makes decisions accordingly. In order to verify the proposed design algorithm MATLAB simulation is adopted and results obtained show concurrency to the calculated values according to the Mamdani Model of the Fuzzy Control System.

  2. Online-Expert: An Expert System for Online Database Selection.

    Science.gov (United States)

    Zahir, Sajjad; Chang, Chew Lik

    1992-01-01

    Describes the design and development of a prototype expert system called ONLINE-EXPERT that helps users select online databases and vendors that meet users' needs. Search strategies are discussed; knowledge acquisition and knowledge bases are described; and the Analytic Hierarchy Process (AHP), a decision analysis technique that ranks databases,…

  3. Expert system based radionuclide identification

    International Nuclear Information System (INIS)

    Aarnio, P.A.; Ala-Heikkil, J.J.; Hakulinen, T.T.; Nikkinen, M.T.

    1998-01-01

    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)

  4. Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    P. Akhavan

    2014-10-01

    Full Text Available Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL created by Leishmania is a special parasitic disease which can be passed on to human through phlebotomus of vector-born. Studies show that economic situation, cultural issues, as well as environmental and ecological conditions can affect the prevalence of this disease. In this study, Data Mining is utilized in order to predict CL prevalence rate and obtain a risk map. This case is based on effective environmental parameters on CL and a Neuro-Fuzzy system was also used. Learning capacity of Neuro-Fuzzy systems in neural network on one hand and reasoning power of fuzzy systems on the other, make it very efficient to use. In this research, in order to predict CL prevalence rate, an adaptive Neuro-fuzzy inference system with fuzzy inference structure of fuzzy C Means clustering was applied to determine the initial membership functions. Regarding to high incidence of CL in Ilam province, counties of Ilam, Mehran, and Dehloran have been examined and evaluated. The CL prevalence rate was predicted in 2012 by providing effective environmental map and topography properties including temperature, moisture, annual, rainfall, vegetation and elevation. Results indicate that the model precision with fuzzy C Means clustering structure rises acceptable RMSE values of both training and checking data and support our analyses. Using the proposed data mining technology, the pattern of disease spatial distribution and vulnerable areas become identifiable and the map can be used by experts and decision makers of public health as a useful tool in management and optimal decision-making.

  5. Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System

    Science.gov (United States)

    Akhavan, P.; Karimi, M.; Pahlavani, P.

    2014-10-01

    Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL) created by Leishmania is a special parasitic disease which can be passed on to human through phlebotomus of vector-born. Studies show that economic situation, cultural issues, as well as environmental and ecological conditions can affect the prevalence of this disease. In this study, Data Mining is utilized in order to predict CL prevalence rate and obtain a risk map. This case is based on effective environmental parameters on CL and a Neuro-Fuzzy system was also used. Learning capacity of Neuro-Fuzzy systems in neural network on one hand and reasoning power of fuzzy systems on the other, make it very efficient to use. In this research, in order to predict CL prevalence rate, an adaptive Neuro-fuzzy inference system with fuzzy inference structure of fuzzy C Means clustering was applied to determine the initial membership functions. Regarding to high incidence of CL in Ilam province, counties of Ilam, Mehran, and Dehloran have been examined and evaluated. The CL prevalence rate was predicted in 2012 by providing effective environmental map and topography properties including temperature, moisture, annual, rainfall, vegetation and elevation. Results indicate that the model precision with fuzzy C Means clustering structure rises acceptable RMSE values of both training and checking data and support our analyses. Using the proposed data mining technology, the pattern of disease spatial distribution and vulnerable areas become identifiable and the map can be used by experts and decision makers of public health as a useful tool in management and optimal decision-making.

  6. Expert System for ASIC Imaging

    Science.gov (United States)

    Gupta, Shri N.; Arshak, Khalil I.; McDonnell, Pearse; Boyce, Conor; Duggan, Andrew

    1989-07-01

    With the developments in the techniques of artificial intelligence over the last few years, development of advisory, scheduling and similar class of problems has become very convenient using tools such as PROLOG. In this paper an expert system has been described which helps lithographers and process engineers in several ways. The methodology used is to model each work station according to its input, output and control parameters, combine these work stations in a logical sequence based on past experience and work out process schedule for a job. In addition, all the requirements vis-a-vis a particular job parameters are converted into decision rules. One example is the exposure time, develop time for a wafer with different feature sizes would be different. This expert system has been written in Turbo Prolog. By building up a large number of rules, one can tune the program to any facility and use it for as diverse applications as advisory help, trouble shooting etc. Leitner (1) has described an advisory expert system that is being used at National Semiconductor. This system is quite different from the one being reported in the present paper. The approach is quite different for one. There is stress on job flow and process for another.

  7. Reliability modelling of repairable systems using Petri nets and fuzzy Lambda-Tau methodology

    International Nuclear Information System (INIS)

    Knezevic, J.; Odoom, E.R.

    2001-01-01

    A methodology is developed which uses Petri nets instead of the fault tree methodology and solves for reliability indices utilising fuzzy Lambda-Tau method. Fuzzy set theory is used for representing the failure rate and repair time instead of the classical (crisp) set theory because fuzzy numbers allow expert opinions, linguistic variables, operating conditions, uncertainty and imprecision in reliability information to be incorporated into the system model. Petri nets are used because unlike the fault tree methodology, the use of Petri nets allows efficient simultaneous generation of minimal cut and path sets

  8. Solving Fully Fuzzy Linear System of Equations in General Form

    Directory of Open Access Journals (Sweden)

    A. Yousefzadeh

    2012-06-01

    Full Text Available In this work, we propose an approach for computing the positive solution of a fully fuzzy linear system where the coefficient matrix is a fuzzy $nimes n$ matrix. To do this, we use arithmetic operations on fuzzy numbers that introduced by Kaffman in and convert the fully fuzzy linear system into two $nimes n$ and $2nimes 2n$ crisp linear systems. If the solutions of these linear systems don't satisfy in positive fuzzy solution condition, we introduce the constrained least squares problem to obtain optimal fuzzy vector solution by applying the ranking function in given fully fuzzy linear system. Using our proposed method, the fully fuzzy linear system of equations always has a solution. Finally, we illustrate the efficiency of proposed method by solving some numerical examples.

  9. The Expert System For Safety Assesment Of Kartini Reactor Operation And Maintenance

    International Nuclear Information System (INIS)

    Syarip

    2000-01-01

    An expert system for safety assessment of Kartini reactor operation and maintenance based on fuzzy logic method has been made. The expert system is developed from the Fuzzy Expert System Tools (FEST), i.e. by developing the knowledge base and data base files of Kartini research reactor system and operations with an inference engine based on FEST. The knowledge base is represented in the procedural knowledge as heuristic rules or generally known as rule-base in the from of If-then rule. The fuzzy inference process and the conclusion of the rule is done by FEST based on direct chaining method with interactive as well as non-interactive modes. The safety assessment of Kartini reactor based on this method gives more realistic value than the conventional method or binary logic

  10. Expert system application for prioritizing preventive actions for shift work: shift expert.

    Science.gov (United States)

    Esen, Hatice; Hatipoğlu, Tuğçen; Cihan, Ahmet; Fiğlali, Nilgün

    2017-09-19

    Shift patterns, work hours, work arrangements and worker motivations have increasingly become key factors for job performance. The main objective of this article is to design an expert system that identifies the negative effects of shift work and prioritizes mitigation efforts according to their importance in preventing these negative effects. The proposed expert system will be referred to as the shift expert. A thorough literature review is conducted to determine the effects of shift work on workers. Our work indicates that shift work is linked to demographic variables, sleepiness and fatigue, health and well-being, and social and domestic conditions. These parameters constitute the sections of a questionnaire designed to focus on 26 important issues related to shift work. The shift expert is then constructed to provide prevention advice at the individual and organizational levels, and it prioritizes this advice using a fuzzy analytic hierarchy process model, which considers comparison matrices provided by users during the prioritization process. An empirical study of 61 workers working on three rotating shifts is performed. After administering the questionnaires, the collected data are analyzed statistically, and then the shift expert produces individual and organizational recommendations for these workers.

  11. The useability of expert systems

    International Nuclear Information System (INIS)

    Martin, D.J.

    1990-01-01

    This talk presents the case that it is the user of an Expert System (ES), and the user alone, who must decide on the acceptability of such a system. Further, the useability of an ES is principally a function of the user interface: if a system takes a long time to learn, it will not be used effectively. Some ES are implemented on computers with command line interfaces. It is shown (via a live demonstration using a computer) that such systems restrict the AI professiona's ability to deliver a system which is satisfactory from the use's viewpoint: the limitations of the computer system will dictate the user interface, independently of the user requirements. Only a computer system with a graphical interface can supply the versatility and functionality required by the user. Examples of graphical interface facilities are given

  12. Expert systems and computer based industrial systems

    International Nuclear Information System (INIS)

    Dunand, R.

    1989-01-01

    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)

  13. Assessment of the Degree of Consistency of the System of Fuzzy Rules

    Directory of Open Access Journals (Sweden)

    Pospelova Lyudmila Yakovlevna

    2013-12-01

    Full Text Available The article analyses recent achievements and publications and shows that difficulties of explaining the nature of fuzziness and equivocation arise in socio-economic models that use the traditional paradigm of classical rationalism (computational, agent and econometric models. The accumulated collective experience of development of optimal models confirms prospectiveness of application of the fuzzy set approach in modelling the society. The article justifies the necessity of study of the nature of inconsistency in fuzzy knowledge bases both on the generalised ontology level and on pragmatic functional level of the logical inference. The article offers the method of search for logical and conceptual contradictions in the form of a combination of the abduction and modus ponens. It discusses the key issue of the proposed method: what properties should have the membership function of the secondary fuzzy set, which describes in fuzzy inference models such a resulting state of the object of management, which combines empirically incompatible properties with high probability. The degree of membership of the object of management in several incompatible classes with respect to the fuzzy output variable is the degree of fuzziness of the “Intersection of all results of the fuzzy inference of the set, applied at some input of rules, is an empty set” statement. The article describes an algorithm of assessment of the degree of consistency. It provides an example of the step-by-step detection of contradictions in statistical fuzzy knowledge bases at the pragmatic functional level of the logical output. The obtained results of testing in the form of sets of incompatible facts, output chains, sets of non-crossing intervals and computed degrees of inconsistency allow experts timely elimination of inadmissible contradictions and, at the same time, increase of quality of recommendations and assessment of fuzzy expert systems.

  14. Cataloging Expert Systems: Optimism and Frustrated Reality.

    Science.gov (United States)

    Olmstadt, William J.

    2000-01-01

    Discusses artificial intelligence and attempts to catalog expert systems. Topics include the nature of expertise; examples of cataloging expert systems; barriers to implementation; and problems, including total automation, cataloging expertise, priorities, and system design. (LRW)

  15. Expert system validation in prolog

    Science.gov (United States)

    Stock, Todd; Stachowitz, Rolf; Chang, Chin-Liang; Combs, Jacqueline

    1988-01-01

    An overview of the Expert System Validation Assistant (EVA) is being implemented in Prolog at the Lockheed AI Center. Prolog was chosen to facilitate rapid prototyping of the structure and logic checkers and since February 1987, we have implemented code to check for irrelevance, subsumption, duplication, deadends, unreachability, and cycles. The architecture chosen is extremely flexible and expansible, yet concise and complementary with the normal interactive style of Prolog. The foundation of the system is in the connection graph representation. Rules and facts are modeled as nodes in the graph and arcs indicate common patterns between rules. The basic activity of the validation system is then a traversal of the connection graph, searching for various patterns the system recognizes as erroneous. To aid in specifying these patterns, a metalanguage is developed, providing the user with the basic facilities required to reason about the expert system. Using the metalanguage, the user can, for example, give the Prolog inference engine the goal of finding inconsistent conclusions among the rules, and Prolog will search the graph intantiations which can match the definition of inconsistency. Examples of code for some of the checkers are provided and the algorithms explained. Technical highlights include automatic construction of a connection graph, demonstration of the use of metalanguage, the A* algorithm modified to detect all unique cycles, general-purpose stacks in Prolog, and a general-purpose database browser with pattern completion.

  16. Efficient fuzzy logic controller for magnetic levitation systems | Shu ...

    African Journals Online (AJOL)

    In this paper magnetic levitation controller using fuzzy logic is proposed. The proposed Fuzzy logic controller (FLC) is designed, and developed using triangular membership function with 7×7 rules. The system model was implemented in MATLAB/SIMULINK and the system responses to Fuzzy controller with different input ...

  17. Design and implementation of expert decision system in Yellow River Irrigation

    Science.gov (United States)

    Fuping, Wang; Bingbing, Lei; Jie, Pan

    2018-03-01

    How to make full use of water resources in the Yellow River irrigation is a problem needed to be solved urgently. On account of the different irrigation strategies in various growth stages of wheat, this paper proposes a novel irrigation expert decision system basing on fuzzy control technique. According to the control experience, expert knowledge and MATLAB simulation optimization, we obtain the irrigation fuzzy control table stored in the computer memory. The controlling irrigation is accomplished by reading the data from fuzzy control table. The experimental results show that the expert system can be used in the production of wheat to achieve timely and appropriate irrigation, and ensure that wheat growth cycle is always in the best growth environment.

  18. Feed type based expert systems in mineral processing plants

    International Nuclear Information System (INIS)

    Jamsa-Jounela, S.-L.; Laine, S.; Laurila, H.

    1999-01-01

    Artificial Intelligence includes excellent tools for the control and supervision of industrial processes. Several thousand industrial applications have been reported worldwide. Recently, the designers of the AI systems have begun to hybridize the intelligent techniques, expert systems, fuzzy logic and neural networks, to enhance the capability of the AI systems. Expert systems have proved to be ideal candidates especially for the control of mineral processes. As successful case projects, expert system based on on-line classification of the feed type is described in this paper. The essential feature of this expert system is the classification of different feed types and their distinct control strategies at the plant. In addition to the classification, the expert system has a database containing information about how to handle the determined feed type. This self-learning database scans historical process data to suggest the best treatment for the ore type under processing. The system has been tested in two concentrators, the Outokumpu Finnmines Oy, Hitura mine and Outokumpu Chrome Oy, Kemi mine. (author)

  19. Pemodelan Sistem Fuzzy Dengan Menggunakan Matlab

    Directory of Open Access Journals (Sweden)

    Afan Galih Salman

    2010-12-01

    Full Text Available Fuzzy logic is a method in soft computing category, a method that could process uncertain, inaccurate, and less cost implemented data. Some methods in soft computing category besides fuzzy logic are artificial network nerve, probabilistic reasoning, and evolutionary computing. Fuzzy logic has the ability to develop fuzzy system that is intelligent system in uncertain environment. Some stages in fuzzy system formation process is input and output analysis, determining input and output variable, defining each fuzzy set member function, determining rules based on experience or knowledge of an expert in his field, and implementing fuzzy system. Overall, fuzzy logic uses simple mathematical concept, understandable, detectable uncertain and accurate data. Fuzzy system could create and apply expert experiences directly without exercise process and effort to decode the knowledge into a computer until becoming a modeling system that could be relied on decision making.

  20. Database and Expert Systems Applications

    DEFF Research Database (Denmark)

    Viborg Andersen, Kim; Debenham, John; Wagner, Roland

    schemata, query evaluation, semantic processing, information retrieval, temporal and spatial databases, querying XML, organisational aspects of databases, natural language processing, ontologies, Web data extraction, semantic Web, data stream management, data extraction, distributed database systems......This book constitutes the refereed proceedings of the 16th International Conference on Database and Expert Systems Applications, DEXA 2005, held in Copenhagen, Denmark, in August 2005.The 92 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 390...... submissions. The papers are organized in topical sections on workflow automation, database queries, data classification and recommendation systems, information retrieval in multimedia databases, Web applications, implementational aspects of databases, multimedia databases, XML processing, security, XML...

  1. Modified Levenberg-Marquardt Method for RÖSSLER Chaotic System Fuzzy Modeling Training

    Science.gov (United States)

    Wang, Yu-Hui; Wu, Qing-Xian; Jiang, Chang-Sheng; Xue, Ya-Li; Fang, Wei

    Generally, fuzzy approximation models require some human knowledge and experience. Operator's experience is involved in the mathematics of fuzzy theory as a collection of heuristic rules. The main goal of this paper is to present a new method for identifying unknown nonlinear dynamics such as Rössler system without any human knowledge. Instead of heuristic rules, the presented method uses the input-output data pairs to identify the Rössler chaotic system. The training algorithm is a modified Levenberg-Marquardt (L-M) method, which can adjust the parameters of each linear polynomial and fuzzy membership functions on line, and do not rely on experts' experience excessively. Finally, it is applied to training Rössler chaotic system fuzzy identification. Comparing this method with the standard L-M method, the convergence speed is accelerated. The simulation results demonstrate the effectiveness of the proposed method.

  2. Fuzzy production planning models for an unreliable production system with fuzzy production rate and stochastic/fuzzy demand rate

    Directory of Open Access Journals (Sweden)

    K. A. Halim

    2011-01-01

    Full Text Available In this article, we consider a single-unit unreliable production system which produces a single item. During a production run, the production process may shift from the in-control state to the out-of-control state at any random time when it produces some defective items. The defective item production rate is assumed to be imprecise and is characterized by a trapezoidal fuzzy number. The production rate is proportional to the demand rate where the proportionality constant is taken to be a fuzzy number. Two production planning models are developed on the basis of fuzzy and stochastic demand patterns. The expected cost per unit time in the fuzzy sense is derived in each model and defuzzified by using the graded mean integration representation method. Numerical examples are provided to illustrate the optimal results of the proposed fuzzy models.

  3. A demonstration of expert systems applications in transportation engineering : volume I, transportation engineers and expert systems.

    Science.gov (United States)

    1987-01-01

    Expert systems, a branch of artificial-intelligence studies, is introduced with a view to its relevance in transportation engineering. Knowledge engineering, the process of building expert systems or transferring knowledge from human experts to compu...

  4. Prediksi Kelulusan Mata Kuliah Menggunakan Hybrid Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Abidatul Izzah

    2016-07-01

    Full Text Available AbstrakPerguruan Tinggi merupakan salah satu institusi yang menyimpan data yang sangat informatif jika diolah secara baik. Prediksi kelulusan mahasiswa merupakan kasus di Perguruan Tinggi yang cukup banyak diteliti. Dengan mengetahui prediksi status kelulusan mahasiswa di tengah semester, dosen dapat mengantisipasi atau memberi perhatian khusus pada siswa yang diprediksi tidak lulus. Metode yang digunakan sangat bervariatif termasuk metode Fuzzy Inference System (FIS. Namun dalam implementasinya, proses pembangkitan rule fuzzy sering dilakukan secara random atau berdasarkan pemahaman pakar sehingga tidak merepresentasikan sebaran data. Oleh karena itu, dalam penelitian ini digunakan teknik Decision Tree (DT untuk membangkitkan rule. Dari uraian tersebut, penelitian bertujuan untuk memprediksi kelulusan mata kuliah menggunakan hybrid FIS dan DT. Data yang digunakan dalam penelitian ini adalah data nilai Posttest, Tugas, Kuis, dan UTS dari 106 mahasiswa Politeknik Kediri pengikut mata kuliah Algoritma dan Struktur Data. Penelitian ini diawali dari membangkitkan 5 rule yang selanjutnya digunakan dalam inferensi. Tahap selanjutnya adalah implementasi FIS dengan tahapan fuzzifikasi, inferensi, dan defuzzifikasi. Hasil yang diperoleh adalah akurasi, sensitivitas, dan spesifisitas  masing-masing adalah 94.33%, 96.55%, dan 84.21%.Kata kunci: Decision Tree, Educational Data Mining, Fuzzy Inference System, Prediksi. AbstractCollege is an institution that holds very informative data if it mined properly. Prediction about student’s graduation is a common case that many discussed. Having the predictions of student’s graduation in the middle semester, lecturer will anticipate or give some special attention to students who would be not passed. The method used to prediction is very varied including Fuzzy Inference System (FIS. However, fuzzy rule process is often generated randomly or based on knowledge experts that not represent the data distribution

  5. Database, expert systems, information retrieval

    International Nuclear Information System (INIS)

    Fedele, P.; Grandoni, G.; Mammarella, M.C.

    1989-12-01

    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)

  6. System and method for creating expert systems

    Science.gov (United States)

    Hughes, Peter M. (Inventor); Luczak, Edward C. (Inventor)

    1998-01-01

    A system and method provides for the creation of a highly graphical expert system without the need for programming in code. An expert system is created by initially building a data interface, defining appropriate Mission, User-Defined, Inferred, and externally-generated GenSAA (EGG) data variables whose data values will be updated and input into the expert system. Next, rules of the expert system are created by building appropriate conditions of the rules which must be satisfied and then by building appropriate actions of rules which are to be executed upon corresponding conditions being satisfied. Finally, an appropriate user interface is built which can be highly graphical in nature and which can include appropriate message display and/or modification of display characteristics of a graphical display object, to visually alert a user of the expert system of varying data values, upon conditions of a created rule being satisfied. The data interface building, rule building, and user interface building are done in an efficient manner and can be created without the need for programming in code.

  7. An expert system for uranium exploration

    International Nuclear Information System (INIS)

    Chhipa, V.K.; Sengupta, M.

    1989-01-01

    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

  8. Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach

    Directory of Open Access Journals (Sweden)

    Rana Dinesh Singh

    2015-01-01

    Full Text Available Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming.

  9. Fire Effects, Education, and Expert Systems

    Science.gov (United States)

    Robert E. Martin

    1987-01-01

    Predicting the effects of fires in the year 2000 and beyond will be enhanced by the use of expert systems. Although our predictions may have broad confidence limits, expert systems should help us to improve the predictions and to focus on the areas where improved knowledge is most needed. The knowledge of experts can be incorporated into previously existing knowledge...

  10. An Application of Fuzzy Inference System by Clustering Subtractive Fuzzy Method for Estimating of Product Requirement

    Directory of Open Access Journals (Sweden)

    Fajar Ibnu Tufeil

    2009-06-01

    Full Text Available Model fuzzy memiliki kemampuan untuk menjelaskan secara linguistik suatu sistem yang terlalu kompleks. Aturan-aturan dalam model fuzzy pada umumnya dibangun berdasarkan keahlian manusia dan pengetahuan heuristik dari sistem yang dimodelkan. Teknik ini selanjutnya dikembangkan menjadi teknik yang dapat mengidentifikasi aturan-aturan dari suatu basis data yang telah dikelompokkan berdasarkan persamaan strukturnya. Dalam hal ini metode pengelompokan fuzzy berfungsi untuk mencari kelompok-kelompok data. Informasi yang dihasilkan dari metode pengelompokan ini, yaitu informasi tentang pusat kelompok, digunakan untuk membentuk aturan-aturan dalam sistem penalaran fuzzy. Dalam skripsi ini dibahas mengenai penerapan fuzzy infereance system dengan metode pengelompokan fuzzy subtractive clustering, yaitu untuk membentuk sistem penalaran fuzzy dengan menggunakan model fuzzy Takagi-Sugeno orde satu. Selanjutnya, metode pengelompokan fuzzy subtractive clustering diterapkan dalam memodelkan masalah dibidang pemasaran, yaitu untuk memprediksi permintaan pasar terhadap suatu produk susu. Aplikasi ini dibangun menggunakan Borland Delphi 6.0. Dari hasil pengujian diperoleh tingkat error prediksi terkecil yaitu dengan Error Average 0.08%.

  11. Expert systems: A 5-year perspective

    International Nuclear Information System (INIS)

    MacAllister, D.J.; Day, R.; McCormack, M.D.

    1996-01-01

    This paper gives an overview of a major integrated oil company's experience with artificial intelligence (AI) over the last 5 years, with an emphasis on expert systems. The authors chronicle the development of an AI group, including details on development tool selection, project selection strategies, potential pitfalls, and descriptions of several completed expert systems. Small expert systems produced by teams of petroleum technology experts and experienced expert system developers that are focused in well-defined technical areas have produced substantial benefits and accelerated petroleum technology transfer

  12. Operational expert system applications in Canada

    CERN Document Server

    Suen, Ching Y

    1992-01-01

    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

  13. Fuzzy controller for an uncertain dynamical system

    DEFF Research Database (Denmark)

    Kulczycki, P.; Wisniewski, Rafal

    2002-01-01

    The present paper deals with the time-optimal control for mechanical systems with uncertain load. A fuzzy approach is used in the design of suboptimal feedback controllers, robust with respect to the load. Statistical kernel estimators are used for the specification of crucial parameters. The met......The present paper deals with the time-optimal control for mechanical systems with uncertain load. A fuzzy approach is used in the design of suboptimal feedback controllers, robust with respect to the load. Statistical kernel estimators are used for the specification of crucial parameters....... The methodology proposed in this work may be easily adopted to other modeling uncertainties of mechanical systems, e.g. motion resistance....

  14. Application of ANNs approach for solving fully fuzzy polynomials system

    Directory of Open Access Journals (Sweden)

    R. Novin

    2017-11-01

    Full Text Available In processing indecisive or unclear information, the advantages of fuzzy logic and neurocomputing disciplines should be taken into account and combined by fuzzy neural networks. The current research intends to present a fuzzy modeling method using multi-layer fuzzy neural networks for solving a fully fuzzy polynomials system. To clarify the point, it is necessary to inform that a supervised gradient descent-based learning law is employed. The feasibility of the method is examined using computer simulations on a numerical example. The experimental results obtained from the investigation of the proposed method are valid and delivers very good approximation results.

  15. A heuristic expert system for forest fire guidance in Greece.

    Science.gov (United States)

    Iliadis, Lazaros S; Papastavrou, Anastasios K; Lefakis, Panagiotis D

    2002-07-01

    Forests and forestlands are common inheritance for all Greeks and a piece of the national wealth that must be handed over to the next generations in the best possible condition. After 1974, Greece faces a severe forest fire problem and forest fire forecasting is the process that will enable the Greek ministry of Agriculture to reduce the destruction. This paper describes the basic design principles of an Expert System that performs forest fire forecasting (for the following fire season) and classification of the prefectures of Greece into forest fire risk zones. The Expert system handles uncertainty and uses heuristics in order to produce scenarios based on the presence or absence of various qualitative factors. The initial research focused on the construction of a mathematical model which attempted to describe the annual number of forest fires and burnt area in Greece based on historical data. However this has proven to be impossible using regression analysis and time series. A closer analysis of the fire data revealed that two qualitative factors dramatically affect the number of forest fires and the hectares of burnt areas annually. The first is political stability and national elections and the other is drought cycles. Heuristics were constructed that use political stability and drought cycles, to provide forest fire guidance. Fuzzy logic was applied to produce a fuzzy expected interval for each prefecture of Greece. A fuzzy expected interval is a narrow interval of values that best describes the situation in the country or a part of the country for a certain time period. A successful classification of the prefectures of Greece in forest fire risk zones was done by the system, by comparing the fuzzy expected intervals to each other. The system was tested for the years 1994 and 1995. The testing has clearly shown that the system can predict accurately, the number of forest fires for each prefecture for the following year. The average accuracy was as high as 85

  16. Expert system for fast reactor diagnostic

    International Nuclear Information System (INIS)

    Parcy, J.P.

    1982-09-01

    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 [fr

  17. Comparison between genetic fuzzy system and neuro fuzzy system to select oil wells for hydraulic fracturing; Comparacao entre genetic fuzzy system e neuro fuzzy system para selecao de pocos de petroleo para fraturamento hidraulico

    Energy Technology Data Exchange (ETDEWEB)

    Castro, Antonio Orestes de Salvo [PETROBRAS, Rio de Janeiro, RJ (Brazil); Ferreira Filho, Virgilio Jose Martins [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)

    2004-07-01

    The hydraulic fracture operation is wide used to increase the oil wells production and to reduce formation damage. Reservoir studies and engineer analysis are made to select the wells for this kind of operation. As the reservoir parameters have some diffuses characteristics, Fuzzy Inference Systems (SIF) have been tested for this selection processes in the last few years. This paper compares the performance of a neuro fuzzy system and a genetic fuzzy system used for hydraulic Fracture well selection, with knowledge acquisition from an operational data base to set the SIF membership functions. The training data and the validation data used were the same for both systems. We concluded that, in despite of the genetic fuzzy system would be a younger process, it got better results than the neuro fuzzy system. Another conclusion was that, as the genetic fuzzy system can work with constraints, the membership functions setting kept the consistency of variables linguistic values. (author)

  18. Expert system development (ESD) shell

    International Nuclear Information System (INIS)

    Padmini, S.; Diwakar, M.P.; Rathode, N.C.; Bairi, B.R.

    1991-01-01

    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

  19. Liquid low level waste management expert system

    International Nuclear Information System (INIS)

    Ferrada, J.J.; Abraham, T.J.; Jackson, J.R.

    1991-01-01

    An expert system has been developed as part of a new initiative for the Oak Ridge National Laboratory (ORNL) systems analysis program. 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. 4 refs., 9 figs

  20. Stability analysis of fuzzy parametric uncertain systems.

    Science.gov (United States)

    Bhiwani, R J; Patre, B M

    2011-10-01

    In this paper, the determination of stability margin, gain and phase margin aspects of fuzzy parametric uncertain systems are dealt. The stability analysis of uncertain linear systems with coefficients described by fuzzy functions is studied. A complexity reduced technique for determining the stability margin for FPUS is proposed. The method suggested is dependent on the order of the characteristic polynomial. In order to find the stability margin of interval polynomials of order less than 5, it is not always necessary to determine and check all four Kharitonov's polynomials. It has been shown that, for determining stability margin of FPUS of order five, four, and three we require only 3, 2, and 1 Kharitonov's polynomials respectively. Only for sixth and higher order polynomials, a complete set of Kharitonov's polynomials are needed to determine the stability margin. Thus for lower order systems, the calculations are reduced to a large extent. This idea has been extended to determine the stability margin of fuzzy interval polynomials. It is also shown that the gain and phase margin of FPUS can be determined analytically without using graphical techniques. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  1. Operational expert system applications in Europe

    CERN Document Server

    Zarri, Gian Piero

    1992-01-01

    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

  2. An expert system for reward systems design.

    OpenAIRE

    Erturk, Alper

    2000-01-01

    Approved for public release; distribution is unlimited Today's business environment is a highly competitive marketplace. In this competition, organizations distribute numerous rewards to motivate, attract and retain employees, such as pay, fringe benefits and promotions. However, not all managers have the necessary knowledge and expertise to effectively decide and structure reward systems. This thesis presents an expert system to assist managers with designing the most appropriate reward s...

  3. Fuzzy Dynamic Discrimination Algorithms for Distributed Knowledge Management Systems

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2010-12-01

    Full Text Available A reduction of the algorithmic complexity of the fuzzy inference engine has the following property: the inputs (the fuzzy rules and the fuzzy facts can be divided in two parts, one being relatively constant for a long a time (the fuzzy rule or the knowledge model when it is compared to the second part (the fuzzy facts for every inference cycle. The occurrence of certain transformations over the constant part makes sense, in order to decrease the solution procurement time, in the case that the second part varies, but it is known at certain moments in time. The transformations attained in advance are called pre-processing or knowledge compilation. The use of variables in a Business Rule Management System knowledge representation allows factorising knowledge, like in classical knowledge based systems. The language of the first-degree predicates facilitates the formulation of complex knowledge in a rigorous way, imposing appropriate reasoning techniques. It is, thus, necessary to define the description method of fuzzy knowledge, to justify the knowledge exploiting efficiency when the compiling technique is used, to present the inference engine and highlight the functional features of the pattern matching and the state space processes. This paper presents the main results of our project PR356 for designing a compiler for fuzzy knowledge, like Rete compiler, that comprises two main components: a static fuzzy discrimination structure (Fuzzy Unification Tree and the Fuzzy Variables Linking Network. There are also presented the features of the elementary pattern matching process that is based on the compiled structure of fuzzy knowledge. We developed fuzzy discrimination algorithms for Distributed Knowledge Management Systems (DKMSs. The implementations have been elaborated in a prototype system FRCOM (Fuzzy Rule COMpiler.

  4. Expert database system for quality control

    Science.gov (United States)

    Wang, Anne J.; Li, Zhi-Cheng

    1993-09-01

    There are more competitors today. Markets are not homogeneous they are fragmented into increasingly focused niches requiring greater flexibility in the product mix shorter manufacturing production runs and above allhigher quality. In this paper the author identified a real-time expert system as a way to improve plantwide quality management. The quality control expert database system (QCEDS) by integrating knowledge of experts in operations quality management and computer systems use all information relevant to quality managementfacts as well as rulesto determine if a product meets quality standards. Keywords: expert system quality control data base

  5. Phase inductance estimation for switched reluctance motor using adaptive neuro-fuzzy inference system

    International Nuclear Information System (INIS)

    Daldaban, Ferhat; Ustkoyuncu, Nurettin; Guney, Kerim

    2006-01-01

    A new method based on an adaptive neuro-fuzzy inference system (ANFIS) for estimating the phase inductance of switched reluctance motors (SRMs) is presented. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the ANFIS. The rotor position and the phase current of the 6/4 pole SRM are used to predict the phase inductance. The phase inductance results predicted by the ANFIS are in excellent agreement with the results of the finite element method

  6. Formalization of software requirements for information systems using fuzzy logic

    Science.gov (United States)

    Yegorov, Y. S.; Milov, V. R.; Kvasov, A. S.; Sorokoumova, S. N.; Suvorova, O. V.

    2018-05-01

    The paper considers an approach to the design of information systems based on flexible software development methodologies. The possibility of improving the management of the life cycle of information systems by assessing the functional relationship between requirements and business objectives is described. An approach is proposed to establish the relationship between the degree of achievement of business objectives and the fulfillment of requirements for the projected information system. It describes solutions that allow one to formalize the process of formation of functional and non-functional requirements with the help of fuzzy logic apparatus. The form of the objective function is formed on the basis of expert knowledge and is specified via learning from very small data set.

  7. Intelligent monitoring of water chemistry - Diagnostic expert system DIWATM

    International Nuclear Information System (INIS)

    Metzner, W.; Streit, K.

    2002-01-01

    For fast and comprehensive evaluation of power plant water chemistry conditions and reliable diagnosis in the event of disturbances considerable advantages are provided by employment of the Diagnostic Expert System DIWA. The interface to the process control system (I and C) and the integration of the DIWA system in the office PC network are the preconditions that DIWA operates as a monitoring system in real time. The performance of diagnosis, which are processed by a fuzzy-logic-supported knowledge base ensures not only the detection of all disturbances but also different analyses of the plant operation mode. By editing the knowledge base the Al of the system can increase without system programming. (authors)

  8. A Proposed Method for Solving Fuzzy System of Linear Equations

    Directory of Open Access Journals (Sweden)

    Reza Kargar

    2014-01-01

    Full Text Available This paper proposes a new method for solving fuzzy system of linear equations with crisp coefficients matrix and fuzzy or interval right hand side. Some conditions for the existence of a fuzzy or interval solution of m×n linear system are derived and also a practical algorithm is introduced in detail. The method is based on linear programming problem. Finally the applicability of the proposed method is illustrated by some numerical examples.

  9. Toward the Development of Expert Assessment Systems.

    Science.gov (United States)

    Hasselbring, Ted S.

    1986-01-01

    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)

  10. Cooperative expert system reasoning for waste remediations

    International Nuclear Information System (INIS)

    Bohn, S.J.; Pennock, K.A.; Franklin, A.L.

    1991-12-01

    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

  11. WINE ADVISOR EXPERT SYSTEM USING DECISION RULES

    Directory of Open Access Journals (Sweden)

    Dinuca Elena Claudia

    2013-07-01

    Full Text Available In this article I focus on developing an expert system for advising the choice of wine that best matches a specific occasion. An expert system is a computer application that performs a task that would be performed by a human expert. The implementation is done using Delphi programming language. I used to represent the knowledge bases a set of rules. The rules are of type IF THEN ELSE rules, decision rules based on different important wine features.

  12. Evaluating Loans Using a Combination of Data Envelopment and Neuro-Fuzzy Systems

    OpenAIRE

    Rashmi Malhotra; D.K. Malhotra

    2015-01-01

    A business organization's objective is to make better decisions at all levels of the firm to improve performance. Typically organizations are multi-faceted and complex systems that use uncertain information. Therefore, making quality decisions to improve organizational performance is a daunting task. Organizations use decision support systems that apply different business intelligence techniques such as statistical models, scoring models, neural networks, expert systems, neuro-fuzzy systems, ...

  13. Effects analysis fuzzy inference system in nuclear problems using approximate reasoning

    International Nuclear Information System (INIS)

    Guimaraes, Antonio C.F.; Franklin Lapa, Celso Marcelo

    2004-01-01

    In this paper a fuzzy inference system modeling technique applied on failure mode and effects analysis (FMEA) is introduced in reactor nuclear problems. This method uses the concept of a pure fuzzy logic system to treat the traditional FMEA parameters: probabilities of occurrence, severity and detection. The auxiliary feed-water system of a typical two-loop pressurized water reactor (PWR) was used as practical example in this analysis. The kernel result is the conceptual confrontation among the traditional risk priority number (RPN) and the fuzzy risk priority number (FRPN) obtained from experts opinion. The set of results demonstrated the great potential of the inference system and advantage of the gray approach in this class of problems

  14. Expert Systems: An Introduction -46 ...

    Indian Academy of Sciences (India)

    C++, and Microsoft C/C++ compilers. The personal edition is licensed for educational, research, and hobby use. Applications created with RT -Expert personal edition are not licensed for commercial purposes. Professional editions are available for commercial applications using DOS, Windows, and. Unix environments.

  15. Expert Systems: An Overview for Teacher-Librarians.

    Science.gov (United States)

    Orwig, Gary; Barron, Ann

    1992-01-01

    Provides an overview of expert systems for teacher librarians. Highlights include artificial intelligence and expert systems; the development of the MYCIN medical expert system; rule-based expert systems; the use of expert system shells to develop a specific system; and how to select an appropriate application for an expert system. (11 references)…

  16. Solution of the fully fuzzy linear systems using iterative techniques

    International Nuclear Information System (INIS)

    Dehghan, Mehdi; Hashemi, Behnam; Ghatee, Mehdi

    2007-01-01

    This paper mainly intends to discuss the iterative solution of fully fuzzy linear systems which we call FFLS. We employ Dubois and Prade's approximate arithmetic operators on LR fuzzy numbers for finding a positive fuzzy vector x-tilde which satisfies A-tildex-tilde=b, where A-tilde and b-tilde are a fuzzy matrix and a fuzzy vector, respectively. Please note that the positivity assumption is not so restrictive in applied problems. We transform FFLS and propose iterative techniques such as Richardson, Jacobi, Jacobi overrelaxation (JOR), Gauss-Seidel, successive overrelaxation (SOR), accelerated overrelaxation (AOR), symmetric and unsymmetric SOR (SSOR and USSOR) and extrapolated modified Aitken (EMA) for solving FFLS. In addition, the methods of Newton, quasi-Newton and conjugate gradient are proposed from nonlinear programming for solving a fully fuzzy linear system. Various numerical examples are also given to show the efficiency of the proposed schemes

  17. Advanced Concepts in Fuzzy Logic and Systems with Membership Uncertainty

    CERN Document Server

    Starczewski, Janusz T

    2013-01-01

    This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic ambiguity resulting from limited perception or lack of knowledge about exact membership functions - lack of attributes or granularity arising from discretization of real data - imprecise description of membership functions - vagueness perceived as fuzzification of conditional attributes. Consequently, the membership uncertainty can be modeled by combining methods of conventional and type-2 fuzzy logic, rough set theory and possibility theory.            In particular, this book provides a number of formulae for implementing the operation extended on fuzzy-valued fuzzy sets and presents some basic structures of generalized uncertain fuzzy logic systems, as well as introduces several of methods to generate fuzzy membership uncertainty. It is desirable as a reference book for under-graduates in higher education, master and doctor graduates in the courses of computer science, computational intelligence, or...

  18. Classification of EEG Signals by Radial Neuro-Fuzzy Systems

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2006-01-01

    Roč. 5, č. 2 (2006), s. 415-423 ISSN 1109-2777 R&D Projects: GA MŠk ME 701 Institutional research plan: CEZ:AV0Z10300504 Keywords : neuro-fuzzy systems * radial fuzzy systems * data mining * hybrid systems Subject RIV: BA - General Mathematics

  19. Expert system for estimating LWR plutonium production

    International Nuclear Information System (INIS)

    Sandquist, G.M.

    1988-01-01

    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

  20. Counseling, Artificial Intelligence, and Expert Systems.

    Science.gov (United States)

    Illovsky, Michael E.

    1994-01-01

    Considers the use of artificial intelligence and expert systems in counseling. Limitations are explored; candidates for counseling versus those for expert systems are discussed; programming considerations are reviewed; and techniques for dealing with rational, nonrational, and irrational thoughts and feelings are described. (Contains 46…

  1. Efficient Fuzzy Logic Controller for Magnetic Levitation Systems

    African Journals Online (AJOL)

    Akorede

    ABSTRACT: Magnetic levitation is a system of suspending a body or a complete system against gravity. Suspending a system ... disturbance signal was applied to the input of the control system. Fuzzy ..... Automatic Control System, fifth edition.

  2. Howard University Energy Expert Systems Institute Summer Program (EESI)

    Science.gov (United States)

    Momoh, James A.; Chuku, Arunsi; Abban, Joseph

    1996-01-01

    Howard University, under the auspices of the Center for Energy Systems and Controls runs the Energy Expert Systems Institute (EESI) summer outreach program for high school/pre-college minority students. The main objectives are to introduce precollege minority students to research in the power industry using modern state-of-the-art technology such as Expert Systems, Fuzzy Logic and Artificial Neural Networks; to involve minority students in space power management, systems and failure diagnosis; to generate interest in career options in electrical engineering; and to experience problem-solving in a teamwork environment consisting of faculty, senior research associates and graduate students. For five weeks the students are exposed not only to the exciting experience of college life, but also to the inspiring field of engineering, especially electrical engineering. The program consists of lectures in the fundamentals of engineering, mathematics, communication skills and computer skills. The projects are divided into mini and major. Topics for the 1995 mini projects were Expert Systems for the Electric Bus and Breast Cancer Detection. Topics on the major projects include Hybrid Electric Vehicle, Solar Dynamics and Distribution Automation. On the final day, designated as 'EESI Day' the students did oral presentations of their projects and prizes were awarded to the best group. The program began in the summer of 1993. The reaction from the students has been very positive. The program also arranges field trips to special places of interest such as the NASA Goddard Space Center.

  3. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    International Nuclear Information System (INIS)

    Upadhyaya, B.R.; Yan, W.; Henry, G.

    1999-01-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  4. Development of a diagnostic expert system for eddy current data analysis using applied artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Upadhyaya, B.R.; Yan, W. [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering; Behravesh, M.M. [Electric Power Research Institute, Palo Alto, CA (United States); Henry, G. [EPRI NDE Center, Charlotte, NC (United States)

    1999-09-01

    A diagnostic expert system that integrates database management methods, artificial neural networks, and decision-making using fuzzy logic has been developed for the automation of steam generator eddy current test (ECT) data analysis. The new system, known as EDDYAI, considers the following key issues: (1) digital eddy current test data calibration, compression, and representation; (2) development of robust neural networks with low probability of misclassification for flaw depth estimation; (3) flaw detection using fuzzy logic; (4) development of an expert system for database management, compilation of a trained neural network library, and a decision module; and (5) evaluation of the integrated approach using eddy current data. The implementation to field test data includes the selection of proper feature vectors for ECT data analysis, development of a methodology for large eddy current database management, artificial neural networks for flaw depth estimation, and a fuzzy logic decision algorithm for flaw detection. A large eddy current inspection database from the Electric Power Research Institute NDE Center is being utilized in this research towards the development of an expert system for steam generator tube diagnosis. The integration of ECT data pre-processing as part of the data management, fuzzy logic flaw detection technique, and tube defect parameter estimation using artificial neural networks are the fundamental contributions of this research. (orig.)

  5. Minimal solution of general dual fuzzy linear systems

    International Nuclear Information System (INIS)

    Abbasbandy, S.; Otadi, M.; Mosleh, M.

    2008-01-01

    Fuzzy linear systems of equations, play a major role in several applications in various area such as engineering, physics and economics. In this paper, we investigate the existence of a minimal solution of general dual fuzzy linear equation systems. Two necessary and sufficient conditions for the minimal solution existence are given. Also, some examples in engineering and economic are considered

  6. Coherence of Radial Implicative Fuzzy Systems with Nominal Consequents

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    -, č. 4 (2006), s. 60-66 ISSN 1509-4553 R&D Projects: GA MŠk 1M0545 Institutional research plan: CEZ:AV0Z10300504 Keywords : implicative fuzzy system * radial fuzzy system * nominal output space * coherence Subject RIV: IN - Informatics, Computer Science

  7. Expert systems in power substation operation and control

    Energy Technology Data Exchange (ETDEWEB)

    Ribeiro, Guilherme Moutinho; Lambert-Torres, Germano; Silva, Alexandre P. Alves da [Escola Federal de Engenharia de Itajuba, MG (Brazil)

    1994-12-31

    With digital technology being increasingly adopted in power substations (SE), perspectives are created for integration of supervision, control and protection systems in addition to making its process automation feasible. Once a SE is digitalized, the systems which previously were implemented physically will be able to be implemented by means of computer programs (software), allowing the expansion of its scope of operation. Studies and research performed at the international level have pointed to the utilization of Expert Systems (ES) as a more suitable alternative for representation and solution of the operation and control problems, especially those which do not have an established theory, which are provided with diagnosis characteristics and that associate themselves with fuzzy data and information. (author) 4 refs., 3 figs.

  8. Power Distribution System Planning Evaluation by a Fuzzy Multi-Criteria Group Decision Support System

    Directory of Open Access Journals (Sweden)

    Tiefeng Zhang

    2010-10-01

    Full Text Available The evaluation of solutions is an important phase in power distribution system planning (PDSP which allows issues such as quality of supply, cost, social service and environmental implications to be considered and usually involves the judgments of a group of experts. The planning problem is thus suitable for the multi-criteria group decision-making (MCGDM method. The evaluation process and evaluation criteria often involve uncertainties incorporated in quantitative analysis with crisp values and qualitative judgments with linguistic terms; therefore, fuzzy sets techniques are applied in this study. This paper proposes a fuzzy multi-criteria group decision-making (FMCGDM method for PDSP evaluation and applies a fuzzy multi-criteria group decision support system (FMCGDSS to support the evaluation task. We introduce a PDSP evaluation model, which has evaluation criteria within three levels, based on the characteristics of a power distribution system. A case-based example is performed on a test distribution network and demonstrates how all the problems in a PDSP evaluation are addressed using FMCGDSS. The results are acceptable to expert evaluators.

  9. A Recursive Fuzzy System for Efficient Digital Image Stabilization

    Directory of Open Access Journals (Sweden)

    Nikolaos Kyriakoulis

    2008-01-01

    Full Text Available A novel digital image stabilization technique is proposed in this paper. It is based on a fuzzy Kalman compensation of the global motion vector (GMV, which is estimated in the log-polar plane. The GMV is extracted using four local motion vectors (LMVs computed on respective subimages in the logpolar plane. The fuzzy Kalman system consists of a fuzzy system with the Kalman filter's discrete time-invariant definition. Due to this inherited recursiveness, the output results into smoothed image sequences. The proposed stabilization system aims to compensate any oscillations of the frame absolute positions, based on the motion estimation in the log-polar domain, filtered by the fuzzy Kalman system, and thus the advantages of both the fuzzy Kalman system and the log-polar transformation are exploited. The described technique produces optimal results in terms of the output quality and the level of compensation.

  10. New approach to solve fully fuzzy system of linear equations using ...

    Indian Academy of Sciences (India)

    Known example problems are solved to illustrate the efficacy and ... The concept of fuzzy set and fuzzy number were first introduced by Zadeh .... (iii) Fully fuzzy linear systems can be solved by linear programming approach, Gauss elim-.

  11. A human error probability estimate methodology based on fuzzy inference and expert judgment on nuclear plants

    International Nuclear Information System (INIS)

    Nascimento, C.S. do; Mesquita, R.N. de

    2009-01-01

    Recent studies point human error as an important factor for many industrial and nuclear accidents: Three Mile Island (1979), Bhopal (1984), Chernobyl and Challenger (1986) are classical examples. Human contribution to these accidents may be better understood and analyzed by using Human Reliability Analysis (HRA), which has being taken as an essential part on Probabilistic Safety Analysis (PSA) of nuclear plants. Both HRA and PSA depend on Human Error Probability (HEP) for a quantitative analysis. These probabilities are extremely affected by the Performance Shaping Factors (PSF), which has a direct effect on human behavior and thus shape HEP according with specific environment conditions and personal individual characteristics which are responsible for these actions. This PSF dependence raises a great problem on data availability as turn these scarcely existent database too much generic or too much specific. Besides this, most of nuclear plants do not keep historical records of human error occurrences. Therefore, in order to overcome this occasional data shortage, a methodology based on Fuzzy Inference and expert judgment was employed in this paper in order to determine human error occurrence probabilities and to evaluate PSF's on performed actions by operators in a nuclear power plant (IEA-R1 nuclear reactor). Obtained HEP values were compared with reference tabled data used on current literature in order to show method coherence and valid approach. This comparison leads to a conclusion that this work results are able to be employed both on HRA and PSA enabling efficient prospection of plant safety conditions, operational procedures and local working conditions potential improvements (author)

  12. An Expert System for Designing Fire Prescriptions

    Science.gov (United States)

    Elizabeth Reinhardt

    1987-01-01

    Managers use prescribed fire to accomplish a variety of resource objectives. The knowledge needed to design successful prescriptions is both quantitative and qualitative. Some of it is available through publications and computer programs, but much of the knowledge of expert practitioners has never been collected or published. An expert system being developed at the,...

  13. customer satisfaction, customer relationship management, Fuzzy Delphi, system dynamics.

    OpenAIRE

    Habib A. Mirghafoori; Ali Morovati Sharifabadi; Ensiyeh Taki

    2016-01-01

    This paper investigates the factors which are affecting customers satisfaction of Mobarake steel complex . Since there is a wide rang of factors affecting customer satisfaction,this paper pays attention to those factors which have CRM approach. The investigation society of the research is the marketing experts of Moabarake steel complex who have direct relationship with customers.At first, the factors were identified by experts using Fuzzy Delphi method and then the relationship between facto...

  14. Model Reduction of Fuzzy Logic Systems

    Directory of Open Access Journals (Sweden)

    Zhandong Yu

    2014-01-01

    Full Text Available This paper deals with the problem of ℒ2-ℒ∞ model reduction for continuous-time nonlinear uncertain systems. The approach of the construction of a reduced-order model is presented for high-order nonlinear uncertain systems described by the T-S fuzzy systems, which not only approximates the original high-order system well with an ℒ2-ℒ∞ error performance level γ but also translates it into a linear lower-dimensional system. Then, the model approximation is converted into a convex optimization problem by using a linearization procedure. Finally, a numerical example is presented to show the effectiveness of the proposed method.

  15. 20 CFR 405.10 - Medical and Vocational Expert System.

    Science.gov (United States)

    2010-04-01

    ... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Medical and Vocational Expert System. 405.10... Vocational Expert System. (a) General. The Medical and Vocational Expert System is comprised of the Medical... Vocational Expert System. (3) Experts who provide evidence at your request. Experts whom you ask to provide...

  16. A first course in fuzzy logic, fuzzy dynamical systems, and biomathematics theory and applications

    CERN Document Server

    de Barros, Laécio Carvalho; Lodwick, Weldon Alexander

    2017-01-01

    This book provides an essential introduction to the field of dynamical models. Starting from classical theories such as set theory and probability, it allows readers to draw near to the fuzzy case. On one hand, the book equips readers with a fundamental understanding of the theoretical underpinnings of fuzzy sets and fuzzy dynamical systems. On the other, it demonstrates how these theories are used to solve modeling problems in biomathematics, and presents existing derivatives and integrals applied to the context of fuzzy functions. Each of the major topics is accompanied by examples, worked-out exercises, and exercises to be completed. Moreover, many applications to real problems are presented. The book has been developed on the basis of the authors’ lectures to university students and is accordingly primarily intended as a textbook for both upper-level undergraduates and graduates in applied mathematics, statistics, and engineering. It also offers a valuable resource for practitioners such as mathematical...

  17. Expert systems for assisting in design reviews

    International Nuclear Information System (INIS)

    Brtis, J.S.; Johnson, W.J.; Weber, N.; Naser, J.

    1990-01-01

    This paper discusses Sargent and Lundy's (S and L's) use of expert system technologies to computerize the procedures used for engineering design reviews. This paper discusses expert systems and the advantages that result from using them to computerize the decision-making process. This paper also discusses the design review expert systems that S and L has developed to perform fire protection and ALARA (as low as reasonably achievable) design reviews, and is currently developing for the Electric Power Research Institute (EPRI) to perform 10 CFR 50.59 safety reviews

  18. An expert system for dispersion model interpretation

    International Nuclear Information System (INIS)

    Skyllingstad, E.D.; Ramsdell, J.V.

    1988-10-01

    A prototype expert system designed to diagnose dispersion model uncertainty is described in this paper with application to a puff transport model. The system obtains qualitative information from the model user and through an expert-derived knowledge base, performs a rating of the current simulation. These results can then be used in combination with dispersion model output for deciding appropriate evacuation measures. Ultimately, the goal of this work is to develop an expert system that may be operated accurately by an individual uneducated in meteorology or dispersion modeling. 5 refs., 3 figs

  19. Fuzzy logic system for BBT based fertility prediction | Yazed | Journal ...

    African Journals Online (AJOL)

    ... been obtained with the accuracy of 95 % and 80 respectively. Besides, this prediction system using fuzzy logic could improve the current practice in the FAM technique by integrating it with an Internet of Things (IoT) technology for automatic BBT charting and monitoring. Keywords: family planning; fertility; BBT; fuzzy logic.

  20. System control fuzzy neural sewage pumping stations using genetic algorithms

    Directory of Open Access Journals (Sweden)

    Владлен Николаевич Кузнецов

    2015-06-01

    Full Text Available It is considered the system of management of sewage pumping station with regulators based on a neuron network with fuzzy logic. Linguistic rules for the controller based on fuzzy logic, maintaining the level of effluent in the receiving tank within the prescribed limits are developed. The use of genetic algorithms for neuron network training is shown.

  1. Expert system aids transport regulation users

    International Nuclear Information System (INIS)

    Cheshire, R.D.; Straw, R.J.

    1990-01-01

    During late 1984 the IAEA Regulations were identified as an area of application for an expert system adviser which could offer many advantages. Over the following year some simple tests were carried out to examine its feasibility, but TRANAID did not get underway until 1986 when British Nuclear Fuels (BNFL) Corporate Management services were engaged on the product. By this time a greater choice of suitable software, in the form of expert system shells, had become available. After a number of trial systems the shell Leonardo was finally adopted for the final system. In order for TRANAID to emulate the expert it was necessary to spend time extracting and documenting the expert knowledge. This was a matter of investigating how the regulations are used and was achieved by a series of meetings including opportunity for the computer specialists to interview the regulations experts. There are several benefits in having an expert system advisor in this area. It is useful to both experienced and inexperienced users of regulations. For those who are learning to use the regulations it is an excellent training aid. For those who know the regulations but use them infrequently it can save time and provide a valuable reassurance. The adviser has enabled the expert user's know how to be captured and to be made widely available to those with less experience. (author)

  2. NESSUS/EXPERT - An expert system for probabilistic structural analysis methods

    Science.gov (United States)

    Millwater, H.; Palmer, K.; Fink, P.

    1988-01-01

    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.

  3. An expert system for turbogenerator diagnostics

    International Nuclear Information System (INIS)

    Bessenyei, Z.; Tomcsanyi, T.; Toth, Z.; Laczay, I.

    1992-01-01

    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

  4. Fuzzy Diagnostic System for Oleo-Pneumatic Drive Mechanism of High-Voltage Circuit Breakers

    Directory of Open Access Journals (Sweden)

    Viorel Nicolau

    2013-01-01

    Full Text Available Many oil-based high-voltage circuit breakers are still in use in national power networks of developing countries, like those in Eastern Europe. Changing these breakers with new more reliable ones is not an easy task, due to their implementing costs. The acting device, called oleo-pneumatic mechanism (MOP, presents the highest fault rate from all components of circuit breaker. Therefore, online predictive diagnosis and early detection of the MOP fault tendencies are very important for their good functioning state. In this paper, fuzzy logic approach is used for the diagnosis of MOP-type drive mechanisms. Expert rules are generated to estimate the MOP functioning state, and a fuzzy system is proposed for predictive diagnosis. The fuzzy inputs give information about the number of starts and time of functioning per hour, in terms of short-term components, and their mean values. Several fuzzy systems were generated, using different sets of membership functions and rule bases, and their output performances are studied. Simulation results are presented based on an input data set, which contains hourly records of operating points for a time horizon of five years. The fuzzy systems work well, making an early detection of the MOP fault tendencies.

  5. Principles of expert fuzzy controller design: AI mobile wall climbing robots for decontamination of nuclear power-station

    International Nuclear Information System (INIS)

    Gradetsky, V.G.; Ul'yanov, S.; Slesarev, Y.V.; Pospelov, D.A.

    1994-01-01

    The arrangement principles for a complex control framework of artificial intelligence control systems are introduced. The notions of intelligence levels with the top boundary (intelligence in large) and the bottom boundary (intelligence in small) are defined. A special methodology for the design of an artificial intelligence control system design for the decontamination of a nuclear power plant using a wall climbing robot with different intelligence levels is presented. The application of WARP (Weight Associative Rule Processor) to the design of an automatic fuzzy controller for the fuzzy correction of the motion of the manipulator and WCR is examined

  6. Jess, the Java expert system shell

    Energy Technology Data Exchange (ETDEWEB)

    Friedman-Hill, E.J.

    1997-11-01

    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.

  7. A neuro-fuzzy inference system for sensor monitoring

    International Nuclear Information System (INIS)

    Na, Man Gyun

    2001-01-01

    A neuro-fuzzy inference system combined with the wavelet denoising, PCA (principal component analysis) and SPRT (sequential probability ratio test) methods has been developed to monitor the relevant sensor using the information of other sensors. The paramters of the neuro-fuzzy inference system which estimates the relevant sensor signal are optimized by a genetic algorithm and a least-squares algorithm. The wavelet denoising technique was applied to remove noise components in input signals into the neuro-fuzzy system. By reducing the dimension of an input space into the neuro-fuzzy system without losing a significant amount of information, the PCA was used to reduce the time necessary to train the neuro-fuzzy system, simplify the structure of the neuro-fuzzy inference system and also, make easy the selection of the input signals into the neuro-fuzzy system. By using the residual signals between the estimated signals and the measured signals, the SPRT is applied to detect whether the sensors are degraded or not. The proposed sensor-monitoring algorithm was verified through applications to the pressurizer water level, the pressurizer pressure, and the hot-leg temperature sensors in pressurized water reactors

  8. Study on advanced nuclear power plants expert evaluation system in China

    International Nuclear Information System (INIS)

    Zhang Qi; Yoshikawa, Hidekazu; Shimoda, Hiroshi; Zhou Zhiwei; Zhu Shutang; Ren Junsheng; Yang Mengjia; Gu Junyang

    2005-01-01

    Based on current status and developing trend of nuclear power plant technology, an evaluation software system is developed to assess advanced NPPs systematically according to a set of pre-established evaluation indices. The selection and classification of the indices, the determination of their weighting factors in applying AHP (analytic hierarchy process) method are discussed. The Fuzzy Comprehensive method and the Fuzzy Borda Number method are studied in detail. The original input data required by the evaluation system are deduced from the expert survey sheets Evaluation results with common significance of public attraction are discussed and analyzed according to the opinions of different experts grouped by age, profession and working expertise etc. The evaluation system is computer network based with high flexible and user friendly human-machine interface on which it is easy to manipulate and update the evaluation system, and to display evaluation results as well. (author)

  9. Supplier Selection Using Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    hamidreza kadhodazadeh

    2014-01-01

    Full Text Available Suppliers are one of the most vital parts of supply chain whose operation has significant indirect effect on customer satisfaction. Since customer's expectations from organization are different, organizations should consider different standards, respectively. There are many researches in this field using different standards and methods in recent years. The purpose of this study is to propose an approach for choosing a supplier in a food manufacturing company considering cost, quality, service, type of relationship and structure standards of the supplier organization. To evaluate supplier according to the above standards, the fuzzy inference system has been used. Input data of this system includes supplier's score in any standard that is achieved by AHP approach and the output is final score of each supplier. Finally, a supplier has been selected that although is not the best in price and quality, has achieved good score in all of the standards.

  10. Expert system in PNC, 4

    International Nuclear Information System (INIS)

    Yamamoto, Fumio; Nakazawa, Hiroaki

    1990-01-01

    We have been developing an operation assisting system, partially supported by AI system, for uranium enrichment plant. The AI system is a proto-type system aiming a final one which can be applied to any future large uranium enrichment plant and also not only to specific operational area but also to complex and multi-phenomenon operational area. An existing AI system, for example facility diagnostic system that utilizes the result of CCT(Cause Consequence Tree) analysis as knowledge base, has weakness in flexibility and potentiality. To build AI system, we have developed the most suitable knowledge representations using deep knowledge for each facility or operation of uranium enrichment plant. This paper describes our AI proto-type system adopting several knowledge representations that can represent an uranium enrichment plant's operation with deep knowledge. (author)

  11. Induction machine Direct Torque Control system based on fuzzy adaptive control

    Science.gov (United States)

    Li, Shi-ping; Yu, Yan; Jiao, Zhen-gang; Gu, Shu-sheng

    2009-07-01

    Direct Torque Control technology is a high-performance communication control method, it uses the space voltage vector method, and then to the inverter switch state control, to obtain high torque dynamic performance. But none of the switching states is able to generate the exact voltage vector to produce the desired changes in torque and flux in most of the switching instances. This causes a high ripple in torque. To solve this problem, a fuzzy implementation of Direct Torque Control of Induction machine is presented here. Error of stator flux, error of motor electromagnetic torque and position of angle of flux are taken as fuzzy variables. In order to further solve nonlinear problem of variation parameters in direct torque control system, the paper proposes a fuzzy parameter PID adaptive control method which is suitable for the direct torque control of an asynchronous motor. The generation of its fuzzy control is obtained by analyzing and optimizing PID control step response and combining expert's experience. For this reason, it carries out fuzzy work to PID regulator of motor speed to achieve to regulate PID parameters. Therefore the control system gets swifter response velocity, stronger robustness and higher precision of velocity control. The computer simulated results verify the validity of this novel method.

  12. System Experts and Decision Making Experts in Transdisciplinary Projects

    Science.gov (United States)

    Mieg, Harald A.

    2006-01-01

    Purpose: This paper aims at a better understanding of expert roles in transdisciplinary projects. Thus, the main purpose is the analysis of the roles of experts in transdisciplinary projects. Design/methodology/approach: The analysis of the ETH-UNS case studies from the point of view of the psychology of expertise and the sociology of professions…

  13. Modeling and control of an unstable system using probabilistic fuzzy inference system

    Directory of Open Access Journals (Sweden)

    Sozhamadevi N.

    2015-09-01

    Full Text Available A new type Fuzzy Inference System is proposed, a Probabilistic Fuzzy Inference system which model and minimizes the effects of statistical uncertainties. The blend of two different concepts, degree of truth and probability of truth in a unique framework leads to this new concept. This combination is carried out both in Fuzzy sets and Fuzzy rules, which gives rise to Probabilistic Fuzzy Sets and Probabilistic Fuzzy Rules. Introducing these probabilistic elements, a distinctive probabilistic fuzzy inference system is developed and this involves fuzzification, inference and output processing. This integrated approach accounts for all of the uncertainty like rule uncertainties and measurement uncertainties present in the systems and has led to the design which performs optimally after training. In this paper a Probabilistic Fuzzy Inference System is applied for modeling and control of a highly nonlinear, unstable system and also proved its effectiveness.

  14. New approach to solve fully fuzzy system of linear equations using ...

    Indian Academy of Sciences (India)

    This paper proposes two new methods to solve fully fuzzy system of linear equations. The fuzzy system has been converted to a crisp system of linear equations by using single and double parametric form of fuzzy numbers to obtain the non-negative solution. Double parametric form of fuzzy numbers is defined and applied ...

  15. Computers start to think with expert systems

    Energy Technology Data Exchange (ETDEWEB)

    1983-03-21

    A growing number of professionals-notably in oil and mineral exploration, plasma research, medicine, VLSI circuit design, drug design and robotics-are beginning to use computerised expert systems. A computer program uses knowledge and inference procedures to solve problems which are sufficiently difficult to require significant human expertise for their solution. The facts constitute a body of information that is widely shared, publicly available and generally agreed upon by experts in the field. The heuristics are mostly private, and little discussed, rules of good judgement (rules of plausible reasoning, rules of good guessing, etc.) that characterise expert-level decision making in the field.

  16. ZEXP - expert system for ZEUS

    International Nuclear Information System (INIS)

    Behrens, U.; Flasinski, M.; Hagge, L.

    1992-10-01

    The proper and timely reactions to errors occurring in the online data-acquisition (DAQ) system are necessary conditions of smooth data taking during the experiment runs. Since the Eventbuilder (EVB) is a central part of the ZEUS DAQ system, it is the best place for monitoring, detecting, and recognizing erroneous behaviour. ZEXP is a software tool for upgrading the DAQ system performance. The pattern recognition methodology used for designing one of its two main modules is discussed. The general design ideas of the system and some preliminary results from the summarizing run module are presented, as well. (orig.)

  17. Study on Design of Control Module and Fuzzy Control System

    International Nuclear Information System (INIS)

    Lee, Chang Kyu; Sohn, Chang Ho; Kim, Jung Seon; Kim, Min Kyu

    2005-01-01

    Performance of control unit is improved by introduction of fuzzy control theory and compensation for input of control unit as FLC(Fuzzy Logic Controller). Here, FLC drives thermal control system by linguistic rule-base. Hence, In case of using compensative PID control unit, it doesn't need to revise or compensate for PID control unit. Consequently, this study shows proof that control system which implements H/W module and then uses fuzzy algorism in this system is stable and has reliable performance

  18. A computerized expert system for mammography

    International Nuclear Information System (INIS)

    Jackson, V.P.; Dines, K.A.; Bassett, L.W.

    1988-01-01

    The authors have developed a computer-based expert system to aid in the interpretation of mammograms, breast sonograms, and clinical findings. The radiologist enters clinical and image data into the artificial intelligence system and receives a prediction of the etiology of lesions seen on breast imaging studies. This prototype interactive system has undergone preliminary clinical testing and evaluation. Ultimately, a more refined and complex system will be of value in mammography education, for general radiologists without ready access to mammography experts, for paramedical personnel, and for all mammographers in need of a breast imaging database and reporting systems

  19. Fuzzy comprehensive evaluation of district heating systems

    International Nuclear Information System (INIS)

    Wei Bing; Wang Songling; Li Li

    2010-01-01

    Selecting the optimal type of district heating (DH) system is of great importance because different heating systems have different levels of efficiency, which will impact the system economics, environment and energy use. In this study, seven DH systems were analysed and evaluated by the fuzzy comprehensive evaluation method. The dimensionless number-goodness was introduced into the calculation, the economics, environment and energy technology factors were considered synthetically, and the final goodness values were obtained. The results show that if only one of the economics, environment or energy technology factors are considered, different heating systems have different goodness values. When all three factors were taken into account, the final ranking of goodness values was: combined heating and power>gas-fired boiler>water-source heat pump>coal-fired boiler>ground-source heat pump>solar-energy heat pump>oil-fired boiler. The combined heating and power system is the best choice from all seven systems; the gas-fired boiler system is the best of the three boiler systems for heating purpose; and the water-source heat pump is the best of the three heat pump systems for heating and cooling.

  20. Enhancing an adaptive e-learning system with didactic test assessment using an expert system

    Science.gov (United States)

    Bradáč, Vladimír; Kostolányová, Kateřina

    2017-07-01

    The paper deals with a follow-up research on intelligent tutoring systems that were studied in authors' previous papers from the point of view of describing their advantages. In this paper, the authors make use of the fuzzy logic expert system, which assesses student's knowledge, and integrate it into the intelligent tutoring system called Barborka. The goal is to create an even more personal student's study plan, which is tailored both to student's sensory/learning preferences and the level of knowledge of the given subject.

  1. Use of expert systems in nuclear safety

    International Nuclear Information System (INIS)

    1990-02-01

    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

  2. An expert system approach for safety diagnosis

    International Nuclear Information System (INIS)

    Erdmann, R.C.; Sun, B.K.H.

    1988-01-01

    An expert system was developed with the intent to provide real-time information about an accident to an operator who is in the process of diagnosing and bringing that accident under control. Explicit use was made of probabilistic risk analysis techniques and plant accident response information in constructing this system. The expert system developed contains 70 logic rules and provides contextual messages during simulated accident sequences and logic sequence information on the entire sequence in graphical form for accident diagnosis. The present analysis focuses on integrated control system-related transients with Babcock and Wilcox-type reactors. While the system developed here is limited in extent and was built for a composite reactor, it demonstrates that an expert system may enhance the operator's capability in the control room

  3. Advisory expert system for test rig operator

    International Nuclear Information System (INIS)

    Zielczynski, P.

    1994-01-01

    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

  4. Expert system in PNC, 7

    International Nuclear Information System (INIS)

    Goto, Takashi; Mano, Tadashi; Yamamoto, Masao; Tuboya, Takao.

    1990-01-01

    As regards radioactive waste management (conditioning, storage and disposal), political, regulatory, economic and technological reviews of the activities in advanced nations are indispensable to PNC's performing effective and efficient R and D projects. However, collecting and analyzing a large quantity of overseas information is so much work that it is difficult to reflect those reviews on the direction in PNC's R and D project appropriately and timely. A work was performed to develop international radioactive waste information data base system named WIND with highly functioned and handy personal computer so that the information in broad range could be effectively updated and readily available for the most effective use for PNC's program. WIND system is utilized in PNC radioactive waste management sections and also in another company, and makes the reviews of the overseas activities on radioactive waste management much easier at present. This paper presents the feature and performance of WIND system. (author)

  5. Fault Diagnosis in Dynamic Systems Using Fuzzy Interacting Observers

    Directory of Open Access Journals (Sweden)

    N. V. Kolesov

    2013-01-01

    Full Text Available A method of fault diagnosis in dynamic systems based on a fuzzy approach is proposed. The new method possesses two basic specific features which distinguish it from the other known fuzzy methods based on the application of fuzzy logic and a bank of state observers. First, this method uses a bank of interacting observers instead of traditional independent observers. The second specific feature of the proposed method is the assumption that there is no strict boundary between the serviceable and disabled technical states of the system, which makes it possible to specify a decision making rule for fault diagnosis.

  6. Expert system for web based collaborative CAE

    Science.gov (United States)

    Hou, Liang; Lin, Zusheng

    2006-11-01

    An expert system for web based collaborative CAE was developed based on knowledge engineering, relational database and commercial FEA (Finite element analysis) software. The architecture of the system was illustrated. In this system, the experts' experiences, theories and typical examples and other related knowledge, which will be used in the stage of pre-process in FEA, were categorized into analysis process and object knowledge. Then, the integrated knowledge model based on object-oriented method and rule based method was described. The integrated reasoning process based on CBR (case based reasoning) and rule based reasoning was presented. Finally, the analysis process of this expert system in web based CAE application was illustrated, and an analysis example of a machine tool's column was illustrated to prove the validity of the system.

  7. Intelligent control-II: review of fuzzy systems and theory of approximate reasoning

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    Fuzzy systems are knowledge-based or rule-based systems. The heart of a fuzzy systems knowledge base consisting of the so-called fuzzy IF -THEN rules. This paper reviews various aspects of fuzzy IF-THEN rules. The theory of approximate reasoning, which provides a powerful framework for reasoning the imprecise and uncertain information, , is also reviewed. Additional properties of fuzzy systems are also discussed. (author)

  8. FUZZY MAPPING IN DATA SONIFICATION SYSTEM OF WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    Arseny A. Markhotin

    2016-11-01

    Full Text Available Problem Statement. This paper describes the modeling of sonification system with possible types of wireless sensor network data. Fuzzy logic is used for the data-to-sound mapping. Methods. Devised sonification system includes input data model and sound synthesis core. It was created in Pure Data. For fuzzy output of mapped data the Fuzzy Logic Toolboxof MATLABwas used. Moreover, the system model has an ability to send data to the side application via UDP protocol. Results. We offer the method of timbre space organization for sonification system output and the following output of control sound characteristics depending on the type of input data. Practical Relevance. The offered approach of using fuzzy logic in sonification systems can be applied in development of new applications when the formalization of data-to-sound mapping is difficult and also complicated timbal space organization is required.

  9. Application of fuzzy control in cooling systems save energy design

    Energy Technology Data Exchange (ETDEWEB)

    Chen, M.L.; Liang, H.Y. [Chienkuo Technology Univ., Changhua, Taiwan (China). Dept. of Electrical Engineering

    2005-07-01

    A fuzzy logic programmable logic controller (PLC) was used to control the cooling systems of frigorific equipment. Frigorific equipment is used to move unwanted heat outside of building in order to control indoor temperatures. The aim of the fuzzy logic PLC was to improve the energy efficiency of the cooling system. Control of the cooling pump and cooling tower in the system was based on the water temperature of the condenser during frigorific system operation. A human computer design for the cooling system control was used to set speeds and to automate and adjust the motor according to the fuzzy logic controller. It was concluded that if fuzzy logic controllers are used with all components of frigorific equipment, energy efficiency will be significantly increased. 5 refs., 3 tabs., 9 figs.

  10. Methodology toward second generation expert systems

    International Nuclear Information System (INIS)

    Dormoy, J.L.

    1989-01-01

    So-called First Generation Expert Systems were aimed at capturing the expert's know-how. Though providing remarkable achievements, this first wave did not give the expected outcome. A new generation is getting out from the laboratories. Instead of remaining at a shallow level of knowledge - that is the unmotivated reasoning processes expressed by an expert when he is forced to tell them - one attempts to re-build this level of knowledge from the first principles which constitute the basis of an expert's knowledge. These systems are called deep knowledge-based, or second generation expert systems. Discussion in the three first parts rests on two examples: A first generation and a half system for process control in nuclear powers plants, than the system EXTRA for alarm processing in nuclear plants, wherein fonctional knowledge is explicitely represented. We show how deep knowledge can be implemented, and the advantages that can be expected from this methodology. Qualitative Physics is discussed in the next part. Future research developments as well as potential payoffs are mentioned [fr

  11. Genetic fuzzy system predicting contractile reactivity patterns of small arteries

    DEFF Research Database (Denmark)

    Tang, J; Sheykhzade, Majid; Clausen, B F

    2014-01-01

    strategies. Results show that optimized fuzzy systems (OFSs) predict contractile reactivity of arteries accurately. In addition, OFSs identified significant differences that were undetectable using conventional analysis in the responses of arteries between groups. We concluded that OFSs may be used...

  12. Hybridizing fuzzy control and timed automata for modeling variable structure fuzzy systems

    NARCIS (Netherlands)

    Acampora, G.; Loia, V.; Vitiello, A.

    2010-01-01

    During the past several years, fuzzy control has emerged as one of the most suitable and efficient methods for designing and developing complex systems in environments characterized by high level of uncertainty and imprecision. Nowadays, this methodology is used to model systems in several

  13. Distributed expert systems for nuclear reactor control

    International Nuclear Information System (INIS)

    Otaduy, P.J.

    1992-01-01

    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

  14. An expert system for USNRC emergency response

    International Nuclear Information System (INIS)

    Sebo, D.E.; Bray, M.A.; King, M.A.

    1986-01-01

    The Reactor Safety Assessment System (RSAS) is an expert system under development for the United States Nuclear Regulatory Commission (USNRC). RSAS is intended for use at the NRO's Operations Center in the event of a serious incident at a licensed nuclear power plant. RSAS is a situation assessment expert system which uses plant parametric data to generate conclusions for use by the NRC Reactor Safety Team. RSAS uses multiple rule bases and plant specific setpoint files in order to be applicable to all licensed power plants. RSAS currently covers several generic reactor types and power plants within those classes

  15. Expert system for USNRC emergency response

    International Nuclear Information System (INIS)

    Sebo, D.E.; Bray, M.A.; King, M.A.

    1986-01-01

    The Reactor Safety Assessment System (RSAS) is an expert system under development for the United States Nuclear Regulatory Commission (USNRC). RSAS is intended for use at the NRC's Operations Center in the event of a serious incident at a licensed nuclear power plant. RSAS is a situation assessment expert system which uses plant parametric data to generate conclusions for use by the NRC Reactor Safety Team. RSAS uses multiple rule bases and plant specific setpoint files in order to be applicable to all licensed power plants. RSAS currently covers several generic reactor types and power plants within those classes

  16. A Formal Definition for Expert Systems used in Real-time Applications

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2015-05-01

    Full Text Available The present paper is situated on the grounds of research in the field of symbolic Artificial Intelligence systems, applied to the new Knowledge Management Systems. The basic feature of these systems is represented by the processing of the fuzzy knowledge involved in the synthesis of some decisions. The work reported in this paper serves to promote an Intelligent System that can operate in dynamic and uncertain environments based on a formal definition of an expert system. We can develop and justify thus a series of modelling and design techniques for Intelligent Knowledge Management Systems (IKMS, as well as methods for the analysis of expert systems performance, and, of a fuzzy expert system in particular, between which there are strong similarities. We will also outline a number of differences between conventional problem solving systems and IKMS, the links between expert systems and those of structural and functional planning, the analogy between the model of the problem or business process and the problem domain.

  17. Expert system aided operator's mental activities training

    International Nuclear Information System (INIS)

    Gieci, A.; Macko, J.; Mosny, J.; Gese, A.

    1994-01-01

    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). 6 refs, 6 figs

  18. An expert system in medical diagnosis

    International Nuclear Information System (INIS)

    Raboanary, R.; Raoelina Andriambololona; Soffer, J.; Raboanary, J.

    2001-01-01

    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 XX t . 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.

  19. An expert system for diesel generator diagnostics

    International Nuclear Information System (INIS)

    Bley, D.C.; Read, J.W.; Kaplan, S.; Liming, J.K.; Brosee, N.M.; Hanley, D.W.

    1987-01-01

    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

  20. ROSIE: A Programming Environment for Expert Systems

    Science.gov (United States)

    1985-10-01

    ence on Artificial Inteligence , Tbilisi, USSR, 1975. Fain, J., D. Gorlin, F. Hayes-Roth, S. Rosenschein, H. Sowizral, and D. Waterman, The ROSIE Language...gramming environment for artificial intelligence (AI) applications. It provides particular support for designing expert systems, systems that embody

  1. Expert system support and juridical quality

    NARCIS (Netherlands)

    Groothuis, Marga M.; Svensson, Jorgen S.; Breuker, J.; Leenes, R.E.; Winkels, R.

    2000-01-01

    This article discusses the use of expert systems as a means of achieving juridical quality within administrative organisations. Do these systems really improve the quality of decision making and provide the desired guarantees with respect to the correct treatment of clients?

  2. Visual Cues for an Adaptive Expert System.

    Science.gov (United States)

    Miller, Helen B.

    NCR (National Cash Register) Corporation is pursuing opportunities to make their point of sale (POS) terminals easy to use and easy to learn. To approach the goal of making the technology invisible to the user, NCR has developed an adaptive expert prototype system for a department store POS operation. The structure for the adaptive system, the…

  3. Fuzzy Backstepping Sliding Mode Control for Mismatched Uncertain System

    Directory of Open Access Journals (Sweden)

    H. Q. Hou

    2014-06-01

    Full Text Available Sliding mode controllers have succeeded in many control problems that the conventional control theories have difficulties to deal with; however it is practically impossible to achieve high-speed switching control. Therefore, in this paper an adaptive fuzzy backstepping sliding mode control scheme is derived for mismatched uncertain systems. Firstly fuzzy sliding mode controller is designed using backstepping method based on the Lyapunov function approach, which is capable of handling mismatched problem. Then fuzzy sliding mode controller is designed using T-S fuzzy model method, it can improve the performance of the control systems and their robustness. Finally this method of control is applied to nonlinear system as a case study; simulation results are also provided the performance of the proposed controller.

  4. Fuzzy systems and soft computing in nuclear engineering

    International Nuclear Information System (INIS)

    Ruan, D.

    2000-01-01

    This book is an organized edited collection of twenty-one contributed chapters covering nuclear engineering applications of fuzzy systems, neural networks, genetic algorithms and other soft computing techniques. All chapters are either updated review or original contributions by leading researchers written exclusively for this volume. The volume highlights the advantages of applying fuzzy systems and soft computing in nuclear engineering, which can be viewed as complementary to traditional methods. As a result, fuzzy sets and soft computing provide a powerful tool for solving intricate problems pertaining in nuclear engineering. Each chapter of the book is self-contained and also indicates the future research direction on this topic of applications of fuzzy systems and soft computing in nuclear engineering. (orig.)

  5. Spacecraft command and control using expert systems

    Science.gov (United States)

    Norcross, Scott; Grieser, William H.

    1994-01-01

    This paper describes a product called the Intelligent Mission Toolkit (IMT), which was created to meet the changing demands of the spacecraft command and control market. IMT is a command and control system built upon an expert system. Its primary functions are to send commands to the spacecraft and process telemetry data received from the spacecraft. It also controls the ground equipment used to support the system, such as encryption gear, and telemetry front-end equipment. Add-on modules allow IMT to control antennas and antenna interface equipment. The design philosophy for IMT is to utilize available commercial products wherever possible. IMT utilizes Gensym's G2 Real-time Expert System as the core of the system. G2 is responsible for overall system control, spacecraft commanding control, and spacecraft telemetry analysis and display. Other commercial products incorporated into IMT include the SYBASE relational database management system and Loral Test and Integration Systems' System 500 for telemetry front-end processing.

  6. A fuzzy logic pitch angle controller for power system stabilization

    Energy Technology Data Exchange (ETDEWEB)

    Jauch, Clemens; Cronin, Tom; Sorensen, Poul [Wind Energy Department, Riso National Laboratory, PO Box 49, DK-4000 Roskilde, (Denmark); Jensen, Birgitte Bak [Institute of Energy Technology, Aalborg University, Pontoppidanstraede 101, DK-9220 Aalborg East, (Denmark)

    2006-07-12

    In this article the design of a fuzzy logic pitch angle controller for a fixed speed, active-stall wind turbine, which is used for power system stabilization, is presented. The system to be controlled, which is the wind turbine and the power system to which the turbine is connected, is described. The advantages of fuzzy logic control when applied to large-signal control of active-stall wind turbines are outlined. The general steps of the design process for a fuzzy logic controller, including definition of the controller inputs, set-up of the fuzzy rules and the method of defuzzification, are described. The performance of the controller is assessed by simulation, where the wind turbine's task is to dampen power system oscillations. In the scenario simulated for this work, the wind turbine has to ride through a transient short-circuit fault and subsequently contribute to the damping of the grid frequency oscillations that are caused by the transient fault. It is concluded that the fuzzy logic controller enables the wind turbine to dampen power system oscillations. It is also concluded that, owing to the inherent non-linearities in a wind turbine and the unpredictability of the whole system, the fuzzy logic controller is very suitable for this application. (Author).

  7. Temporal logics and real time expert systems.

    Science.gov (United States)

    Blom, J A

    1996-10-01

    This paper introduces temporal logics. Due to the eternal compromise between expressive adequacy and reasoning efficiency that must decided upon in any application, full (first order logic or modal logic based) temporal logics are frequently not suitable. This is especially true in real time expert systems, where a fixed (and usually small) response time must be guaranteed. One such expert system, Fagan's VM, is reviewed, and a delineation is given of how to formally describe and reason with time in medical protocols. It is shown that Petri net theory is a useful tool to check the correctness of formalised protocols.

  8. Expert System Software Assistant for Payload Operations

    Science.gov (United States)

    Rogers, Mark N.

    1997-01-01

    The broad objective of this expert system software based application was to demonstrate the enhancements and cost savings that can be achieved through expert system software utilization in a spacecraft ground control center. Spacelab provided a valuable proving ground for this advanced software technology; a technology that will be exploited and expanded for future ISS operations. Our specific focus was on demonstrating payload cadre command and control efficiency improvements through the use of "smart" software which monitors flight telemetry, provides enhanced schematic-based data visualization, and performs advanced engineering data analysis.

  9. AN EXPERT SYSTEM USED IN DESIGN

    Directory of Open Access Journals (Sweden)

    Hüdayim BAŞAK

    2001-03-01

    Full Text Available In this work, an expert system used in computer aided design has been developed. In the developed program, the features which are used in the models prepared by a feature based design program are evaluated by the expert system module and are used in part modeling after determining of their compatibilty according to the rules. This program, particulary for those who do not know or know very little manufacturing stages, accomplishes the duty of informing and directing them. The program developed warns the user for design mistakes made during modeling.

  10. Assessing experience in the deliberate practice of running using a fuzzy decision-support system.

    Directory of Open Access Journals (Sweden)

    Maria Isabel Roveri

    Full Text Available The judgement of skill experience and its levels is ambiguous though it is crucial for decision-making in sport sciences studies. We developed a fuzzy decision support system to classify experience of non-elite distance runners. Two Mamdani subsystems were developed based on expert running coaches' knowledge. In the first subsystem, the linguistic variables of training frequency and volume were combined and the output defined the quality of running practice. The second subsystem yielded the level of running experience from the combination of the first subsystem output with the number of competitions and practice time. The model results were highly consistent with the judgment of three expert running coaches (r>0.88, p0.86, p<0.001. From the expert's knowledge and the fuzzy model, running experience is beyond the so-called "10-year rule" and depends not only on practice time, but on the quality of practice (training volume and frequency and participation in competitions. The fuzzy rule-based model was very reliable, valid, deals with the marked ambiguities inherent in the judgment of experience and has potential applications in research, sports training, and clinical settings.

  11. Uncertain rule-based fuzzy systems introduction and new directions

    CERN Document Server

    Mendel, Jerry M

    2017-01-01

    The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy se...

  12. Possibility-based robust design optimization for the structural-acoustic system with fuzzy parameters

    Science.gov (United States)

    Yin, Hui; Yu, Dejie; Yin, Shengwen; Xia, Baizhan

    2018-03-01

    The conventional engineering optimization problems considering uncertainties are based on the probabilistic model. However, the probabilistic model may be unavailable because of the lack of sufficient objective information to construct the precise probability distribution of uncertainties. This paper proposes a possibility-based robust design optimization (PBRDO) framework for the uncertain structural-acoustic system based on the fuzzy set model, which can be constructed by expert opinions. The objective of robust design is to optimize the expectation and variability of system performance with respect to uncertainties simultaneously. In the proposed PBRDO, the entropy of the fuzzy system response is used as the variability index; the weighted sum of the entropy and expectation of the fuzzy response is used as the objective function, and the constraints are established in the possibility context. The computations for the constraints and objective function of PBRDO are a triple-loop and a double-loop nested problem, respectively, whose computational costs are considerable. To improve the computational efficiency, the target performance approach is introduced to transform the calculation of the constraints into a double-loop nested problem. To further improve the computational efficiency, a Chebyshev fuzzy method (CFM) based on the Chebyshev polynomials is proposed to estimate the objective function, and the Chebyshev interval method (CIM) is introduced to estimate the constraints, thereby the optimization problem is transformed into a single-loop one. Numerical results on a shell structural-acoustic system verify the effectiveness and feasibility of the proposed methods.

  13. EXPERT SYSTEMS - DEVELOPMENT OF AGRICULTURAL INSURANCE TOOL

    Directory of Open Access Journals (Sweden)

    NAN Anca-Petruţa

    2013-07-01

    Full Text Available Because of the fact that specialty agricultural assistance is not always available when the farmers need it, we identified expert systems as a strong instrument with an extended potential in agriculture. This started to grow in scale recently, including all socially-economic activity fields, having the role of collecting data regarding different aspects from human experts with the purpose of assisting the user in the necessary steps for solving problems, at the performance level of the expert, making his acquired knowledge and experience available. We opted for a general presentation of the expert systems as well as their necessity, because, the solution to develop the agricultural system can come from artificial intelligence by implementing the expert systems in the field of agricultural insurance, promoting existing insurance products, farmers finding options in depending on their necessities and possibilities. The objective of this article consists of collecting data about different aspects about specific areas of interest of agricultural insurance, preparing the database, a conceptual presentation of a pilot version which will become constantly richer depending on the answers received from agricultural producers, with the clearest exposure of knowledgebase possible. We can justify picking this theme with the fact that even while agricultural insurance plays a very important role in agricultural development, the registered result got from them are modest, reason why solutions need to be found in the scope of developing the agricultural sector. The importance of this consists in the proposal of an immediate viable solution to correspond with the current necessities of agricultural producers and in the proposal of an innovative solution, namely the implementation of expert system in agricultural insurance as a way of promoting insurance products. Our research, even though it treats the subject at an conceptual level, it wants to undertake an

  14. Expert system for transuranic waste assay

    Energy Technology Data Exchange (ETDEWEB)

    Zoolalian, M.L.; Gibbs, A.; Kuhns, J.D.

    1989-01-01

    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.

  15. Expert system for transuranic waste assay

    International Nuclear Information System (INIS)

    Zoolalian, M.L.; Gibbs, A.; Kuhns, J.D.

    1989-01-01

    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

  16. Advances in type-2 fuzzy sets and systems theory and applications

    CERN Document Server

    Mendel, Jerry; Tahayori, Hooman

    2013-01-01

    This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet.  The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.

  17. Range of expert system for control, modeling and safely operation in nuclear energy

    International Nuclear Information System (INIS)

    Gorlin, A.; Semenov, S.

    1990-01-01

    The paper describes expert system projects which had been developed formerly and are under the development now in NVIIAES Institute, Moscow. One of the accomplished systems (PEX) is a ES-shell of classical type able to manipulate fuzzy expert assessments. The system is used as a shell for ES-advisor for MCP failures diagnostics and in some applications of the same sort. Another realized system (EDES) is on-line express-diagnostical ES for NPP unit emergency regimes identification. EDES is implemented now as a component of NPP system of control and operation conditions diagnostics. Both systems are realized on conventional programming languages Pascal and C, respectively. The presentation describes current developments in ES as well, including classification system for material researches, the project of training ES for second circuit diagnostics based on event tree generating and expert planner for neutron-physical three-dimensional reactor calculations. All this projects are implemented on different versions of PROLOG programming language

  18. STUDENT PREDICTION SYSTEM FOR PLACEMENT TRAINING USING FUZZY INFERENCE SYSTEM

    Directory of Open Access Journals (Sweden)

    Ravi Kumar Rathore

    2017-04-01

    Full Text Available Proposed student prediction system is most vital approach which may be used to differentiate the student data/information on the basis of the student performance. Managing placement and training records in any larger organization is quite difficult as the student number are high; in such condition differentiation and classification on different categories becomes tedious. Proposed fuzzy inference system will classify the student data with ease and will be helpful to many educational organizations. There are lots of classification algorithms and statistical base technique which may be taken as good assets for classify the student data set in the education field. In this paper, Fuzzy Inference system has been applied to predict student performance which will help to identify performance of the students and also provides an opportunity to improve to performance. For instance, here we will classify the student’s data set for placement and non-placement classes.

  19. REXS : A financial risk diagnostic expert system

    Directory of Open Access Journals (Sweden)

    W. Richter

    2012-01-01

    Full Text Available

    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

  20. A fuzzy intelligent system for land consolidation - a case study in Shunde, China

    Science.gov (United States)

    Wang, J.; Ge, A.; Hu, Y.; Li, C.; Wang, L.

    2015-04-01

    Traditionally, potential evaluation methods for farmland consolidation have depended mainly on the experts' experiences, statistical computations or subjective adjustments. Some biases usually exist in the results. Thus, computer-aided technology has become essential. In this study, an intelligent evaluation system based on a fuzzy decision tree was established, and this system can deal with numerical data, discrete data and symbolic data. When the original land data are input, the level of potential of the agricultural land for development will be output by this new model. The provision of objective proof for decision making by authorities in rural management is helpful. Agricultural land data characteristically comprise large volumes, complex varieties and more indexes. In land consolidation, it is very important to construct an effective index system. We needed to select a group of indexes useful for land consolidation according to the concrete demand. In this paper, a fuzzy measure, which can describe the importance of a single feature or a group of features, is adopted to accomplish the selection of specific features. A fuzzy integral that is based on a fuzzy measure is a type of fusion tool. We obtained the optimal solution for a fuzzy measure by solving a fuzzy integral. The fuzzy integrals can be transformed to a set of linear equations. We applied the L1-norm regularization method to solve the linear equations, and we found a solution with the fewest nonzero elements for the fuzzy measure; this solution shows the contribution of corresponding features or the combinations of decisions. This algorithm provides a quick and optimal way to identify the land index system when preparing to conduct the research, such as we describe herein, on land consolidation. Shunde's "Three Old" consolidation project provides the data for this work. Our estimation system was compared with a conventional evaluation system that is still accepted by the public. Our results prove

  1. Diagnosis Penyakit Jantung Menggunakan Adaptive Neuro-Fuzzy Inference System (ANFIS

    Directory of Open Access Journals (Sweden)

    Khadijah Fahmi Hayati Holle

    2016-09-01

    Full Text Available The number of uncertain risk factor in heart disease makes experts difficult to diagnose its disease. Computer technology in the health field is mostly used. In this paper, we implement a system to diagnose heart disease. The used method is Adaptive neuro-fuzzy inference system which combine the advantage of fuzzy and neural network. The used data is UCI Cleveland data that have 13 attributes as inputs. Output system diagnosis compared with observational data for evaluation. System performance tested by calculating accuracy. Tests were also conducted on the variation of the learning rate, iteration, minimum error, and the use of membership functions. Accuracy obtained from test is 65,657% where using membership function Beta.

  2. Industrial disasters - the expert systems solution

    International Nuclear Information System (INIS)

    Sachs, P.

    1986-01-01

    Six mistakes by the operators led to the accident at the Cherobyl nuclear reactor. These have been studied. It is suggested that an expert systems approach could prevent similar accidents. The expert system is a new approach to software programming where programs are required to perform intelligent analyses of complex situations. It separates the knowledge of a problem from the procedural code that performs the decision. An expert system will evaluate data and indicate a priority on alarms in real time. Now software systems can detect the cause of a problem in a process plant and present their findings to the operators in the control room. This should enable operators to make the correct decisions as they will know which underlying process faults are causing the alarms to operate. The Chernobyl post-mortem meeting made 13 proposals for improving safety. Two in particular are noted as relevant to expert advice systems; international collaboration on man-reactor relationships and a conference to explore the balance of automation and human action to minimise operating errors. (U.K.)

  3. Simulation Study of IMC and Fuzzy Controller for HVAC System

    Directory of Open Access Journals (Sweden)

    Umamaheshwari

    2009-06-01

    Full Text Available This paper presents how the fuzzy logic controller is used to solve the control problems of complex and non linear process and show that it is more robust and their performance are less sensitive to parametric variations than conventional controllers. These systems will yield a linear response when compared to ordinary controllers. The main advantage of Fuzzy control over conventional controllers is regulation can be done without over shoot.

  4. Energy Analysis for Air Conditioning System Using Fuzzy Logic Control

    Directory of Open Access Journals (Sweden)

    Henry Nasution

    2011-04-01

    Full Text Available Reducing energy consumption and to ensure thermal comfort are two important considerations for the designing an air conditioning system. An alternative approach to reduce energy consumption proposed in this study is to use a variable speed compressor. The control strategy will be proposed using the fuzzy logic controller (FLC. FLC was developed to imitate the performance of human expert operators by encoding their knowledge in the form of linguistic rules. The system is installed on a thermal environmental room with a data acquisition system to monitor the temperature of the room, coefficient of performance (COP, energy consumption and energy saving. The measurements taken during the two hour experimental periods at 5-minutes interval times for temperature setpoints of 20oC, 22oC and 24oC with internal heat loads 0, 500, 700 and 1000 W. The experimental results indicate that the proposed technique can save energy in comparison with On/Off and proportional-integral-derivative (PID control.

  5. EXPERT SYSTEMS SHOW PROMISE FOR CUSTOMER INQUIRIES

    Science.gov (United States)

    This article describes results of an agreement between the North Penn Water Authority in Lansdale, Pa., and the US Environmental Protection Agency, Drinking Water Research Division, Cincinnati, Ohio, to study use of expert systems technology in a water utility. The threeyear stud...

  6. Using Expert Systems To Build Cognitive Simulations.

    Science.gov (United States)

    Jonassen, David H.; Wang, Sherwood

    2003-01-01

    Cognitive simulations are runnable computer programs for modeling human cognitive activities. A case study is reported where expert systems were used as a formalism for modeling metacognitive processes in a seminar. Building cognitive simulations engages intensive introspection, ownership and meaning making in learners who build them. (Author/AEF)

  7. Laserjet Printer Troubleshooting Expert System | Adesola | West ...

    African Journals Online (AJOL)

    This paper model an expert system called LAPTEX for troubleshooting LaserJet printers' faults. Today, with the innumerable advances in information technologies, computerizing printer's fault troubleshooting and identifying faults is far becoming so vital. Also, printers' fault detection is a complicated process that requires a ...

  8. Knowledge representation and use. I. Expert systems

    Energy Technology Data Exchange (ETDEWEB)

    Lauriere, J L

    1982-01-01

    Expert systems are designed as aids in human reasoning in various specific areas. Symbolic knowledge manipulation, uncertain and incomplete deduction capabilities, natural communication with humans in non-procedural ways are their essential features. The paper describes their design and several implementations. 105 references.

  9. Expert System Model for Educational Personnel Selection

    Directory of Open Access Journals (Sweden)

    Héctor A. Tabares-Ospina

    2013-06-01

    Full Text Available The staff selection is a difficult task due to the subjectivity that the evaluation means. This process can be complemented using a system to support decision. This paper presents the implementation of an expert system to systematize the selection process of professors. The management of software development is divided into 4 parts: requirements, design, implementation and commissioning. The proposed system models a specific knowledge through relationships between variables evidence and objective.

  10. 3D images and expert system

    International Nuclear Information System (INIS)

    Hasegawa, Jun-ichi

    1998-01-01

    This paper presents an expert system called 3D-IMPRESS for supporting applications of three dimensional (3D) image processing. This system can automatically construct a 3D image processing procedure based on a pictorial example of the goal given by a user. In the paper, to evaluate the performance of the system, it was applied to construction of procedures for extracting specific component figures from practical chest X-ray CT images. (author)

  11. Make man-machine communication easier: fuzzy programming

    Energy Technology Data Exchange (ETDEWEB)

    Farreny, H; Prade, H

    1982-06-01

    Procedures and data used by the human brain are not always accurately specified; fuzzy programming may help in the realisation of languages for the manipulation of such fuzzy entities. After having considered fuzzy instruction and its requirements, arguments, functions, predicates and designations, the authors present the outlines of a fuzzy filtering system. Two applications are given as examples; these are the accessing of a database and an expert system which may be used to solve problems in robotics.

  12. Disturbance attenuation of nonlinear control systems using an observer-based fuzzy feedback linearization control

    International Nuclear Information System (INIS)

    Chen, C.-C.; Hsu, C.-H.; Chen, Y.-J.; Lin, Y.-F.

    2007-01-01

    The almost disturbance decoupling and trajectory tracking of nonlinear control systems using an observer-based fuzzy feedback linearization control (FLC) is developed. Because not all of the state variables of the nonlinear dynamic equations are available, a nonlinear state observer is employed to estimate the state variables. The feedback linearization control guarantees the almost disturbance decoupling performance and the uniform ultimate bounded stability of the tracking error system. Once the tracking errors are driven to touch the global final attractor with the desired radius, the fuzzy logic control is immediately applied via human expert's knowledge to improve the convergence rate. One example, which cannot be solved by the first paper on the almost disturbance decoupling problem, is proposed in this paper to exploit the fact that the tracking and the almost disturbance decoupling performances are easily achieved by our proposed approach. In order to demonstrate the practical applicability, the study has investigated a pendulum control system

  13. Enhanced Decision Support Systems in Intensive Care Unit Based on Intuitionistic Fuzzy Sets

    Directory of Open Access Journals (Sweden)

    Hanen Jemal

    2017-01-01

    Full Text Available In areas of medical diagnosis and decision-making, several uncertainty and ambiguity shrouded situations are most often imposed. In this regard, one may well assume that intuitionistic fuzzy sets (IFS should stand as a potent technique useful for demystifying associated with the real healthcare decision-making situations. To this end, we are developing a prototype model helpful for detecting the patients risk degree in Intensive Care Unit (ICU. Based on the intuitionistic fuzzy sets, dubbed Medical Intuitionistic Fuzzy Expert Decision Support System (MIFEDSS, the shown work has its origins in the Modified Early Warning Score (MEWS standard. It is worth noting that the proposed prototype effectiveness validation is associated through a real case study test at the Polyclinic ESSALEMA cited in Sfax, Tunisia. This paper does actually provide some practical initial results concerning the system as carried out in real life situations. Indeed, the proposed system turns out to prove that the MIFEDSS does actually display an imposing capability for an established handily ICU related uncertainty issues. The performance of the prototypes is compared with the MEWS standard which exposed that the IFS application appears to perform highly better in deferring accuracy than the expert MEWS score with higher degrees of sensitivity and specificity being recorded.

  14. An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination.

    Science.gov (United States)

    Kuo, R J; Wu, P; Wang, C P

    2002-09-01

    Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.

  15. Management of Uncertainty by Statistical Process Control and a Genetic Tuned Fuzzy System

    Directory of Open Access Journals (Sweden)

    Stephan Birle

    2016-01-01

    Full Text Available In food industry, bioprocesses like fermentation often are a crucial part of the manufacturing process and decisive for the final product quality. In general, they are characterized by highly nonlinear dynamics and uncertainties that make it difficult to control these processes by the use of traditional control techniques. In this context, fuzzy logic controllers offer quite a straightforward way to control processes that are affected by nonlinear behavior and uncertain process knowledge. However, in order to maintain process safety and product quality it is necessary to specify the controller performance and to tune the controller parameters. In this work, an approach is presented to establish an intelligent control system for oxidoreductive yeast propagation as a representative process biased by the aforementioned uncertainties. The presented approach is based on statistical process control and fuzzy logic feedback control. As the cognitive uncertainty among different experts about the limits that define the control performance as still acceptable may differ a lot, a data-driven design method is performed. Based upon a historic data pool statistical process corridors are derived for the controller inputs control error and change in control error. This approach follows the hypothesis that if the control performance criteria stay within predefined statistical boundaries, the final process state meets the required quality definition. In order to keep the process on its optimal growth trajectory (model based reference trajectory a fuzzy logic controller is used that alternates the process temperature. Additionally, in order to stay within the process corridors, a genetic algorithm was applied to tune the input and output fuzzy sets of a preliminarily parameterized fuzzy controller. The presented experimental results show that the genetic tuned fuzzy controller is able to keep the process within its allowed limits. The average absolute error to the

  16. Fuzzy Logic Temperature Control System For The Induction Furnace

    Directory of Open Access Journals (Sweden)

    Lei Lei Hnin

    2015-08-01

    Full Text Available This research paper describes the fuzzy logic temperature control system of the induction furnace. Temperature requirement of the heating system varies during the heating process. In the conventional control schemes the switching losses increase with the change in the load. A closed loop control is required to have a smooth control on the system. In this system pulse width modulation based power control scheme for the induction heating system is developed using the fuzzy logic controller. The induction furnace requires a good voltage regulation to have efficient response. The controller controls the temperature depending upon weight of meat water and time. This control system is implemented in hardware system using microcontroller. Here the fuzzy logic controller is designed and simulated in MATLAB to get the desire condition.

  17. Development of nickel hydrogen battery expert system

    Science.gov (United States)

    Shiva, Sajjan G.

    1990-01-01

    The Hubble Telescope Battery Testbed employs the nickel-cadmium battery expert system (NICBES-2) which supports the evaluation of performances of Hubble Telescope spacecraft batteries and provides alarm diagnosis and action advice. NICBES-2 also provides a reasoning system along with a battery domain knowledge base to achieve this battery health management function. An effort to modify NICBES-2 to accommodate nickel-hydrogen battery environment in testbed is described.

  18. Diagnostic expert system in the PF LINAC

    International Nuclear Information System (INIS)

    Abe, Isamu; Nakahara, Kazuo; Kitamura, Masaharu.

    1992-01-01

    A prototype diagnostic expert system (ES) was developed for the Photon Factory 2.5-GeV electron/positron LINAC injector system. The ES has been on-lined with the conventional linac computer network for receiving real data. This project was undertaken in an attempt to reduce the linac operator's mental workload, diagnosis duties, and to explore Artificial Intelligence (AI) technologies. The outlook for ES and its problems, and what has been achieved are outlined in this presentation. (author)

  19. Developing a multipurpose sun tracking system using fuzzy control

    Energy Technology Data Exchange (ETDEWEB)

    Alata, Mohanad [Department of Mechanical Engineering, Jordan University of Science and Technology (JUST), PO Box 3030, Irbid 22110 (Jordan)]. E-mail: alata@just.edu.jo; Al-Nimr, M.A. [Department of Mechanical Engineering, Jordan University of Science and Technology (JUST), PO Box 3030, Irbid 22110 (Jordan); Qaroush, Yousef [Department of Mechanical Engineering, Jordan University of Science and Technology (JUST), PO Box 3030, Irbid 22110 (Jordan)

    2005-05-01

    The present work demonstrates the design and simulation of time controlled step sun tracking systems that include: one axis sun tracking with the tilted aperture equal to the latitude angle, equatorial two axis sun tracking and azimuth/elevation sun tracking. The first order Sugeno fuzzy inference system is utilized for modeling and controller design. In addition, an estimation of the insolation incident on a two axis sun tracking system is determined by fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm, along with least square estimation (LSE), generates the fuzzy rules that describe the relationship between the input/output data of solar angles that change with time. The fuzzy rules are tuned by an adaptive neuro-fuzzy inference system (ANFIS). Finally, an open loop control system is designed for each of the previous types of sun tracking systems. The results are shown using simulation and virtual reality. The site of application is chosen at Amman, Jordan (32 deg. North, 36 deg. East), and the period of controlling and simulating each type of tracking system is the year 2003.

  20. WWW expert system on producer gas cleaning

    Energy Technology Data Exchange (ETDEWEB)

    Schouten, E.J.; Lammers, G.; Beenackers, A.A.C.M. [University of Groningen (Netherlands)

    1999-07-01

    The University of Groningen (RUG) has developed an expert system on cleaning of biomass producer gas. This work was carried out in close co-operation with the Biomass Technology Group B.V. (BTG) in Enschede, The Netherlands within the framework of the EC supported JOR3-CT95-0084 project. The expert system was developed as a tool for the designer-engineer of downstream gas cleaning equipment and consists of an information package and a flowsheet package. The packages are integrated in a client/server system. The flowsheeting package of the expert system has been designed for the evaluation of different gas cleaning methods. The system contains a number of possible gas cleaning devices such as: cyclone, fabric filter, ceramic filter, venturi scrubber and catalytic cracker. The user can select up to five cleaning steps in an arbitrary order for his specific gas cleaning problem. After specification of the required design parameters, the system calculates the main design characteristics of the cleaning device. The information package is a collection of HTML{sup TM} files. It contains a large amount of information, tips, experience data, literature references and hyperlinks to other interesting Internet sites. This information is arranged per cleaning device. (orig.)

  1. The vulcain N expert fire system

    International Nuclear Information System (INIS)

    Roche, A.

    1989-03-01

    The Institute for Nuclear Safety and Protection (IPSN) has begun work on an expert system to aid in the diagnosis of fire hazards in nuclear installations. This system is called Vulcain N and is designed as a support tool for the analyses carried out by the IPSN. Vulcain N, is based on the Vulcain expert system already developed by Bertin for its own needs and incorporates the specific rules and know-how of the IPSN experts. The development of Vulcain N began in October 1986 with the drawing up of the technical specifications, and should be completed by the end of 1988. Vulcain N brings together knowledge from a number of different domains: the locations of the combustible materials, the thermal characteristics of the combustible materials and of the walls of the room, the ventilation conditions and, finally, knowledge of fire experts concerning the development of fire. The latter covers four levels of expert knowledge: standards and their associated calculations, the simplified physics of the fire enabling more precise values to be obtained for the figures given by the standards, the rules and knowledge which enables a certain number of deductions to be made concerning the development of the fire, and a numerical simulation code which can be used to monitor the variation of certain characteristic parameters with time. For a given fire out-break scenario, Vulcain N performs diagnosis of different aspects: development of fire, effect of ventilation, emergency action possibilities, propagation hazards, etc. Owing to its flexibility, it can be used in the analysis of fire hazards to simulate a number of possible scenarios and to very rapidly deduce the essential, predominant factors. It will also be used to assist in drafting emergency procedures for application in facilities with nuclear hazards

  2. Fuzzy combination of fuzzy and switching state-feedback controllers for nonlinear systems subject to parameter uncertainties.

    Science.gov (United States)

    Lam, H K; Leung, Frank H F

    2005-04-01

    This paper presents a fuzzy controller, which involves a fuzzy combination of local fuzzy and global switching state-feedback controllers, for nonlinear systems subject to parameter uncertainties with known bounds. The nonlinear system is represented by a fuzzy combined Takagi-Sugeno-Kang model, which is a fuzzy combination of the global and local fuzzy plant models. By combining the local fuzzy and global switching state-feedback controllers using fuzzy logic techniques, the advantages of both controllers can be retained and the undesirable chattering effect introduced by the global switching state-feedback controller can be eliminated. The steady-state error introduced by the global switching state-feedback controller when a saturation function is used can also be removed. Stability conditions, which are related to the system matrices of the local and global closed-loop systems, are derived to guarantee the closed-loop system stability. An application example will be given to demonstrate the merits of the proposed approach.

  3. Intelligent control-III: fuzzy control system

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    During the last decade or so, fuzzy logic control (FLC) has emerged as one of the most active and fruitful areas of research and development. The applications include industrial process control to medical diagnostic and financial markets. Many consumer products using this technology are available in the market place. FLC is best suited to complex ill-defined processes that can be controlled by a skilled human operator without much knowledge of their underlying dynamics. This lecture will cover the basic architecture and the design methodology of fuzzy logic controllers. FLC will be strongly based on the concepts of fuzzy set theory, introduced in first lecture. Some practical applications will also be discussed and presented. (author)

  4. Fuzzy Controllers for a Gantry Crane System with Experimental Verifications

    Directory of Open Access Journals (Sweden)

    Naif B. Almutairi

    2016-01-01

    Full Text Available The control problem of gantry cranes has attracted the attention of many researchers because of the various applications of these cranes in the industry. In this paper we propose two fuzzy controllers to control the position of the cart of a gantry crane while suppressing the swing angle of the payload. Firstly, we propose a dual PD fuzzy controller where the parameters of each PD controller change as the cart moves toward its desired position, while maintaining a small swing angle of the payload. This controller uses two fuzzy subsystems. Then, we propose a fuzzy controller which is based on heuristics. The rules of this controller are obtained taking into account the knowledge of an experienced crane operator. This controller is unique in that it uses only one fuzzy system to achieve the control objective. The validity of the designed controllers is tested through extensive MATLAB simulations as well as experimental results on a laboratory gantry crane apparatus. The simulation results as well as the experimental results indicate that the proposed fuzzy controllers work well. Moreover, the simulation and the experimental results demonstrate the robustness of the proposed control schemes against output disturbances as well as against uncertainty in some of the parameters of the crane.

  5. Employing expert systems for process control

    International Nuclear Information System (INIS)

    Ahrens, W.

    1987-01-01

    The characteristic features of expert systems are explained in detail, and the systems' application in process control engineering. Four points of main interest are there, namely: Applications for diagnostic tasks, for safety analyses, planning, and training and expert training. For the modelling of the technical systems involved in all four task fields mentioned above, an object-centred approach has shown to be the suitable method, as process control techniques are determined by technical objects that in principle are specified by data sheets, schematic representations, flow charts, and plans. The graphical surface allows these data to be taken into account, so that the object can be displayed in the way best suited to the individual purposes. (orig./GL) [de

  6. THE MODEL OF UNCLEAR EXPERT SYSTEM OF PROGNOSTICATION THE CONTENT OF EDUCATION

    Directory of Open Access Journals (Sweden)

    Ivan M. Tsidylo

    2012-12-01

    Full Text Available The article deals with the problem of development of the expert system of prognostication of the educational content by means of fuzzy logic. It was the model of making decision by the group of experts in accordance to meaningfulness of the theme in the educational programme on the base of the hierarchical system that combines in itself the use of both unclear and stochastic data. The structure of the unclear system, function and mechanisms of construction of separate blocks of the model are described. The surface of review of the unclear system represents dependence of estimation of the theme meaningfulness on the level of competence of group of experts and size to the point at the permanent value of level’s variation. The testing of the controller on a test selection proves the functional fitness of the developed model.

  7. Expert systems for protective monitoring of facilities

    International Nuclear Information System (INIS)

    Carr, K.R.

    1987-01-01

    In complex plants, the possibility of serious operator error always exists to some extent, but, this can be especially true during an experiment or some other unusual exercise. Possible contributing factors to operational error include personnel fatigue, misunderstanding in communication, mistakes in executing orders, uncertainty about the delegated authority, pressure to meet a demanding schedule, and a lack of understanding of the possible consequences of deliberate violations of the facility's established operating procedures. Authoritative reports indicate that most of these factors were involved in the disastrous Russian Chernobyl-4 nuclear reactor accident in April 1986, which, ironically, occurred when a safety experiment was being conducted. Given the computer hardware and software now available for implementing expert systems together with integrated signal monitoring and communications, plant protection could be enhanced by an expert system with extended features to monitor the plant. The system could require information from the operators on a rigidly enforced schedule and automatically log in and report on a scheduled time basis to authorities at a central remote site during periods of safe operation. Additionally, the system could warn an operator or automatically shut down the plant in case of dangerous conditions, while simultaneously notifying independent, responsible, off-site personnel of the action taken. This approach would provide protection beyond that provided by typical facility scram circuits. This paper presents such an approach to implementing an expert system for plant protection, together with specific hardware and software configurations. The Chernobyl accident is used as the basis of discussion

  8. Paradigms and building tools for real-time expert systems

    International Nuclear Information System (INIS)

    Behrens, U.; Flasinski, M.; Hagge, L.; Ohrenberg, K.

    1994-01-01

    An expert system is a software which can simulate the problem solving behavior of a human expert. The rule-based paradigm is chosen to describe the different aspects involved in expert system development. Differences between expert systems and common procedural or object-oriented programs are investigated. Expert system shells are introduced as a building tool for expert systems, together with some guidelines on the evaluation of such shells. A discussion of special needs for real-time expert system development concludes the paper

  9. Expert Systems as a Mindtool To Facilitate Mental Model Learning.

    Science.gov (United States)

    Mason-Mason, Susan Dale; Tessmer, Martin A.

    2000-01-01

    This exploratory study investigated whether the process of constructing an expert system model promotes the formation of expert-like mental models. Discusses expert systems as mindtools, expert systems as learning tools, the assessment of mental models, results of pretests and posttests, and future research. (Contains 56 references.) (Author/LRW)

  10. Fuzzy logic based variable speed wind generation system

    Energy Technology Data Exchange (ETDEWEB)

    Simoes, M.G. [Sao Paulo Univ., SP (Brazil). Escola Politecnica. PMC - Mecatronica; Bose, B.K. [Tennessee Univ., Knoxville, TN (United States). Dept. of Electrical Engineering; Spiegel, Ronal J. [Environmental Protection Agency, Research Triangle Park, NC (United States). Air and Energy Engineering Research Lab.

    1996-12-31

    This work demonstrates the successful application of fuzzy logic to enhance the performance and control of a variable speed wind generation system. A maximum power point tracker control is performed with three fuzzy controllers, without wind velocity measurement, and robust to wind vortex and turbine torque ripple. A squirrel cage induction generator feeds the power to a double-sided PWM converter system which pumps the power to a utility grid or supplies to an autonomous system. The fuzzy logic controller FLC-1 searches on-line the generator speed so that the aerodynamic efficiency of the wind turbine is optimized. A second fuzzy controller FLC-2 programs the machine flux by on-line search so as to optimize the machine-converter system wind vortex. Detailed analysis and simulation studies were performed for development of the control strategy and fuzzy algorithms, and a DSP TMS320C30 based hardware with C control software was built for the performance evaluation of a laboratory experimental set-up. The theoretical development was fully validated and the system is ready to be reproduced in a higher power installation. (author) 7 refs., 3 figs., 1 tab.

  11. Evaluating Loans Using a Combination of Data Envelopment and Neuro-Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Rashmi Malhotra

    2015-02-01

    Full Text Available A business organization's objective is to make better decisions at all levels of the firm to improve performance. Typically organizations are multi-faceted and complex systems that use uncertain information. Therefore, making quality decisions to improve organizational performance is a daunting task. Organizations use decision support systems that apply different business intelligence techniques such as statistical models, scoring models, neural networks, expert systems, neuro-fuzzy systems, case-based systems, or simply rules that have been developed through experience. Managers need a decision-making approach that is robust, competent, effective, efficient, and integrative to handle the multi-dimensional organizational entities. The decision maker deals with multiple players in an organization such as products, customers, competitors, location, geographic structure, scope, internal organization, and cultural dimension [46]. Sound decisions include two important concepts: efficiency (return on invested resources and effectiveness (reaching predetermined goals. However, quite frequently, the decision maker cannot simultaneously handle data from different sources. Hence, we recommend that managers analyze different aspects of data from multiple sources separately and integrate the results of the analysis. This study proposes the design of a multi-attribute-decision-support-system that combines the analytical power of two different tools: data envelopment analysis (DEA and fuzzy logic. DEA evaluates and measures the relative efficiency of decision making units that use multiple inputs and outputs to provide non-objective measures without making any specific assumptions about data. On the other hand fuzzy logic's main strength lies in handling imprecise data. This study proposes a modeling technique that jointly uses the two techniques to benefit from the two methodologies. A major advantage of the DEA approach is that it clearly identifies the

  12. AUTOMATIC ROAD GAP DETECTION USING FUZZY INFERENCE SYSTEM

    Directory of Open Access Journals (Sweden)

    S. Hashemi

    2012-09-01

    Full Text Available Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1 Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2 Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3 Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4 Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

  13. Automatic Road Gap Detection Using Fuzzy Inference System

    Science.gov (United States)

    Hashemi, S.; Valadan Zoej, M. J.; Mokhtarzadeh, M.

    2011-09-01

    Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1) Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2) Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3) Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4) Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

  14. Steam Generator Inspection Planning Expert System

    International Nuclear Information System (INIS)

    Rzasa, P.

    1987-01-01

    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

  15. Row Reduced Echelon Form for Solving Fully Fuzzy System with Unknown Coefficients

    Directory of Open Access Journals (Sweden)

    Ghassan Malkawi

    2014-08-01

    Full Text Available This study proposes a new method for finding a feasible fuzzy solution in positive Fully Fuzzy Linear System (FFLS, where the coefficients are unknown. The fully fuzzy system is transferred to linear system in order to obtain the solution using row reduced echelon form, thereafter; the crisp solution is restricted in obtaining the positive fuzzy solution. The fuzzy solution of FFLS is included crisp intervals, to assign alternative values of unknown entries of fuzzy numbers. To illustrate the proposed method, numerical examples are solved, where the entries of coefficients are unknown in right or left hand side, to demonstrate the contributions in this study.

  16. The Expert Project Management System (EPMS)

    Science.gov (United States)

    Silverman, Barry G.; Diakite, Coty

    1986-01-01

    Successful project managers (PMs) have been shown to rely on 'intuition,' experience, and analogical reasoning heuristics. For new PMs to be trained and experienced PMs to avoid repeating others' mistakes, it is necessary to make the knowledge and heuristics of successful PMs more widely available. The preparers have evolved a model of PM thought processes over the last decade that is now ready to be implemented as a generic PM aid. This aid consists of a series of 'specialist' expert systems (CRITIC, LIBRARIAN, IDEA MAN, CRAFTSMAN, and WRITER) that communicate with each other via a 'blackboard' architecture. The various specialist expert systems are driven to support PM training and problem solving since any 'answers' they pass to the blackboard are subjected to conflict identification (AGENDA FORMULATOR) and GOAL SETTER inference engines.

  17. Artificial intelligence/expert (AI/EX) systems for steelworks pollution control

    Energy Technology Data Exchange (ETDEWEB)

    Schofield, N.; Le Louer, P.; Mirabile, D.; Hubner, R. [Corus UK Ltd., Rotherham (United Kingdom)

    2002-07-01

    The objectives of this project have been to develop and apply artificial intelligence and expert system (AI/EX) methods to improve the control and operational performance of steelworks' pollution control equipment and to assess the viability and benefits of using such systems in dynamic process plant applications. Four distinct sub-projects were carried out: an expert system incorporating knowledge-based rules and neural network simulations has been developed by Corus which provides plant personnel with a real-time condition monitoring tool for the plant. Abnormalities with plant operation are now instantly recognised and alarmed, allowing prioritised maintenance to increase plant availability. The LECES project focused on studies concerning three different sites in order to evaluate predictive emission monitoring systems using neural networks to replace conventional instrumental and controls in steelworks' combustion systems. VAI developed a software template for pollution control expert systems to demonstrate the transferability of AI/EX technology. This has been done through the development of a validated process database containing data from the Corus sub-project and the subsequent integration of this data with dynamic emission models to produce rules for input to an evaluation database. CSM developed a fuzzy logic controlled process management system applied to the biological treatment of coke-oven waste water. A pilot plant has been installed and results on simulations performed using the fuzzy logic system linked to a neural network simulator show that it is possible to obtain great advantages in the biological pilot plant performance.

  18. Expert system for designing the manufacturing conditions

    International Nuclear Information System (INIS)

    Henin, F.

    1990-01-01

    The expert system TOTEM (French acronym for Material and Time Optimal Processing), used in computer aided manufacturing, is presented. The flow chart describing the TOTEM operation principles is given. The calculation rules which allow the optimization of the fabrication means are summarized. The steps of the TOTEM operations and an application example are included. TOTEM allows the standardization of the manufacturing specifications and takes into account technological improvements [fr

  19. Planning bioinformatics workflows using an expert system

    Science.gov (United States)

    Chen, Xiaoling; Chang, Jeffrey T.

    2017-01-01

    Abstract Motivation: Bioinformatic analyses are becoming formidably more complex due to the increasing number of steps required to process the data, as well as the proliferation of methods that can be used in each step. To alleviate this difficulty, pipelines are commonly employed. However, pipelines are typically implemented to automate a specific analysis, and thus are difficult to use for exploratory analyses requiring systematic changes to the software or parameters used. Results: To automate the development of pipelines, we have investigated expert systems. We created the Bioinformatics ExperT SYstem (BETSY) that includes a knowledge base where the capabilities of bioinformatics software is explicitly and formally encoded. BETSY is a backwards-chaining rule-based expert system comprised of a data model that can capture the richness of biological data, and an inference engine that reasons on the knowledge base to produce workflows. Currently, the knowledge base is populated with rules to analyze microarray and next generation sequencing data. We evaluated BETSY and found that it could generate workflows that reproduce and go beyond previously published bioinformatics results. Finally, a meta-investigation of the workflows generated from the knowledge base produced a quantitative measure of the technical burden imposed by each step of bioinformatics analyses, revealing the large number of steps devoted to the pre-processing of data. In sum, an expert system approach can facilitate exploratory bioinformatic analysis by automating the development of workflows, a task that requires significant domain expertise. Availability and Implementation: https://github.com/jefftc/changlab Contact: jeffrey.t.chang@uth.tmc.edu PMID:28052928

  20. Assessing experience in the deliberate practice of running using a fuzzy decision-support system

    Science.gov (United States)

    Roveri, Maria Isabel; Manoel, Edison de Jesus; Onodera, Andrea Naomi; Ortega, Neli R. S.; Tessutti, Vitor Daniel; Vilela, Emerson; Evêncio, Nelson

    2017-01-01

    The judgement of skill experience and its levels is ambiguous though it is crucial for decision-making in sport sciences studies. We developed a fuzzy decision support system to classify experience of non-elite distance runners. Two Mamdani subsystems were developed based on expert running coaches’ knowledge. In the first subsystem, the linguistic variables of training frequency and volume were combined and the output defined the quality of running practice. The second subsystem yielded the level of running experience from the combination of the first subsystem output with the number of competitions and practice time. The model results were highly consistent with the judgment of three expert running coaches (r>0.88, p0.86, p<0.001). From the expert’s knowledge and the fuzzy model, running experience is beyond the so-called "10-year rule" and depends not only on practice time, but on the quality of practice (training volume and frequency) and participation in competitions. The fuzzy rule-based model was very reliable, valid, deals with the marked ambiguities inherent in the judgment of experience and has potential applications in research, sports training, and clinical settings. PMID:28817655

  1. Adaptive fuzzy controller based MPPT for photovoltaic systems

    International Nuclear Information System (INIS)

    Guenounou, Ouahib; Dahhou, Boutaib; Chabour, Ferhat

    2014-01-01

    Highlights: • We propose a fuzzy controller with adaptive output scaling factor as a maximum power point tracker of photovoltaic system. • The proposed controller integrates two different rule bases defined on error and change of error. • Our controller can track the maximum power point with better performances when compared to its conventional counterpart. - Abstract: This paper presents an intelligent approach to optimize the performances of photovoltaic systems. The system consists of a PV panel, a DC–DC boost converter, a maximum power point tracker controller and a resistive load. The key idea of the proposed approach is the use of a fuzzy controller with an adaptive gain as a maximum power point tracker. The proposed controller integrates two different rule bases. The first is used to adjust the duty cycle of the boost converter as in the case of a conventional fuzzy controller while the second rule base is designed for an online adjusting of the controller’s gain. The performances of the adaptive fuzzy controller are compared with those obtained using a conventional fuzzy controllers with different gains and in each case, the proposed controller outperforms its conventional counterpart

  2. Fuzzy multiobjective models for optimal operation of a hydropower system

    Science.gov (United States)

    Teegavarapu, Ramesh S. V.; Ferreira, André R.; Simonovic, Slobodan P.

    2013-06-01

    Optimal operation models for a hydropower system using new fuzzy multiobjective mathematical programming models are developed and evaluated in this study. The models use (i) mixed integer nonlinear programming (MINLP) with binary variables and (ii) integrate a new turbine unit commitment formulation along with water quality constraints used for evaluation of reservoir downstream impairment. Reardon method used in solution of genetic algorithm optimization problems forms the basis for development of a new fuzzy multiobjective hydropower system optimization model with creation of Reardon type fuzzy membership functions. The models are applied to a real-life hydropower reservoir system in Brazil. Genetic Algorithms (GAs) are used to (i) solve the optimization formulations to avoid computational intractability and combinatorial problems associated with binary variables in unit commitment, (ii) efficiently address Reardon method formulations, and (iii) deal with local optimal solutions obtained from the use of traditional gradient-based solvers. Decision maker's preferences are incorporated within fuzzy mathematical programming formulations to obtain compromise operating rules for a multiobjective reservoir operation problem dominated by conflicting goals of energy production, water quality and conservation releases. Results provide insight into compromise operation rules obtained using the new Reardon fuzzy multiobjective optimization framework and confirm its applicability to a variety of multiobjective water resources problems.

  3. ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR END MILLING

    Directory of Open Access Journals (Sweden)

    ANGELOS P. MARKOPOULOS

    2016-09-01

    Full Text Available Soft computing is commonly used as a modelling method in various technological areas. Methods such as Artificial Neural Networks and Fuzzy Logic have found application in manufacturing technology as well. NeuroFuzzy systems, aimed to combine the benefits of both the aforementioned Artificial Intelligence methods, are a subject of research lately as have proven to be superior compared to other methods. In this paper an adaptive neuro-fuzzy inference system for the prediction of surface roughness in end milling is presented. Spindle speed, feed rate, depth of cut and vibrations were used as independent input variables, while roughness parameter Ra as dependent output variable. Several variations are tested and the results of the optimum system are presented. Final results indicate that the proposed model can accurately predict surface roughness, even for input that was not used in training.

  4. Component aging evaluation with expert systems

    International Nuclear Information System (INIS)

    Wiesemann, J.S.; Maguire, H.T. Jr.

    1988-01-01

    The age degradation of components involves a complex relationship between a variety of variables. These relationships are typically modeled using probabilistic and deterministic analyses. These methods depend upon a formal understanding of the underlying degradation mechanisms and a database of experience which allows statistical analyses to extract numerical trends. At present, not all age degradation mechanisms are adequately modeled and available data for age degradation is in most cases insufficient. In addition, these methods tend to focus upon answers to isolated questions (e.g., What is the component failure rate?) rather than the more pertinent questions concerning operations and maintenance (e.g., should the component be replaced at the next outage). Fortunately, knowledge in the form of personal experience does exist which allows plant personnel to make decisions concerning operations and maintenance. This knowledge can be modeled using expert systems. This paper discusses CAGES (Component Aging Expert System). It combines expert rules (heuristics), probabilistic models, and deterministic models to make evaluations of component aging; predict the implications for component life extension, operational readiness, maintenance effectiveness, and safety, and make recommendations for maintenance and operation

  5. Uncertainty modeling in vibration, control and fuzzy analysis of structural systems

    CERN Document Server

    Halder, Achintya; Ayyub, Bilal M

    1997-01-01

    This book gives an overview of the current state of uncertainty modeling in vibration, control, and fuzzy analysis of structural and mechanical systems. It is a coherent compendium written by leading experts and offers the reader a sampling of exciting research areas in several fast-growing branches in this field. Uncertainty modeling and analysis are becoming an integral part of system definition and modeling in many fields. The book consists of ten chapters that report the work of researchers, scientists and engineers on theoretical developments and diversified applications in engineering sy

  6. An expert system for microbiologically influenced corrosion

    International Nuclear Information System (INIS)

    Carney, C.E.; Licina, G.J.

    1991-01-01

    Microbiologically Influenced Corrosion (MIC) is a damage mechanism that can cause serious degradation of service water system components. MIC can be particularly insidious since damage can occur very quickly, even in environments otherwise resistant to corrosion. Plant operations or maintenance personnel or system engineers typically do not have sufficient expertise to predict when and where MIC may occur or what methods of treatment are effective. An expert system (MICPro) has been devised which provides a tool for utilities to predict where MIC will occur, which systems or components are most susceptible, how operating parameters may affect vulnerability, and how to implement corrective and preventative measures. The system is designed to be simple to use: required inputs are common system parameters and results are presented as numbers from 1 to 10 indicating the likelihood of damage due to the given input. In this paper the structure and operation of the system is described, and future refinements are discussed

  7. MARBLE: A system for executing expert systems in parallel

    Science.gov (United States)

    Myers, Leonard; Johnson, Coe; Johnson, Dean

    1990-01-01

    This paper details the MARBLE 2.0 system which provides a parallel environment for cooperating expert systems. The work has been done in conjunction with the development of an intelligent computer-aided design system, ICADS, by the CAD Research Unit of the Design Institute at California Polytechnic State University. MARBLE (Multiple Accessed Rete Blackboard Linked Experts) is a system of C Language Production Systems (CLIPS) expert system tool. A copied blackboard is used for communication between the shells to establish an architecture which supports cooperating expert systems that execute in parallel. The design of MARBLE is simple, but it provides support for a rich variety of configurations, while making it relatively easy to demonstrate the correctness of its parallel execution features. In its most elementary configuration, individual CLIPS expert systems execute on their own processors and communicate with each other through a modified blackboard. Control of the system as a whole, and specifically of writing to the blackboard is provided by one of the CLIPS expert systems, an expert control system.

  8. Multipurpose expert-robot system model for control, diagnosis, maintenance, and repairs at the steam generators of the NPP

    International Nuclear Information System (INIS)

    Popa, I.

    1994-01-01

    The paper presents the model concept for a multipurpose expert-robot system for control, diagnosis, forecast, maintenance, and repairs at the steam generators of CANDU type nuclear power plants. The system has two separate parts: the expert system and the robot (manipulator) system. These parts compose a hierarchic structure with the expert system on the upper level. The expert system has a blackboard architecture, to which tree interfaces with the robot system, with the control system of the NPP and with the methods and techniques of control, maintenance and repairs system of the steam generator are added. Due to complex nature of its activities the expert-robot system model combines the deterministic type reasons with probabilistic, fuzzy, and neural-networks type ones. The information that enter the expert system comes from the robot system, from process, from user, and human expert. The information that enter robot system comes from the expert system, from the human operator (when connected) and from process. Control maintenance and repair operations take place by means of the robot system that can be monitored either directly by the expert system or by the human operator who follows its activity. All these activities are performed in parallel with the adequate information of the expert system directly, by the human operator, about the status parameters and, possibly, operating parameters of the steam generator components. The expert-robot system can work independently, but it can be connected and integrated in the control system of NPP, to take over and develop some of its functions. The activities concerning diagnosis and characterization of the state of steam generator components subsequent to control, as well as the forecast of their future behavior, are performed by means of the expert system. Due to these characteristics the expert-robot system can be used successfully in personnel training activities. (Author)

  9. SEPI an expert system for plant design

    International Nuclear Information System (INIS)

    Carotenuto, M.; Corleto, P.; Landeyro, P.

    1988-01-01

    The availability and suitability of technological information is of great importance in every kind of design task, especially when safety and reliability considerations are involved. In this paper an ''expert system for plant design'' (SEPI), is presented, together with its first application to nuclear back-end plants. This system is available on ENEA computer network. It is thought to be used both to collect know-how developed in the field and to assist unskilled designers during selection, evaluation and dimensioning tasks. It attemps to reproduce the normal way of ''reasoning'' and acting, and provides some graphic facilities

  10. An expert system for ranking companies and investments: wood industry case

    Directory of Open Access Journals (Sweden)

    Hliadis Lazaros

    2003-01-01

    Full Text Available Wood industry is a very important part of both the Greek Rural and industrial sector. The discovery of the differentiation in the level of growth and in the quality of financial management between the Greek wood companies can provide very important aid in the design of an effective rural development policy. The evaluation and ranking of Greek wood companies based on actual financial data is a very complicated task and it requires expertise knowledge and skills. On the other hand a computer expert system can perform validation and evaluation in an efficient way and can substitute human experts. An expert system was designed and developed towards this direction. It uses multicriteria analysis for each one of the wood companies based on actual financial data and it applies fundamental principles of fuzzy logic in order to calculate the expected intervals of flows for the following years. .

  11. Fuzzy expert system for the intelligent recognition of cerebral palsy ...

    African Journals Online (AJOL)

    Journal of Computer Science and Its Application. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 21, No 1 (2014) >. Log in or Register to get access to full text downloads.

  12. Designing a fuzzy expert system for selecting knowledge management strategy

    OpenAIRE

    Ameneh Khadivar; Shohreh Nasri Nasr Abadi; Elham Fallah

    2014-01-01

    knowledge management strategy is mentioned as one of the most important success factors for implementing knowledge management. The KM strategy selection is a complex decision that requires consideration of several factors. For evaluation and selection of an appropriate knowledge management strategy in organizations, many factors must be considered. The identified factors and their impact on knowledge management strategy are inherently ambiguous. In this study, an overview of theoretical found...

  13. Evaluation of Combined Heat and Power (CHP Systems Using Fuzzy Shannon Entropy and Fuzzy TOPSIS

    Directory of Open Access Journals (Sweden)

    Fausto Cavallaro

    2016-06-01

    Full Text Available Combined heat and power (CHP or cogeneration can play a strategic role in addressing environmental issues and climate change. CHP systems require less fuel than separate heat and power systems in order to produce the same amount of energy saving primary energy, improving the security of the supply. Because less fuel is combusted, greenhouse gas emissions and other air pollutants are reduced. If we are to consider the CHP system as “sustainable”, we must include in its assessment not only energetic performance but also environmental and economic aspects, presenting a multicriteria issue. The purpose of the paper is to apply a fuzzy multicriteria methodology to the assessment of five CHP commercial technologies. Specifically, the combination of the fuzzy Shannon’s entropy and the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS approach will be tested for this purpose. Shannon’s entropy concept, using interval data such as the α-cut, is a particularly suitable technique for assigning weights to criteria—it does not require a decision-making (DM to assign a weight to the criteria. To rank the proposed alternatives, a fuzzy TOPSIS method has been applied. It is based on the principle that the chosen alternative should be as close as possible to the positive ideal solution and be as far as possible from the negative ideal solution. The proposed approach provides a useful technical–scientific decision-making tool that can effectively support, in a consistent and transparent way, the assessment of various CHP technologies from a sustainable point of view.

  14. Expert system for nuclear power plant feedwater system diagnosis

    International Nuclear Information System (INIS)

    Meguro, R.; Kinoshita, Y.; Sato, T.; Yokota, Y.; Yokota, M.

    1987-01-01

    The Expert System for Nuclear Power Plant Feedwater System Diagnosis has been developed to assist maintenance engineers in nuclear power plants. This system adopts the latest process computer TOSBAC G8050 and the expert system developing tool TDES2, and has a large scale knowledge base which consists of the expert knowledge and experience of engineers in many fields. The man-machine system, which has been developed exclusively for diagnosis, improves the man-machine interface and realizes the graphic displays of diagnostic process and path, stores diagnostic results and searches past reference

  15. Recent Advances in Interval Type-2 Fuzzy Systems

    CERN Document Server

    Castillo, Oscar

    2012-01-01

    This book reviews current state of the art methods for building intelligent systems using type-2 fuzzy logic and bio-inspired optimization techniques. Combining type-2 fuzzy logic with optimization algorithms, powerful hy-brid intelligent systems have been built using the advantages that each technique offers. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation. This book can also be used as a reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intelligence, and similar ones. We con-sider that this book can also be used to get novel ideas for new lines of re-search, or to continue the lines of research proposed by the authors.

  16. Advanced Takagi‒Sugeno fuzzy systems delay and saturation

    CERN Document Server

    Benzaouia, Abdellah

    2014-01-01

    This monograph puts the reader in touch with a decade’s worth of new developments in the field of fuzzy control specifically those of the popular Takagi-Sugeno (T-S) type. New techniques for stabilizing control analysis and design based on multiple Lyapunov functions and linear matrix inequalities (LMIs), are proposed. All the results are illustrated with numerical examples and figures and a rich bibliography is provided for further investigation. Control saturations are taken into account within the fuzzy model. The concept of positive invariance is used to obtain sufficient asymptotic stability conditions for the fuzzy system with constrained control inside a subset of the state space. The authors also consider the non-negativity of the states. This is of practical importance in many chemical, physical and biological processes that involve quantities that have intrinsically constant and non-negative sign: concentration of substances, level of liquids, etc. Results for linear systems are then extended to l...

  17. Application of genetic algorithms to tuning fuzzy control systems

    Science.gov (United States)

    Espy, Todd; Vombrack, Endre; Aldridge, Jack

    1993-01-01

    Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.

  18. The UK system of recognising qualified experts

    International Nuclear Information System (INIS)

    Bines, W.

    2002-01-01

    EURATOM Basic Safety Standards (BSS) Directives have long included requirements for the involvement of qualified experts, the definition of which has scarcely changed since at least 1976. The Directive requirement, in the definition of qualified expert,, for competent authorities to recognise the capacity to act as a qualified expert has been interpreted by Member States in widely differing ways, ranging from the minimalist or case by case to the highly detailed and prescriptive. In the United Kingdom (UK), the qualified expert for occupational radiation protection is the radiation protection adviser and the competent authority is the Health and Safety Executive (HSE). The Ionising Radiations Regulations 1985, which largely implemented the 1980 BSS Directive, required an employer to appoint one or more radiation protection advisers for the purpose of advising him as to the observance of these Regulations and other health and safety matters in connection with ionising radiation. The Regulations addressed the question of recognition by forbidding an employer to appoint a person as a radiation protection adviser unless: that person was suitably qualified and experienced; the employer had notified the Health and Safety Executive in writing of the intended appointment at least 28 days in advance, giving the name of the person and particulars of his qualifications and experience and the scope of the advice he would be required to give; and the employer had received from HSE an acknowledgement in writing of the notification. This system allowed HSE to follow up and query any apparently unsuitable potential appointments while applying a light overall administrative touch. The Approved Code of Practice supporting the Regulations included advice on the qualifications, experience and qualities that the employer should look for in a suitable radiation protection adviser

  19. System for corrosion monitoring in pipeline applying fuzzy logic mathematics

    Science.gov (United States)

    Kuzyakov, O. N.; Kolosova, A. L.; Andreeva, M. A.

    2018-05-01

    A list of factors influencing corrosion rate on the external side of underground pipeline is determined. Principles of constructing a corrosion monitoring system are described; the system performance algorithm and program are elaborated. A comparative analysis of methods for calculating corrosion rate is undertaken. Fuzzy logic mathematics is applied to reduce calculations while considering a wider range of corrosion factors.

  20. New approach to solve symmetric fully fuzzy linear systems

    Indian Academy of Sciences (India)

    In this paper, we present a method to solve fully fuzzy linear systems with symmetric coefficient matrix. The symmetric coefficient matrix is decomposed into two systems of equations by using Cholesky method and then a solution can be obtained. Numerical examples are given to illustrate our method.

  1. Systems control with generalized probabilistic fuzzy-reinforcement learning

    NARCIS (Netherlands)

    Hinojosa, J.; Nefti, S.; Kaymak, U.

    2011-01-01

    Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input-output data are not available. In most combinations of fuzzy systems and RL, the environment is considered to be

  2. System control module diagnostic Expert Assistant

    Science.gov (United States)

    Flores, Luis M.; Hansen, Roger F.

    1990-01-01

    The Orbiter EXperiments (OEX) Program was established by NASA's Office of Aeronautics and Space Technology (OAST) to accomplish the precise data collection necessary to support a complete and accurate assessment of Space Transportation System (STS) Orbiter performance during all phases of a mission. During a mission, data generated by the various experiments are conveyed to the OEX System Control Module (SCM) which arranges for and monitors storage of the data on the OEX tape recorder. The SCM Diagnostic Expert Assistant (DEA) is an expert system which provides on demand advice to technicians performing repairs of a malfunctioning SCM. The DEA is a self-contained, data-driven knowledge-based system written in the 'C' Language Production System (CLIPS) for a portable micro-computer of the IBM PC/XT class. The DEA reasons about SCM hardware faults at multiple levels; the most detailed layer of encoded knowledge of the SCM is a representation of individual components and layouts of the custom-designed component boards.

  3. The Study of Expert System Utilization for the Accelerator Operation

    International Nuclear Information System (INIS)

    Budi-Santosa; Slamet-Santosa; Subari-Santosa

    2000-01-01

    The utilization of expert system in the accelerator laboratory has been studied. The study covers the utilization of expert system in the setting up experiment (tuning parameter), controlling system, safety or warning system. The results study shows, that using the expert system in the accelerator would be easy to operate the accelerator for user and operator. Increasing the skill of expert system could be updated without logical mechanism modification. (author)

  4. Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system

    Science.gov (United States)

    Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.

    2000-01-01

    Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

  5. An expert system for automated robotic grasping

    International Nuclear Information System (INIS)

    Stansfield, S.A.

    1990-01-01

    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

  6. An expert system to estimate SNM production at LWR systems

    International Nuclear Information System (INIS)

    Sandquist, G.M.; Allison, J.L.; Rogers, V.C.

    1988-01-01

    An artificial intelligence expert system, analysis of proliferation by expert system (APES), has been developed and tested to permit a nonexpert to quickly evaluate the capabilities and capacities of a reactor and reprocessing system for producing and separating plutonium [special nuclear material (SNM)] even when system information may be limited and uncertain. The present analysis domain of APES is directed at light water reactors and Purex reprocessing, but extension of the domain is planned

  7. Diagnosis of Diabetes Diseases Using an Artificial Immune Recognition System2 (AIRS2) with Fuzzy K-nearest Neighbor

    OpenAIRE

    CHIKH, Mohamed Amine; SAIDI, Meryem; SETTOUTI, Nesma

    2012-01-01

    The use of expert systems and artificial intelligence techniques in disease diagnosis has been increasing gradually. Artificial Immune Recognition System (AIRS) is one of the methods used in medical classification problems. AIRS2 is a more efficient version of the AIRS algorithm. In this paper, we used a modified AIRS2 called MAIRS2 where we replace the K- nearest neighbors algorithm with the fuzzy K-nearest neighbors to improve the diagnostic accuracy of diabetes diseases. The diabetes disea...

  8. Rotating Machinery Predictive Maintenance Through Expert System

    Directory of Open Access Journals (Sweden)

    M. Sarath Kumar

    2000-01-01

    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++.

  9. WES: A well test analysis expert system

    International Nuclear Information System (INIS)

    Mensch, A.

    1988-06-01

    This report describes part of the development of an expert system in the domain of well-test analysis. This work has been done during my final internship, completed at the Lawrence Berkeley Laboratory. The report is divided in three parts: the first one gives a description of the state of the project at the time I first began to work on it, and raises some problems that have to be solved. The second section shows the results that have been reached, and the last one draws conclusions from these results and proposes extensions that would be useful in the future

  10. An on-line diagnostic expert system

    International Nuclear Information System (INIS)

    Felkel, L.

    1987-01-01

    As experience with on-line information systems, experts systems and artificial intelligence tools grows, the authors retreat from the first euphoria that AI could help them solve the problem they were unable to solve with conventional programming. The major effort of the development time goes into building the knowledge-base. There is no such thing as a generic knowledge-base for nuclear power plants as there is, for example, for the diagnosis of a Boeing 747 aircraft. AI-methods, tools and hardware are still in a state which does not optimally lend itself to real-time application. The ability of developing prototype systems to investigate variants otherwise too costly to justify is one advantage that the authors gladly accept. Last, but no least the tools provide a flexible and adaptable user interface (desktop window systems) etc. The development of such tools in a project would be prohibitive and room for experimentation would be limited

  11. An Expert System for Concrete Bridge Management

    DEFF Research Database (Denmark)

    Brito, J. de; Branco, F. A.; Thoft-Christensen, Palle

    1997-01-01

    The importance of bridge repair versus new bridge construction has risen in recent decades due to high deterioration rates that have been observed in these structures. Budgets both for building new bridges and keeping the existing ones are always limited. To help rational decision-making, bridge...... management systems are presently being implemented by bridge authorities in several countries. The prototype of an expert system for concrete bridge management is presented in this paper, with its functionality relying on two modules. The inspection module relies on a periodic acquisition of field...... information complemented by a knowledge-based interactive system, BRIDGE-1. To optimize management strategies at the headquarters, the BRIDGE-2 module was implemented, including three submodules: inspection strategy, maintenance and repair....

  12. The plant expert system (PLEXSYS) development environment

    International Nuclear Information System (INIS)

    Hashemi, S.; Patterson, L.; Jeffery, M.; Delashmutt, L.

    1989-06-01

    The PLEXSYS software engineering tool provides an environment with which utility engineers can build and use expert systems for power plant applications. PLEXSYS provides the engineer with access to many powerful Artificial Intelligence methodologies, while retaining an engineering frame of reference and minimizing the need for a formal background in computer science. The principle concept is that the description and understanding of power plant systems centers on graphical forms such as piping and instrumentation diagrams and electrical line diagrams, which define a graphics-based model of plant knowledge that is common to many applications. PLEXSYS provides a model editor that allows the user to construct and modify models of hydraulic, electrical, and information systems in terms of elementary components and their interconnections. Analysis of the resulting schematic models is provided by several functions that perform network analysis, schematic browsing, mathematical modeling and customization of the user interface. 41 figs., 1 tab

  13. Spatial xenon oscillation control with expert systems

    International Nuclear Information System (INIS)

    Alten, S.; Danofsky, R.A.

    1993-01-01

    Spatial power oscillations were attributed to the xenon transients in a reactor core in 1958 by Randall and St. John. These transients are usually initiated by a local reactivity insertion and lead to divergent axial flux oscillations in the core at constant power. Several heuristic manual control strategies and automatic control methods were developed to damp the xenon oscillations at constant power operations. However, after the load-follow operation of the reactors became a necessity of life, a need for better control strategies arose. Even though various advanced control strategies were applied to solve the xenon oscillation control problem for the load-follow operation, the complexity of the system created difficulties in modeling. The strong nonlinearity of the problem requires highly sophisticated analytical approaches that are quite inept for numerical solutions. On the other hand, the complexity of a system and heuristic nature of the solutions are the basic reasons for using artificial intelligence techniques such as expert systems

  14. TOXPERT: An Expert System for Risk Assessment

    Science.gov (United States)

    Soto, R. J.; Osimitz, T. G.; Oleson, A.

    1988-01-01

    TOXPERT is an artificial intelligence based system used to model product safety, toxicology (TOX) and regulatory (REG) decision processes. An expert system shell uses backward chaining rule control to link “marketing approval” goals to the type of product, REG agency, exposure conditions and TOX. Marketing risks are primarily a function of the TOX, hazards and exposure potential. The method employed differentiates between REG requirements in goal seeking control for various types of products. This is accomplished by controlling rule execution by defining frames for each REG agency. In addition, TOXPERT produces classifications of TOX ratings and suggested product labeling. This production rule system uses principles of TOX, REGs, corporate guidelines and internal “rules of thumb.” TOXPERT acts as an advisor for this narrow domain. Advantages are that it can make routine decisions freeing professional's time for more complex problem solving, provide backup and training.

  15. An expert system technology for work authorization information systems

    International Nuclear Information System (INIS)

    Munchausen, J.H.; Glazer, K.A.

    1988-01-01

    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

  16. Fuzzy Based Decision Support System for Condition Assessment and Rating of Bridges

    Science.gov (United States)

    Srinivas, Voggu; Sasmal, Saptarshi; Karusala, Ramanjaneyulu

    2016-09-01

    In this work, a knowledge based decision support system has been developed to efficiently handle the issues such as distress diagnosis, assessment of damages and condition rating of existing bridges towards developing an exclusive and robust Bridge Management System (BMS) for sustainable bridges. The Knowledge Based Expert System (KBES) diagnoses the distresses and finds the cause of distress in the bridge by processing the data which are heuristic and combined with site inspection results, laboratory test results etc. The coupling of symbolic and numeric type of data has been successfully implemented in the expert system to strengthen its decision making process. Finally, the condition rating of the bridge is carried out using the assessment results obtained from the KBES and the information received from the bridge inspector. A systematic procedure has been developed using fuzzy mathematics for condition rating of bridges by combining the fuzzy weighted average and resolution identity technique. The proposed methodologies and the decision support system will facilitate in developing a robust and exclusive BMS for a network of bridges across the country and allow the bridge engineers and decision makers to carry out maintenance of bridges in a rational and systematic way.

  17. Adaptive fuzzy trajectory control for biaxial motion stage system

    Directory of Open Access Journals (Sweden)

    Wei-Lung Mao

    2016-04-01

    Full Text Available Motion control is an essential part of industrial machinery and manufacturing systems. In this article, the adaptive fuzzy controller is proposed for precision trajectory tracking control in biaxial X-Y motion stage system. The theoretical analyses of direct fuzzy control which is insensitive to parameter uncertainties and external load disturbances are derived to demonstrate the feasibility to track the reference trajectories. The Lyapunov stability theorem has been used to testify the asymptotic stability of the whole system, and all the signals are bounded in the closed-loop system. The intelligent position controller combines the merits of the adaptive fuzzy control with robust characteristics and learning ability for periodic command tracking of a servo drive mechanism. The simulation and experimental results on square, triangle, star, and circle reference contours are presented to show that the proposed controller indeed accomplishes the better tracking performances with regard to model uncertainties. It is observed that the convergence of parameters and tracking errors can be faster and smaller compared with the conventional adaptive fuzzy control in terms of average tracking error and tracking error standard deviation.

  18. An intelligent temporal pattern classification system using fuzzy ...

    Indian Academy of Sciences (India)

    In this paper, we propose a new pattern classification system by combining Temporal features with Fuzzy Min–Max (TFMM) neural network based classifier for effective decision support in medical diagnosis. Moreover, a Particle Swarm Optimization (PSO) algorithm based rule extractor is also proposed in this work for ...

  19. Advanced biofeedback from surface electromyography signals using fuzzy system

    DEFF Research Database (Denmark)

    Samani, Afshin; Holtermann, Andreas; Søgaard, Karen

    2010-01-01

    The aims of this study were to develop a fuzzy inference-based biofeedback system and investigate its effects when inducing active (shoulder elevation) and passive (relax) pauses on the trapezius muscle electromyographic (EMG) activity during computer work. Surface EMG signals were recorded from...

  20. Fuzzy data analysis

    CERN Document Server

    Bandemer, Hans

    1992-01-01

    Fuzzy data such as marks, scores, verbal evaluations, imprecise observations, experts' opinions and grey tone pictures, are quite common. In Fuzzy Data Analysis the authors collect their recent results providing the reader with ideas, approaches and methods for processing such data when looking for sub-structures in knowledge bases for an evaluation of functional relationship, e.g. in order to specify diagnostic or control systems. The modelling presented uses ideas from fuzzy set theory and the suggested methods solve problems usually tackled by data analysis if the data are real numbers. Fuzzy Data Analysis is self-contained and is addressed to mathematicians oriented towards applications and to practitioners in any field of application who have some background in mathematics and statistics.

  1. Fuzzy Evidence in Identification, Forecasting and Diagnosis

    CERN Document Server

    Rotshtein, Alexander P

    2012-01-01

    The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving. The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fu...

  2. A genetic fuzzy system for unstable angina risk assessment.

    Science.gov (United States)

    Dong, Wei; Huang, Zhengxing; Ji, Lei; Duan, Huilong

    2014-02-18

    Unstable Angina (UA) is widely accepted as a critical phase of coronary heart disease with patients exhibiting widely varying risks. Early risk assessment of UA is at the center of the management program, which allows physicians to categorize patients according to the clinical characteristics and stratification of risk and different prognosis. Although many prognostic models have been widely used for UA risk assessment in clinical practice, a number of studies have highlighted possible shortcomings. One serious drawback is that existing models lack the ability to deal with the intrinsic uncertainty about the variables utilized. In order to help physicians refine knowledge for the stratification of UA risk with respect to vagueness in information, this paper develops an intelligent system combining genetic algorithm and fuzzy association rule mining. In detail, it models the input information's vagueness through fuzzy sets, and then applies a genetic fuzzy system on the acquired fuzzy sets to extract the fuzzy rule set for the problem of UA risk assessment. The proposed system is evaluated using a real data-set collected from the cardiology department of a Chinese hospital, which consists of 54 patient cases. 9 numerical patient features and 17 categorical patient features that appear in the data-set are selected in the experiments. The proposed system made the same decisions as the physician in 46 (out of a total of 54) tested cases (85.2%). By comparing the results that are obtained through the proposed system with those resulting from the physician's decision, it has been found that the developed model is highly reflective of reality. The proposed system could be used for educational purposes, and with further improvements, could assist and guide young physicians in their daily work.

  3. Fuzzy self-learning control for magnetic servo system

    Science.gov (United States)

    Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

    1994-01-01

    It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

  4. Expert Graphics System Research in the Department of the Navy.

    Science.gov (United States)

    Duff, Jon M.

    1987-01-01

    Presents current trends in the development of expert systems within the Department of the Navy, particularly research into expert graphics systems intended to support the Authoring Instructional Methods (AIM) research project. Defines artificial intelligence and expert systems. Discusses the operations and functions of the Navy's intelligent…

  5. Criteria for the CAREM reactor's expert system design conduction

    International Nuclear Information System (INIS)

    Furman, A.; Delgado, R.

    1990-01-01

    The present work describes the analysis made to start with the development of an Expert System for the CAREM (SE) reactor's conduction. The following tasks are presented: a) purpose of the Expert System; b) Decision Making structure; c) Architecture of the Expert System; d) Description of Subsystems and e) Licensing. (Author) [es

  6. Expert Systems: A Challenge for the Reading Profession.

    Science.gov (United States)

    Balajthy, Ernest

    The expert systems are designed to imitate the reasoning of a human expert in a content area field. Designed to be advisors, these software systems combine the content area knowledge and decision-making ability of an expert with the user's understanding and knowledge of particular circumstances. The reading diagnosis system, the RD2P System…

  7. LANDSLIDE SUSCEPTIBILITY ASSESSMENT THROUGH FUZZY LOGIC INFERENCE SYSTEM (FLIS

    Directory of Open Access Journals (Sweden)

    T. Bibi

    2016-09-01

    Full Text Available Landslide is among one of the most important natural hazards that lead to modification of the environment. It is a regular feature of a rapidly growing district Mansehra, Pakistan. This caused extensive loss of life and property in the district located at the foothills of Himalaya. Keeping in view the situation it is concluded that besides structural approaches the non-structural approaches such as hazard and risk assessment maps are effective tools to reduce the intensity of damage. A landslide susceptibility map is base for engineering geologists and geomorphologists. However, it is not easy to produce a reliable susceptibility map due to complex nature of landslides. Since 1980s, several mathematical models have been developed to map landslide susceptibility and hazard. Among various models this paper is discussing the effectiveness of fuzzy logic approach for landslide susceptibility mapping in District Mansehra, Pakistan. The factor maps were modified as landslide susceptibility and fuzzy membership functions were assessed for each class. Likelihood ratios are obtained for each class of contributing factors by considering the expert opinion. The fuzzy operators are applied to generate landslide susceptibility maps. According to this map, 17% of the study area is classified as high susceptibility, 32% as moderate susceptibility, 51% as low susceptibility and areas. From the results it is found that the fuzzy model can integrate effectively with various spatial data for landslide hazard mapping, suggestions in this study are hope to be helpful to improve the applications including interpretation, and integration phases in order to obtain an accurate decision supporting layer.

  8. Fuzzy Logic Based MPPT Controller for a PV System

    Directory of Open Access Journals (Sweden)

    Carlos Robles Algarín

    2017-12-01

    Full Text Available The output power of a photovoltaic (PV module depends on the solar irradiance and the operating temperature; therefore, it is necessary to implement maximum power point tracking controllers (MPPT to obtain the maximum power of a PV system regardless of variations in climatic conditions. The traditional solution for MPPT controllers is the perturbation and observation (P&O algorithm, which presents oscillation problems around the operating point; the reason why improving the results obtained with this algorithm has become an important goal to reach for researchers. This paper presents the design and modeling of a fuzzy controller for tracking the maximum power point of a PV System. Matlab/Simulink (MathWorks, Natick, MA, USA was used for the modeling of the components of a 65 W PV system: PV module, buck converter and fuzzy controller; highlighting as main novelty the use of a mathematical model for the PV module, which, unlike diode based models, only needs to calculate the curve fitting parameter. A P&O controller to compare the results obtained with the fuzzy control was designed. The simulation results demonstrated the superiority of the fuzzy controller in terms of settling time, power loss and oscillations at the operating point.

  9. A simulation-based expert system for nuclear power plant diagnostics

    International Nuclear Information System (INIS)

    Hassberger, J.A.; Lee, J.C.

    1989-01-01

    An expert system for diagnosing operational transients in a nuclear power plant is discussed. Hypothesis and test is used as the problem-solving strategy with hypotheses generated by an expert system that monitors the plant for patterns of data symptomatic of known failure modes. Fuzzy logic is employed as the inferencing mechanism with two complementary implication schemes to handle scenarios involving competing failures. Hypothesis testing is performed. An artificial intelligence framework based on a critical functions approach is used to deal with the complexity of a nuclear plant. A prototype system for diagnosing transients in the reactor coolant system of a pressurized water reactor has been developed to test the algorithms described here. Results are presented for the diagnosis of data from the Three Mile Island Unit 2 loss-of-feedwater/small-break loss-of-collant accident

  10. A framework expert system for pressure vessels

    International Nuclear Information System (INIS)

    Wang, Y.C.; Qin, S.J.

    1989-01-01

    Expert systems, known as a powerful tool to those numerical problems accompanied with logical argumentation, are facing the era of extended application into the engineering fields beyond the classical scopes of diagnosis and consultation. With regard to pressure vessels design it seems that the most important task is to establish a general purpose frame based on a microcomputer skeleton system to meet the various requirements of different vessels. The authors have made an attempt to perform such a skeleton designated file, ESTOOL, in order to achieve the objectives of executing numerical calculation combined with logical reasoning, and attaining higher efficiency of rules searching process. It has been successfully patched to the design software package for jacketed vessel with stirring shaft. This paper presents the guiding concepts and basic structure of ESTOOL via knowledge acquisition subsystem and inference engine

  11. A survey of Framatome's expert systems activity

    International Nuclear Information System (INIS)

    Delaigue, D.; Grundstein, M.

    1987-01-01

    The French multinational nuclear energy world leader, Framatome, has designed and installed more than 40000 MWe of power in both France and abroad using Pressurized Water Reactor (PWR) technology. The French nuclear program ranks as one of the most successful in the world. In 1983, Framatome entered the Applied Artificial Intelligence (A.I.) field by setting up FRAMENTEC S.A., a joint venture with TEKNOWLEDGE Inc. Today, Framentec is a wholly-owned subsidiary of Framatome and is among the leading European companies specializing in Applied Artificial Intelligence. Framatome now has a 7.5% stake in Teknowledge Inc. The main applications in the nuclear industry can be summarized as follows: quality assurance; design of systems subject to extreme operating conditions; maintenance of complex systems; control of complex phenomenon producing high velocity transients; expert advice in multiple fields; compliance with complex regulations; high-skill personnel requirements; heavy financial investments

  12. A Fuzzy Semantic Information Retrieval System for Transactional Applications

    OpenAIRE

    A O Ajayi; H A Soriyan; G A Aderounmu

    2009-01-01

    In this paper, we present an information retrieval system based on the concept of fuzzy logic to relate vague and uncertain objects with un-sharp boundaries. The simple but comprehensive user interface of the system permits the entering of uncertain specifications in query forms. The system was modelled and simulated in a Matlab environment; its implementation was carried out using Borland C++ Builder. The result of the performance measure of the system using precision and recall rates is enc...

  13. Fuzzy set classifier for waste classification tracking

    International Nuclear Information System (INIS)

    Gavel, D.T.

    1992-01-01

    We have developed an expert system based on fuzzy logic theory to fuse the data from multiple sensors and make classification decisions for objects in a waste reprocessing stream. Fuzzy set theory has been applied in decision and control applications with some success, particularly by the Japanese. We have found that the fuzzy logic system is rather easy to design and train, a feature that can cut development costs considerably. With proper training, the classification accuracy is quite high. We performed several tests sorting radioactive test samples using a gamma spectrometer to compare fuzzy logic to more conventional sorting schemes

  14. Fuzzy control for optimal operation of complex chilling systems; Betriebsoptimierung von komplexen Kaelteanlagen mit Fuzzy-Control

    Energy Technology Data Exchange (ETDEWEB)

    Talebi-Daryani, R. [Fachhochschule Koeln (Germany). Lehrgebiet und Lab. fuer Regelungs- und Gebaeudeleittechnik; Luther, C. [JCI Regelungstechnik GmbH, Koeln (Germany)

    1998-05-01

    The optimization potentials for the operation of chilling systems within the building supervisory control systems are limited to abilities of PLC functions with their binary logic. The aim of this project is to replace inefficient PLC-solutions for the operation of chilling system by a Fuzzy control system. Optimal operation means: reducing operation time and operation costs of the system, reducing cooling energy generation- and consumption costs. Analysis of the thermal behaviour of the building and the chilling system is necessary, in order to find the current efficient cooling potentials and cooling methods during the operation. Three different Fuzzy controller have been developed with a total rule number of just 70. This realized Fuzzy control system is able to forecast the maximum cooling power of the building, but also to determine the cooling potential of the out door air. This new Fuzzy control system has been successfully commissioned, and remarkable improvement of the system behaviour is reached. Comparison of the system behaviour before and after the implementation of Fuzzy control system proved the benefits of the Fuzzy logic based operation system realized here. The system described here is a joint project between the University of applied sciences Cologne, and Johnson Controls International Cologne. The Fuzzy software tool used here (SUCO soft Fuzzy TECH 4.0), was provided by Kloeckner Moeller Bonn. (orig.) [Deutsch] Die Betriebsoptimierung von Kaelteanlagen innerhalb von Gebaeudeleitsystemen ist auf die Faehigkeiten von logischen Steuerverknuepfungen der Digitaltechnik begrenzt. In diesem Zusammenhang kann nur ein geringer Anteil der Information ueber das thermische Speicherverhalten des jeweiligen Gebaeudes herangezogen werden. Ziel des vorliegenden Projektes war es, die unzureichenden logischen Steuerverknuepfungen durch ein Fuzzy-Control-System zu ersetzen, um die Arbeitsweise der Kaelteanlage zu optimieren. Die Optimierungskriterien dieses

  15. Selection Input Output by Restriction Using DEA Models Based on a Fuzzy Delphi Approach and Expert Information

    Science.gov (United States)

    Arsad, Roslah; Nasir Abdullah, Mohammad; Alias, Suriana; Isa, Zaidi

    2017-09-01

    Stock evaluation has always been an interesting problem for investors. In this paper, a comparison regarding the efficiency stocks of listed companies in Bursa Malaysia were made through the application of estimation method of Data Envelopment Analysis (DEA). One of the interesting research subjects in DEA is the selection of appropriate input and output parameter. In this study, DEA was used to measure efficiency of stocks of listed companies in Bursa Malaysia in terms of the financial ratio to evaluate performance of stocks. Based on previous studies and Fuzzy Delphi Method (FDM), the most important financial ratio was selected. The results indicated that return on equity, return on assets, net profit margin, operating profit margin, earnings per share, price to earnings and debt to equity were the most important ratios. Using expert information, all the parameter were clarified as inputs and outputs. The main objectives were to identify most critical financial ratio, clarify them based on expert information and compute the relative efficiency scores of stocks as well as rank them in the construction industry and material completely. The methods of analysis using Alirezaee and Afsharian’s model were employed in this study, where the originality of Charnes, Cooper and Rhodes (CCR) with the assumption of Constant Return to Scale (CSR) still holds. This method of ranking relative efficiency of decision making units (DMUs) was value-added by the Balance Index. The interested data was made for year 2015 and the population of the research includes accepted companies in stock markets in the construction industry and material (63 companies). According to the ranking, the proposed model can rank completely for 63 companies using selected financial ratio.

  16. A fuzzy control technique for a magnetically levitated system

    Energy Technology Data Exchange (ETDEWEB)

    Lo Verso, G [C.N.R., Ce.Ri.S.E.P., Palermo (Italy); Trapanese, M [Dipt. di Ingegneria Elettrica, Univ. di Palermo (Italy)

    1996-12-31

    This paper presents the results of some analytical and numerical investigations on a control approach for magnetically leviated systems. This approach is based on fuzzy logic. It has been widely demonstrated that traditional control systems consent to maintain a stiff control on the air gap length. However, the traditional approaches could cause at very high speed, a vertical acceleration of the vehicle cabin larger than the maximum value currently allowed by the ISO standard. It is aim of this work to investigate the possibilities that a fuzzy controller offer in order to solve this problem. In order set up the controller, every mechanical degree of freedom is modelled in terms of some linguistic variables. These linguistic variables are described by several fuzzy sets. It must be noted that, doing so, the disturbances can be described in terms of fuzzy sets, too. A single-mass-model of the vehicle is considered in the paper. The features of the controller are numerically simulated under several types of disturbances and they are compared with a traditional control approach. It is shown how some parameters (especially the vertical acceleration) improve their behaviour. (orig.)

  17. Design of a Polynomial Fuzzy Observer Controller With Sampled-Output Measurements for Nonlinear Systems Considering Unmeasurable Premise Variables

    OpenAIRE

    Liu, Chuang; Lam, H. K.

    2015-01-01

    In this paper, we propose a polynomial fuzzy observer controller for nonlinear systems, where the design is achieved through the stability analysis of polynomial-fuzzy-model-based (PFMB) observer-control system. The polynomial fuzzy observer estimates the system states using estimated premise variables. The estimated states are then employed by the polynomial fuzzy controller for the feedback control of nonlinear systems represented by the polynomial fuzzy model. The system stability of the P...

  18. A fuzzy recommendation system for daily water intake

    Directory of Open Access Journals (Sweden)

    Bin Dai

    2016-05-01

    Full Text Available Water is one of the most important constituents of the human body. Daily consumption of water is thus necessary to protect human health. Daily water consumption is related to several factors such as age, ambient temperature, and degree of physical activity. These factors are generally difficult to express with exact numerical values. The main objective of this article is to build a daily water intake recommendation system using fuzzy methods. This system will use age, physical activity, and ambient temperature as the input factors and daily water intake values as the output factor. The reasoning mechanism of the fuzzy system can calculate the recommended value of daily water intake. Finally, the system will compare the actual recommended values with our system to determine the usefulness. The experimental results show that this recommendation system is effective in actual application.

  19. Biogas plant control system

    International Nuclear Information System (INIS)

    Balasevicius, L.; Dervinis, G.; Macerauskas, V.

    2002-01-01

    This paper presents intelligent control system for the pig farm biogas production process. The system uses a fuzzy logic models based on knowledge of experts and operators. Four fuzzy models are introduced. The adequacy of fuzzy models is verified using real data and MATLAB simulation. Proposed expert system is implemented into traditional SCADA system for biogas process prediction and failure analyzing. (authors)

  20. A study on expert system applications for nuclear power plant

    International Nuclear Information System (INIS)

    Huh, Young Hwan; Kim, Yeong Jin; Park, Nam Seog; Dong, In Sook; Choi, In Seon

    1987-12-01

    The application of artificial intelligence techniques to nuclear power plants such as expert systems is rapidly emerging. expert systems can contribute significantly to the availability and the improved operation and safety of nuclear power plants. The objective of the project is to develop an expert system in a selected application area in the nuclear power plants. This project will last for 3 years. The first year's tasks are: - Information collection and literature survey on expert systems. - Analysis of several applicable areas for applying AI technologies to the nuclear power plants. - Conceptual design of a few selected domains. - Selection of hardware and software tools for the development of the expert system

  1. ART-Ada: An Ada-based expert system tool

    Science.gov (United States)

    Lee, S. Daniel; Allen, Bradley P.

    1991-01-01

    The Department of Defense mandate to standardize on Ada as the language for software systems development has resulted in increased interest in making expert systems technology readily available in Ada environments. NASA's Space Station Freedom is an example of the large Ada software development projects that will require expert systems in the 1990's. Another large scale application that can benefit from Ada based expert system tool technology is the Pilot's Associate (PA) expert system project for military combat aircraft. Automated Reasoning Tool (ART) Ada, an Ada Expert system tool is described. ART-Ada allow applications of a C-based expert system tool called ART-IM to be deployed in various Ada environments. ART-Ada is being used to implement several prototype expert systems for NASA's Space Station Freedom Program and the U.S. Air Force.

  2. Expert systems and optimisation in process control

    International Nuclear Information System (INIS)

    Mamdani, A.; Efstathiou, J.

    1986-01-01

    This report brings together recent developments both in expert systems and in optimisation, and deals with current applications in industry. Part One is concerned with Artificial Intellegence in planning and scheduling and with rule-based control implementation. The tasks of control maintenance, rescheduling and planning are each discussed in relation to new theoretical developments, techniques available, and sample applications. Part Two covers model based control techniques in which the control decisions are used in a computer model of the process. Fault diagnosis, maintenance and trouble-shooting are just some of the activities covered. Part Three contains case studies of projects currently in progress, giving details of the software available and the likely future trends. One of these, on qualitative plant modelling as a basis for knowledge-based operator aids in nuclear power stations is indexed separately. (author)

  3. Research on laser cladding control system based on fuzzy PID

    Science.gov (United States)

    Zhang, Chuanwei; Yu, Zhengyang

    2017-12-01

    Laser cladding technology has a high demand for control system, and the domestic laser cladding control system mostly uses the traditional PID control algorithm. Therefore, the laser cladding control system has a lot of room for improvement. This feature is suitable for laser cladding technology, Based on fuzzy PID three closed-loop control system, and compared with the conventional PID; At the same time, the laser cladding experiment and friction and wear experiment were carried out under the premise of ensuring the reasonable control system. Experiments show that compared with the conventional PID algorithm in fuzzy the PID algorithm under the surface of the cladding layer is more smooth, the surface roughness increases, and the wear resistance of the cladding layer is also enhanced.

  4. A Genetic Based Neuro-Fuzzy Controller System

    International Nuclear Information System (INIS)

    Mohamed, A.H.

    2014-01-01

    Recently, the mobile robots have great importance in the manufacturing processes. They are widely used for assembling processes, handling the dangerous components, moving the weighted things, etc. Designing the controller of the mobile robot is a very complex task. Many simple control systems used the neuro-fuzzy controller in the mobile robots. But, they faced with great complexity when moving in unstructured and dynamic environments. The proposed system introduces the uses of the genetic algorithm for optimizing the parameters of the neuro-fuzzy controller. So, the proposed system can improve the performance of the mobile robots. It has applied for a mobile robot used for moving the dangerous and critical materials in unstructured environment. Its results are compared with other traditional controller systems. The suggested system has proved its success for the real-time applications

  5. Robust fuzzy output feedback controller for affine nonlinear systems via T-S fuzzy bilinear model: CSTR benchmark.

    Science.gov (United States)

    Hamdy, M; Hamdan, I

    2015-07-01

    In this paper, a robust H∞ fuzzy output feedback controller is designed for a class of affine nonlinear systems with disturbance via Takagi-Sugeno (T-S) fuzzy bilinear model. The parallel distributed compensation (PDC) technique is utilized to design a fuzzy controller. The stability conditions of the overall closed loop T-S fuzzy bilinear model are formulated in terms of Lyapunov function via linear matrix inequality (LMI). The control law is robustified by H∞ sense to attenuate external disturbance. Moreover, the desired controller gains can be obtained by solving a set of LMI. A continuous stirred tank reactor (CSTR), which is a benchmark problem in nonlinear process control, is discussed in detail to verify the effectiveness of the proposed approach with a comparative study. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  6. Intelligent neural network and fuzzy logic control of industrial and power systems

    Science.gov (United States)

    Kuljaca, Ognjen

    The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of

  7. An Outsourcing Expert System for Governing Organizations

    Directory of Open Access Journals (Sweden)

    Meisam Shahbazi

    2016-10-01

    Full Text Available Making the right decision about doing activities in-house vs. outsourcing is one of the important management decisions. The considerable effect of this decision on organizational performance and responsiveness is supported by theoretical and empirical evidence. In this study, using the experts’ knowledge extraction and modeling, we have designed a logical framework for deciding about outsourcing in governing organizations and accordingly an expert system has been developed. As an applied research a descriptive approach and case study method have been used. Objectives, inevitable circumstances, requirements, background conditions and facilitators have been identified as the underlying components of the system. The system provides a recommendation for each activity and prioritizes them based on readiness for outsourcing. An implementation in IT department of a sample organization is provided and the results are analyzed.  In the end, the proposed system for activities of IT Management was carried out in one of the organizations and consequently the obtained outputs and results were analyzed.

  8. Concept of expert system for modal split in transportation planning

    Directory of Open Access Journals (Sweden)

    Popović Maja M.

    2006-01-01

    Full Text Available The objective of this paper is to develop a concept of expert system based on the survey of experts' opinions and their experience concerning relations in modal split, on the basis of parameters of transport system demand and transport supply, defined through PT travel time and city size, i.e. mean trip length. This expert system could be of use both to experts and less experienced planners who could apply the knowledge contained in this expert system for further improvement, on operational as well as on strategic level.

  9. Fuzzy Logic Applied to an Oven Temperature Control System

    Directory of Open Access Journals (Sweden)

    Nagabhushana KATTE

    2011-10-01

    Full Text Available The paper describes the methodology of design and development of fuzzy logic based oven temperature control system. As simple fuzzy logic controller (FLC structure with an efficient realization and a small rule base that can be easily implemented in existing underwater control systems is proposed. The FLC has been designed using bell-shaped membership function for fuzzification, 49 control rules in its rule base and centre of gravity technique for defuzzification. Analog interface card with 16-bits resolution is designed to achieve higher precision in temperature measurement and control. The experimental results of PID and FLC implemented system are drawn for a step input and presented in a comparative fashion. FLC exhibits fast response and it has got sharp rise time and smooth control over conventional PID controller. The paper scrupulously discusses the hardware and software (developed using ‘C’ language features of the system.

  10. Designing a fuzzy scheduler for hard real-time systems

    Science.gov (United States)

    Yen, John; Lee, Jonathan; Pfluger, Nathan; Natarajan, Swami

    1992-01-01

    In hard real-time systems, tasks have to be performed not only correctly, but also in a timely fashion. If timing constraints are not met, there might be severe consequences. Task scheduling is the most important problem in designing a hard real-time system, because the scheduling algorithm ensures that tasks meet their deadlines. However, the inherent nature of uncertainty in dynamic hard real-time systems increases the problems inherent in scheduling. In an effort to alleviate these problems, we have developed a fuzzy scheduler to facilitate searching for a feasible schedule. A set of fuzzy rules are proposed to guide the search. The situation we are trying to address is the performance of the system when no feasible solution can be found, and therefore, certain tasks will not be executed. We wish to limit the number of important tasks that are not scheduled.

  11. Use of Fuzzy Logic Systems for Assessment of Primary Faults

    Science.gov (United States)

    Petrović, Ivica; Jozsa, Lajos; Baus, Zoran

    2015-09-01

    In electric power systems, grid elements are often subjected to very complex and demanding disturbances or dangerous operating conditions. Determining initial fault or cause of those states is a difficult task. When fault occurs, often it is an imperative to disconnect affected grid element from the grid. This paper contains an overview of possibilities for using fuzzy logic in an assessment of primary faults in the transmission grid. The tool for this task is SCADA system, which is based on information of currents, voltages, events of protection devices and status of circuit breakers in the grid. The function model described with the membership function and fuzzy logic systems will be presented in the paper. For input data, diagnostics system uses information of protection devices tripping, states of circuit breakers and measurements of currents and voltages before and after faults.

  12. Fundamentals of computational intelligence neural networks, fuzzy systems, and evolutionary computation

    CERN Document Server

    Keller, James M; Fogel, David B

    2016-01-01

    This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basi function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzz...

  13. An hierarchical approach to performance evaluation of expert systems

    Science.gov (United States)

    Dominick, Wayne D. (Editor); Kavi, Srinu

    1985-01-01

    The number and size of expert systems is growing rapidly. Formal evaluation of these systems - which is not performed for many systems - increases the acceptability by the user community and hence their success. Hierarchical evaluation that had been conducted for computer systems is applied for expert system performance evaluation. Expert systems are also evaluated by treating them as software systems (or programs). This paper reports many of the basic concepts and ideas in the Performance Evaluation of Expert Systems Study being conducted at the University of Southwestern Louisiana.

  14. A fuzzy recommendation system for daily water intake

    OpenAIRE

    Bin Dai; Rung-Ching Chen; Shun-Zhi Zhu; Chung-Yi Huang

    2016-01-01

    Water is one of the most important constituents of the human body. Daily consumption of water is thus necessary to protect human health. Daily water consumption is related to several factors such as age, ambient temperature, and degree of physical activity. These factors are generally difficult to express with exact numerical values. The main objective of this article is to build a daily water intake recommendation system using fuzzy methods. This system will use age, physical activity, and a...

  15. An expert system for emergency response

    International Nuclear Information System (INIS)

    Sebo, D.

    1989-01-01

    An expert system, the Reactor Safety Assessment System (RSAS), is being developed by the Idaho National Engineering Laboratory and the US Nuclear Regulatory Commission (NRC) for the NRC Operations Center. The RSAS is intended to aid the reactor safety team (RST) at the operations center in monitoring and projecting core and containment status during an emergency at a licensed nuclear power plant. The RSAS system development has two major aspects. The first is the compilation and storage of knowledge required for RST assessment tasks. The knowledge structure used by RSAS is a goal tree-success tree (GTST) model. The upper level structure of the GTST model is generic in nature. This allows development of models for generic plant-specific GTST models. The second aspect of the RSAS is the development of inferencing techniques for the access, display, and manipulation of the knowledge to meet RST requirements in a real-time manner during the activation of the operations center. This objective is achieved by critical safety function and success path monitoring. This basic strategy is used to determine the current status and estimate future challenges to the status of the reactor, identify procedures and equipment required to maintain or regain the critical safety functions, identify critical equipment, determine information requirements, and display pertinent information concerning current reactor status

  16. An expert system for steam generator maintenance

    International Nuclear Information System (INIS)

    Remond, A.

    1988-01-01

    The tube bundles in PWR steam generators are, by far, the major source of problems whether they are due to primary and secondary side corrosion mechanisms or to tube vibration-induced wear at tube support locations. Because of differences in SG operating, materials, and fabrication processes, the damage may differ from steam generator to steam generator. MPGV, an expert system for steam generator maintenance uses all steam generator data containing data on materials, fabrication processes, inservice inspection, and water chemistry. It has access to operational data for individual steam generators and contains models of possible degradation mechanisms. The objectives of the system are: · Diagnosing the most probable degradation mechanism or mechanisms by reviewing the entire steam generator history. · Identifying the tubes most exposed to future damage and evaluating the urgency of repair by simulating the probable development of the problem in time. · Establishing the appropriate preventive actions such as repair, inspection or other measures and establishing an action schedule. The system is intended for utilities either for individual plants before each inspection outage or any time an incident occurs or for a set of plants through a central MPGV center. (author)

  17. Expert System Models for Forecasting Forklifts Engagement in a Warehouse Loading Operation: A Case Study

    Directory of Open Access Journals (Sweden)

    Dejan Mirčetić

    2016-08-01

    Full Text Available The paper focuses on the problem of forklifts engagement in warehouse loading operations. Two expert system (ES models are created using several machine learning (ML models. Models try to mimic expert decisions while determining the forklifts engagement in the loading operation. Different ML models are evaluated and adaptive neuro fuzzy inference system (ANFIS and classification and regression trees (CART are chosen as the ones which have shown best results for the research purpose. As a case study, a central warehouse of a beverage company was used. In a beverage distribution chain, the proper engagement of forklifts in a loading operation is crucial for maintaining the defined customer service level. The created ES models represent a new approach for the rationalization of the forklifts usage, particularly for solving the problem of the forklifts engagement incargo loading. They are simple, easy to understand, reliable, and practically applicable tool for deciding on the engagement of the forklifts in a loading operation.

  18. A demonstration of expert systems applications in transportation engineering : volume III, evaluation of the prototype expert system TRANZ.

    Science.gov (United States)

    1990-01-01

    The validation and evaluation of an expert system for traffic control in highway work zones (TRANZ) is described. The stages in the evaluation process consisted of the following: revisit the experts, selectively distribute copies of TRANZ with docume...

  19. Developing a fuzzy rule based cognitive map for total system safety assessment

    International Nuclear Information System (INIS)

    Lemos, Francisco Luiz de; Sullivan, Terry

    2007-01-01

    Total System Performance Assessment, TSPA, for radioactive waste disposal is a multi and interdisciplinary task that is characterized by complex interactions between parameters and processes; lack of data; and ignorance regarding natural processes and conditions. The vagueness in the determination of ranges of values of parameters and identification of interacting processes pose further difficulties to the analysts with regard to the establishment of the relations between processes and parameters. More specifically the vagueness makes uncertainty propagation and sensitivity analysis challenging to analyze. To cope with these difficulties experts often use simplifications and linguistic terms to express their state of knowledge about a certain situation. For example, experts use terms such as 'low pH', 'very unlikely', etc to describe their perception about natural processes or conditions. In this work we propose the use of Fuzzy Cognitive Maps, FCM, for representation of interrelation between processes and parameters as well as to promote a better understanding of the system performance. Fuzzy cognitive maps are suited for the case where the causal relations are not clearly defined and, therefore, can not be represented by crisp values. In other words, instead of representing the quality of the interactions by crisp values, they are assigned degrees of truth. For example, we can assign values to the effect of one process on another such that (+) 1 corresponds to positive, (-) 1 to negative and 0 to neutral effects respectively. In this case the effect of a process A, on a process, B, can be depicted as function of the membership to the fuzzy set 'causal effect' of the cause process to the target one. One of the main advantages of this methodology would be that it allows one to aggregate the linguistic expressions as descriptions of processes. For example, a process can be known to have a 'very strong' positive effect on another one, or using fuzzy sets terminology

  20. Expert system to control a fusion energy experiment

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, R.R.; Canales, T.; Lager, D.

    1986-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques by encoding the behavior of several experts as a set of if-then rules in an expert system. One of the functions of the expert system is to control an adaptive controller that, in turn, controls the neutral beam source. The architecture of the system is presented followed by a description of its performance.

  1. Expert system to control a fusion energy experiment

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.; Lager, D.

    1986-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques by encoding the behavior of several experts as a set of if-then rules in an expert system. One of the functions of the expert system is to control an adaptive controller that, in turn, controls the neutral beam source. The architecture of the system is presented followed by a description of its performance

  2. Trans-skull ultrasonic Doppler system aided by fuzzy logic

    Science.gov (United States)

    Hata, Yutaka; Nakamura, Masato; Yagi, Naomi; Ishikawa, Tomomoto

    2012-06-01

    This paper describes a trans-skull ultrasonic Doppler system for measuring the blood flow direction in brain under skull. In this system, we use an ultrasonic array probe with the center frequency of 1.0 MHz. The system determines the fuzzy degree of blood flow by Doppler Effect, thereby it locates blood vessel. This Doppler Effect is examined by the center of gravity shift of the frequency magnitudes. In in-vitro experiment, a cow bone was employed as the skull, and three silicon tubes were done as blood vessels, and bubble in water as blood. We received the ultrasonic waves through a protein, the skull and silicon tubes in order. In the system, fuzzy degrees are determined with respect to the Doppler shift, amplitude of the waves and attenuation of the tissues. The fuzzy degrees of bone and blood direction are calculated by them. The experimental results showed that the system successfully visualized the skull and flow direction, compared with the location and flow direction of the phantom. Thus, it detected the flow direction by Doppler Effect under skull, and automatically extracted the region of skull and blood vessel.

  3. Expert-systems and computer-based industrial systems

    International Nuclear Information System (INIS)

    Terrien, J.F.

    1987-01-01

    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)

  4. Analysis of inventory difference using fuzzy controllers

    International Nuclear Information System (INIS)

    Zardecki, A.

    1994-01-01

    The principal objectives of an accounting system for safeguarding nuclear materials are as follows: (a) to provide assurance that all material quantities are present in the correct amount; (b) to provide timely detection of material loss; and (c) to estimate the amount of any loss and its location. In fuzzy control, expert knowledge is encoded in the form of fuzzy rules, which describe recommended actions for different classes of situations represented by fuzzy sets. The concept of a fuzzy controller is applied to the forecasting problem in a time series, specifically, to forecasting and detecting anomalies in inventory differences. This paper reviews the basic notion underlying the fuzzy control systems and provides examples of application. The well-known material-unaccounted-for diffusion plant data of Jaech are analyzed using both feedforward neural networks and fuzzy controllers. By forming a deference between the forecasted and observed signals, an efficient method to detect small signals in background noise is implemented

  5. A hybrid fuzzy-ontology based intelligent system to determine level of severity and treatment recommendation for Benign Prostatic Hyperplasia.

    Science.gov (United States)

    Torshizi, Abolfazl Doostparast; Zarandi, Mohammad Hossein Fazel; Torshizi, Ghazaleh Doostparast; Eghbali, Kamyar

    2014-01-01

    This paper deals with application of fuzzy intelligent systems in diagnosing severity level and recommending appropriate therapies for patients having Benign Prostatic Hyperplasia. Such an intelligent system can have remarkable impacts on correct diagnosis of the disease and reducing risk of mortality. This system captures various factors from the patients using two modules. The first module determines severity level of the Benign Prostatic Hyperplasia and the second module, which is a decision making unit, obtains output of the first module accompanied by some external knowledge and makes an appropriate treatment decision based on its ontology model and a fuzzy type-1 system. In order to validate efficiency and accuracy of the developed system, a case study is conducted by 44 participants. Then the results are compared with the recommendations of a panel of experts on the experimental data. Then precision and accuracy of the results were investigated based on a statistical analysis. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. Expert systems for real-time monitoring and fault diagnosis

    Science.gov (United States)

    Edwards, S. J.; Caglayan, A. K.

    1989-01-01

    Methods for building real-time onboard expert systems were investigated, and the use of expert systems technology was demonstrated in improving the performance of current real-time onboard monitoring and fault diagnosis applications. The potential applications of the proposed research include an expert system environment allowing the integration of expert systems into conventional time-critical application solutions, a grammar for describing the discrete event behavior of monitoring and fault diagnosis systems, and their applications to new real-time hardware fault diagnosis and monitoring systems for aircraft.

  7. Expert system for liquid low-level waste management

    International Nuclear Information System (INIS)

    Ferrada, J.J.

    1992-01-01

    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

  8. Hybrid ellipsoidal fuzzy systems in forecasting regional electricity loads

    Energy Technology Data Exchange (ETDEWEB)

    Pai, Ping-Feng [Department of Information Management, National Chi Nan University, 1 University Road, Puli, Nantou 545, Taiwan (China)

    2006-09-15

    Because of the privatization of electricity in many countries, load forecasting has become one of the most crucial issues in the planning and operations of electric utilities. In addition, accurate regional load forecasting can provide the transmission and distribution operators with more information. The hybrid ellipsoidal fuzzy system was originally designed to solve control and pattern recognition problems. The main objective of this investigation is to develop a hybrid ellipsoidal fuzzy system for time series forecasting (HEFST) and apply the proposed model to forecast regional electricity loads in Taiwan. Additionally, a scaled conjugate gradient learning method is employed in the supervised learning phase of the HEFST model. Subsequently, numerical data taken from the existing literature is used to demonstrate the forecasting performance of the HEFST model. Simulation results reveal that the proposed model has better forecasting performance than the artificial neural network model and the regression model. Thus, the HEFST model is a valid and promising alternative for forecasting regional electricity loads. (author)

  9. Evolutionary Computation and Its Applications in Neural and Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Biaobiao Zhang

    2011-01-01

    Full Text Available Neural networks and fuzzy systems are two soft-computing paradigms for system modelling. Adapting a neural or fuzzy system requires to solve two optimization problems: structural optimization and parametric optimization. Structural optimization is a discrete optimization problem which is very hard to solve using conventional optimization techniques. Parametric optimization can be solved using conventional optimization techniques, but the solution may be easily trapped at a bad local optimum. Evolutionary computation is a general-purpose stochastic global optimization approach under the universally accepted neo-Darwinian paradigm, which is a combination of the classical Darwinian evolutionary theory, the selectionism of Weismann, and the genetics of Mendel. Evolutionary algorithms are a major approach to adaptation and optimization. In this paper, we first introduce evolutionary algorithms with emphasis on genetic algorithms and evolutionary strategies. Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. Some topics pertaining to evolutionary algorithms are also discussed, and a comparison between evolutionary algorithms and simulated annealing is made. Finally, the application of EAs to the learning of neural networks as well as to the structural and parametric adaptations of fuzzy systems is also detailed.

  10. Solution of a System of Linear Equations with Fuzzy Numbers

    Czech Academy of Sciences Publication Activity Database

    Horčík, Rostislav

    2008-01-01

    Roč. 159, č. 14 (2008), s. 1788-1810 ISSN 0165-0114 R&D Projects: GA AV ČR KJB100300502 Institutional research plan: CEZ:AV0Z10300504 Keywords : fuzzy number * fuzzy interval * interval analysis * fuzzy arithmetic * fuzzy class theory * united solution set Subject RIV: BA - General Mathematics Impact factor: 1.833, year: 2008

  11. Fuzzy model-based servo and model following control for nonlinear systems.

    Science.gov (United States)

    Ohtake, Hiroshi; Tanaka, Kazuo; Wang, Hua O

    2009-12-01

    This correspondence presents servo and nonlinear model following controls for a class of nonlinear systems using the Takagi-Sugeno fuzzy model-based control approach. First, the construction method of the augmented fuzzy system for continuous-time nonlinear systems is proposed by differentiating the original nonlinear system. Second, the dynamic fuzzy servo controller and the dynamic fuzzy model following controller, which can make outputs of the nonlinear system converge to target points and to outputs of the reference system, respectively, are introduced. Finally, the servo and model following controller design conditions are given in terms of linear matrix inequalities. Design examples illustrate the utility of this approach.

  12. Expert system characteristics and potential applications in safeguards

    International Nuclear Information System (INIS)

    Chapman, L.D.

    1986-01-01

    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

  13. Diagnosis - Using automatic test equipment and artificial intelligence expert systems

    Science.gov (United States)

    Ramsey, J. E., Jr.

    Three expert systems (ATEOPS, ATEFEXPERS, and ATEFATLAS), which were created to direct automatic test equipment (ATE), are reviewed. The purpose of the project was to develop an expert system to troubleshoot the converter-programmer power supply card for the F-15 aircraft and have that expert system direct the automatic test equipment. Each expert system uses a different knowledge base or inference engine, basing the testing on the circuit schematic, test requirements document, or ATLAS code. Implementing generalized modules allows the expert systems to be used for any different unit under test. Using converted ATLAS to LISP code allows the expert system to direct any ATE using ATLAS. The constraint propagated frame system allows for the expansion of control by creating the ATLAS code, checking the code for good software engineering techniques, directing the ATE, and changing the test sequence as needed (planning).

  14. A Fuzzy Control System for Inductive Video Games

    OpenAIRE

    Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo; Flores, Juan; Fuentes, Maria

    2017-01-01

    It has been shown that the emotional state of students has an important relationship with learning; for instance, engaged concentration is positively correlated with learning. This paper proposes the Inductive Control (IC) for educational games. Unlike conventional approaches that only modify the game level, the proposed technique also induces emotions in the player for supporting the learning process. This paper explores a fuzzy system that analyzes the players' performance and their emotion...

  15. A Fuzzy Logic System to Analyze a Student's Lifestyle

    OpenAIRE

    Ghosh, Sourish; Boob, Aaditya Sanjay; Nikhil, Nishant; Vysyaraju, Nayan Raju; Kumar, Ankit

    2016-01-01

    A college student's life can be primarily categorized into domains such as education, health, social and other activities which may include daily chores and travelling time. Time management is crucial for every student. A self realisation of one's daily time expenditure in various domains is therefore essential to maximize one's effective output. This paper presents how a mobile application using Fuzzy Logic and Global Positioning System (GPS) analyzes a student's lifestyle and provides recom...

  16. Switch Reluctance Motor Control Based on Fuzzy Logic System

    Directory of Open Access Journals (Sweden)

    S. V. Aleksandrovsky

    2012-01-01

    Full Text Available Due to its intrinsic simplicity and reliability, the switched reluctance motor (SRM has now become a promising candidate for variable-speed drive applications as an alternative induction motor in various industrial application. However, the SRM has the disadvantage of nonlinear characteristic and control. It is suggested to use controller based on fuzzy logic system. Design of FLS controller and simulation model presented.

  17. CHEBYSHEV ACCELERATION TECHNIQUE FOR SOLVING FUZZY LINEAR SYSTEM

    Directory of Open Access Journals (Sweden)

    S.H. Nasseri

    2011-07-01

    Full Text Available In this paper, Chebyshev acceleration technique is used to solve the fuzzy linear system (FLS. This method is discussed in details and followed by summary of some other acceleration techniques. Moreover, we show that in some situations that the methods such as Jacobi, Gauss-Sidel, SOR and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrated by some numerical examples.

  18. CHEBYSHEV ACCELERATION TECHNIQUE FOR SOLVING FUZZY LINEAR SYSTEM

    Directory of Open Access Journals (Sweden)

    S.H. Nasseri

    2009-10-01

    Full Text Available In this paper, Chebyshev acceleration technique is used to solve the fuzzy linear system (FLS. This method is discussed in details and followed by summary of some other acceleration techniques. Moreover, we show that in some situations that the methods such as Jacobi, Gauss-Sidel, SOR and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrated by some numerical examples.

  19. Intelligent control-I: review of fuzzy logic and fuzzy set theory

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    In the past decade or so, fuzzy systems have supplanted conventional technologies in many engineering systems, in particular in control systems and pattern recognition. Fuzzy logic has found applications in a variety of consumer products e.g. washing machines, camcorders, digital cameras, air conditioners, subway trains, cement kilns and many others. The fuzzy technology is also being applied in information technology, where it provides decision-support and expert systems with powerful reasoning capabilities. Fuzzy sets, introduced by Zadeh in 1965 as a mathematical way to represent vagueness in linguistics, can be considered a generalisation of classical set theory. Fuzziness is often confused with probability. This lecture will introduce the principal concepts and mathematical notions of fuzzy set theory. (author)

  20. Fuzzy Risk Analysis for a Production System Based on the Nagel Point of a Triangle

    Directory of Open Access Journals (Sweden)

    Handan Akyar

    2016-01-01

    Full Text Available Ordering and ranking fuzzy numbers and their comparisons play a significant role in decision-making problems such as social and economic systems, forecasting, optimization, and risk analysis problems. In this paper, a new method for ordering triangular fuzzy numbers using the Nagel point of a triangle is presented. With the aid of the proposed method, reasonable properties of ordering fuzzy numbers are verified. Certain comparative examples are given to illustrate the advantages of the new method. Many papers have been devoted to studies on fuzzy ranking methods, but some of these studies have certain shortcomings. The proposed method overcomes the drawbacks of the existing methods in the literature. The suggested method can order triangular fuzzy numbers as well as crisp numbers and fuzzy numbers with the same centroid point. An application to the fuzzy risk analysis problem is given, based on the suggested ordering approach.

  1. Handbook of VLSI chip design and expert systems

    CERN Document Server

    Schwarz, A F

    1993-01-01

    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.

  2. Expert System Applications for the Electric Power Industry: Proceedings

    International Nuclear Information System (INIS)

    1992-06-01

    A conference on Expert System Applications for the Electric Power Industry was held in Boston on September 8--11, 1991 to provide a forum for technology transfer, technical information exchange, and education. The conference was attended by more than 150 representatives of electric utilities, equipment manufacturers, engineering consulting organizations, universities, national laboratories, and government agencies. The meeting included a keynote address, 70 papers, and 18 expert system demonstrations. Sessions covered expert systems in power system planning operations, fossil power plant applications, nuclear power plant applications, and intelligent user interfaces. The presentations showed how expert systems can provide immediate benefits to the electric power industry in many applications. Individual papers are indexed separately

  3. A Fuzzy Semantic Information Retrieval System for Transactional Applications

    Directory of Open Access Journals (Sweden)

    A O Ajayi

    2009-09-01

    Full Text Available In this paper, we present an information retrieval system based on the concept of fuzzy logic to relate vague and uncertain objects with un-sharp boundaries. The simple but comprehensive user interface of the system permits the entering of uncertain specifications in query forms. The system was modelled and simulated in a Matlab environment; its implementation was carried out using Borland C++ Builder. The result of the performance measure of the system using precision and recall rates is encouraging. Similarly, the smaller amount of more precise information retrieved by the system will positively impact the response time perceived by the users.

  4. Periodicity of a class of nonlinear fuzzy systems with delays

    International Nuclear Information System (INIS)

    Yu Jiali; Yi Zhang; Zhang Lei

    2009-01-01

    The well known Takagi-Sugeno (T-S) model gives an effective method to combine some simple local systems with their linguistic description to represent complex nonlinear dynamic systems. By using the T-S method, a class of local nonlinear systems having nice dynamic properties can be employed to represent some global complex nonlinear systems. This paper proposes to study the periodicity of a class of global nonlinear fuzzy systems with delays by using T-S method. Conditions for guaranteeing periodicity are derived. Examples are employed to illustrate the theory.

  5. Expert System Techniques and Applications in AEC-Design

    DEFF Research Database (Denmark)

    Andersen, Tom

    This part of a book presents expert system techniques applicable to building design and construction, and it reports and evaluates on systems developed in thar domain.......This part of a book presents expert system techniques applicable to building design and construction, and it reports and evaluates on systems developed in thar domain....

  6. A new type of simplified fuzzy rule-based system

    Science.gov (United States)

    Angelov, Plamen; Yager, Ronald

    2012-02-01

    Over the last quarter of a century, two types of fuzzy rule-based (FRB) systems dominated, namely Mamdani and Takagi-Sugeno type. They use the same type of scalar fuzzy sets defined per input variable in their antecedent part which are aggregated at the inference stage by t-norms or co-norms representing logical AND/OR operations. In this paper, we propose a significantly simplified alternative to define the antecedent part of FRB systems by data Clouds and density distribution. This new type of FRB systems goes further in the conceptual and computational simplification while preserving the best features (flexibility, modularity, and human intelligibility) of its predecessors. The proposed concept offers alternative non-parametric form of the rules antecedents, which fully reflects the real data distribution and does not require any explicit aggregation operations and scalar membership functions to be imposed. Instead, it derives the fuzzy membership of a particular data sample to a Cloud by the data density distribution of the data associated with that Cloud. Contrast this to the clustering which is parametric data space decomposition/partitioning where the fuzzy membership to a cluster is measured by the distance to the cluster centre/prototype ignoring all the data that form that cluster or approximating their distribution. The proposed new approach takes into account fully and exactly the spatial distribution and similarity of all the real data by proposing an innovative and much simplified form of the antecedent part. In this paper, we provide several numerical examples aiming to illustrate the concept.

  7. An examination of expert systems activities within the nuclear industry

    International Nuclear Information System (INIS)

    Bernard, J.A.; Washio, Takashi.

    1988-01-01

    This paper provides an overview of a detailed evaluation that the authors recently completed on expert systems applications within the nuclear industry. That evaluation examined the motivation for utilizing expert systems, identified the areas to which they were being applied, and provided an assessment of their utility. Listed here are some of the salient findings of that report. (1) Utilities are developing their own artificial intelligence tools rather than using commercial products. (2) Few expert systems are being developed for the express purpose of capturing human expertise. (3) A number of successful expert systems have been developed to assist in plant design, management, and maintenance scheduling. (4) Interactive diagnostic systems are being developed for the analysis of physical processes that vary slowly. (5) Real-time diagnostic expert systems are currently at the cutting edge of the technology. (6) Operator adviser and emergency response expert systems constitute ∼25% of the total. (7) Research on the use of expert systems for reactor control is quite active. (8) Too few quantitative evaluations of the benefits of expert systems to reactor operators have been performed. The operator's need is for timely, factual information on plant status. Hence, the true challenge to expert systems is real-time diagnostics

  8. Expert system for accelerator single-freedom nonlinear components

    International Nuclear Information System (INIS)

    Wang Sheng; Xie Xi; Liu Chunliang

    1995-01-01

    An expert system by Arity Prolog is developed for accelerator single-freedom nonlinear components. It automatically yields any order approximate analytical solutions for various accelerator single-freedom nonlinear components. As an example, the eighth order approximate analytical solution is derived by this expert system for a general accelerator single-freedom nonlinear component, showing that the design of the expert system is successful

  9. Fuzzy assessment of health information system users' security awareness.

    Science.gov (United States)

    Aydın, Özlem Müge; Chouseinoglou, Oumout

    2013-12-01

    Health information systems (HIS) are a specific area of information systems (IS), where critical patient data is stored and quality health service is only realized with the correct use and efficient dissemination of this data to health workers. Therefore, a balance needs to be established between the levels of security and flow of information on HIS. Instead of implementing higher levels and further mechanisms of control to increase the security of HIS, it is preferable to deal with the arguably weakest link on HIS chain with respect to security: HIS users. In order to provide solutions and approaches for transforming users to the first line of defense in HIS but also to employ capable and appropriate candidates from the pool of newly graduated students, it is important to assess and evaluate the security awareness levels and characteristics of these existing and future users. This study aims to provide a new perspective to understand the phenomenon of security awareness of HIS users with the use of fuzzy analysis, and to assess the present situation of current and future HIS users of a leading medical and educational institution of Turkey, with respect to their security characteristics based on four different security scales. The results of the fuzzy analysis, the guide on how to implement this fuzzy analysis to any health institution and how to read and interpret these results, together with the possible implications of these results to the organization are provided.

  10. A Temporal Fuzzy Logic Formalism for Knowledge Based Systems

    Directory of Open Access Journals (Sweden)

    Vasile MAZILESCU

    2012-11-01

    Full Text Available This paper shows that the influence of knowledge on new forms of work organisation can be described as mutual relationships. Different changes in work organisation also have a strong influence on the increasing importance of knowledge of different individual and collective actors in working situations. After that, we characterize a piece of basic formal system, an Extended Fuzzy Logic System (EFLS with temporal attributes, to conceptualize future DKMSs based on human imprecise for distributed just in time decisions. The approximate reasoning is perceived as a derivation of new formulas with the corresponding temporal attributes, within a fuzzy theory defined by the fuzzy set of special axioms. In a management application, the reasoning is evolutionary because of unexpected events which may change the state of the DKMS. In this kind of situations it is necessary to elaborate certain mechanisms in order to maintain the coherence of the obtained conclusions, to figure out their degree of reliability and the time domain for which these are true. These last aspects stand as possible further directions of development at a basic logic level for future technologies that must automate knowledge organizational processes.

  11. Expert systems for plant operations training and assistance

    International Nuclear Information System (INIS)

    Pack, R.W.; Lazar, P.M.; Schmidt, R.V.; Gaddy, C.D.

    1988-01-01

    The project described in this paper explored the use of expert systems for plant operations training and assistance. Three computer technologies were reviewed: computer-aided instruction, expert systems, and expert training systems (ETS). The technology of CAI has been developed since the early 1960s, and a wide range of applications are available commercially today. Expert systems have been developed primarily as job performance aids, and the number of commercial applications is increasing. A fully developed ETS has models of the trainer and trainee, in addition to a knowledge base

  12. Feedforward Tracking Control of Flat Recurrent Fuzzy Systems

    International Nuclear Information System (INIS)

    Gering, Stefan; Adamy, Jürgen

    2014-01-01

    Flatness based feedforward control has proven to be a feasible solution for the problem of tracking control, which may be applied to a broad class of nonlinear systems. If a flat output of the system is known, the control is often based on a feedforward controller generating a nominal input in combination with a linear controller stabilizing the linearized error dynamics around the trajectory. We show in this paper that the very same idea may be incorporated for tracking control of MIMO recurrent fuzzy systems. Their dynamics is given by means of linguistic differential equations but may be converted into a hybrid system representation, which then serves as the basis for controller synthesis

  13. Feedforward Tracking Control of Flat Recurrent Fuzzy Systems

    Science.gov (United States)

    Gering, Stefan; Adamy, Jürgen

    2014-12-01

    Flatness based feedforward control has proven to be a feasible solution for the problem of tracking control, which may be applied to a broad class of nonlinear systems. If a flat output of the system is known, the control is often based on a feedforward controller generating a nominal input in combination with a linear controller stabilizing the linearized error dynamics around the trajectory. We show in this paper that the very same idea may be incorporated for tracking control of MIMO recurrent fuzzy systems. Their dynamics is given by means of linguistic differential equations but may be converted into a hybrid system representation, which then serves as the basis for controller synthesis.

  14. Geo-Spatial Tactical Decision Aid Systems: Fuzzy Logic for Supporting Decision Making

    National Research Council Canada - National Science Library

    Grasso, Raffaele; Giannecchini, Simone

    2006-01-01

    .... This paper describes a tactical decision aid system based on fuzzy logic reasoning for data fusion and on current Open Geospatial Consortium specifications for interoperability, data dissemination...

  15. Chaotic System Identification Based on a Fuzzy Wiener Model with Particle Swarm Optimization

    International Nuclear Information System (INIS)

    Yong, Li; Ying-Gan, Tang

    2010-01-01

    A fuzzy Wiener model is proposed to identify chaotic systems. The proposed fuzzy Wiener model consists of two parts, one is a linear dynamic subsystem and the other is a static nonlinear part, which is represented by the Takagi–Sugeno fuzzy model. Identification of chaotic systems is converted to find optimal parameters of the fuzzy Wiener model by minimizing the state error between the original chaotic system and the fuzzy Wiener model. Particle swarm optimization algorithm, a global optimizer, is used to search the optimal parameter of the fuzzy Wiener model. The proposed method can identify the parameters of the linear part and nonlinear part simultaneously. Numerical simulations for Henón and Lozi chaotic system identification show the effectiveness of the proposed method

  16. EPRI expert system activities for nuclear utility industry application

    International Nuclear Information System (INIS)

    Naser, J.A.

    1990-01-01

    This paper reports on expert systems which have reached a level of maturity where they offer considerable benefits for the nuclear utility industry. The ability of expert systems to enhance expertise makes them an important tool for the nuclear utility industry in the areas of engineering, operations and maintenance. Benefits of expert system applications include comprehensive and consistent reasoning, reduction of time required for activities, retention of human expertise and ability to utilize multiple experts knowledge for an activity. The Electric Power Research Institute (EPRI) has been performing four basic activities to help the nuclear industry take advantage of this expert system technology. The first is the development of expert system building tools which are tailored to nuclear utility industry applications. The second is the development of expert system applications. The third is work in developing a methodology for verification and validation of expert systems. The last is technology transfer activities to help the nuclear utility industry benefit from expert systems. The purpose of this paper is to describe the EPRI activities

  17. An Efficient Expert System Generator for Qualitative Feed-Back Loop Analysis

    Directory of Open Access Journals (Sweden)

    Manoj Kumar Jain

    2012-04-01

    Full Text Available Quite often the variables used in system analysis are qualitative in nature. They cannot be defined precisely, whereas software development for system analysis needs a mathematical framework with precise computations. It is not trivial to capture the uncertainty in the system.
    Fuzzy sets provide us the facility to capture the uncertainty in the system. In normal crisp set where the membership of an element is always certain in a sense that it would be member or not of the given set. In contrast to this a membership functions or possibility (ranging from 0 to 1, including both values is assigned with each member. System analysis is done through system dynamics which is not very efficient. We present an efficient technique to generate expert system using fuzzy set. In our proposed approach five linguistic qualifiers are used for each variable, namely, Very Low (VL, Low (L, Medium (M, High (H, and Very High
    (VH. We capture the influence or feedback in the system with the help of if then else rules and matrices are generated for them which are used for analysis. Complete methodology and its applicability are presented here.

  18. Stability Analysis of Positive Polynomial Fuzzy-Model-Based Control Systems with Time Delay under Imperfect Premise Matching

    OpenAIRE

    Li, Xiaomiao; Lam, Hak Keung; Song, Ge; Liu, Fucai

    2017-01-01

    This paper deals with the stability and positivity analysis of polynomial-fuzzy-model-based ({PFMB}) control systems with time delay, which is formed by a polynomial fuzzy model and a polynomial fuzzy controller connected in a closed loop, under imperfect premise matching. To improve the design and realization flexibility, the polynomial fuzzy model and the polynomial fuzzy controller are allowed to have their own set of premise membership functions. A sum-of-squares (SOS)-based stability ana...

  19. Robust Takagi-Sugeno Fuzzy Dynamic Regulator for Trajectory Tracking of a Pendulum-Cart System

    Directory of Open Access Journals (Sweden)

    Miguel A. Llama

    2015-01-01

    Full Text Available Starting from a nonlinear model for a pendulum-cart system, on which viscous friction is considered, a Takagi-Sugeno (T-S fuzzy augmented model (TSFAM as well as a TSFAM with uncertainty (TSFAMwU is proposed. Since the design of a T-S fuzzy controller is based on the T-S fuzzy model of the nonlinear system, then, to address the trajectory tracking problem of the pendulum-cart system, three T-S fuzzy controllers are proposed via parallel distributed compensation: (1 a T-S fuzzy servo controller (TSFSC designed from the TSFAM; (2 a robust TSFSC (RTSFSC designed from the TSFAMwU; and (3 a robust T-S fuzzy dynamic regulator (RTSFDR designed from the RTSFSC with the addition of a T-S fuzzy observer, which estimates cart and pendulum velocities. Both TSFAM and TSFAMwU are comprised of two fuzzy rules and designed via local approximation in fuzzy partition spaces technique. Feedback gains for the three fuzzy controllers are obtained via linear matrix inequalities approach. A swing-up controller is developed to swing the pendulum up from its pendant position to its upright position. Real-time experiments validate the effectiveness of the proposed schemes, keeping the pendulum in its upright position while the cart follows a reference signal, standing out the RTSFDR.

  20. Fuzzy inference system for evaluating and improving nuclear power plant operating performance

    International Nuclear Information System (INIS)

    Guimaraes, Antonio Cesar F.; Lapa, Celso Marcelo Franklin

    2003-01-01

    This paper presents a fuzzy inference system (FIS) as an approach to estimate Nuclear Power Plant (NPP) performance indicators. The performance indicators for this study are the energy availability factor (EAF) and the planned (PUF) and unplanned unavailability factor (UUF). These indicators are obtained from a non analytical combination among the same operational parameters. Such parameters are, for example, environment impacts, industrial safety, radiological protection, safety indicators, scram rate, thermal efficiency, and fuel reliability. This approach uses the concept of a pure fuzzy logic system where the fuzzy rule base consists of a collection of fuzzy IF-THEN rules. The fuzzy inference engine uses these fuzzy IF-THEN rules to determine a mapping from fuzzy sets in the input universe of discourse to fuzzy sets in the output universe of discourse based on fuzzy logic principles. The results demonstrated the potential of the fuzzy inference to generate a knowledge basis that correlate operations occurrences and NPP performance. The inference system became possible the development of the sensitivity studies, future operational condition previsions and may support the eventual corrections on operation of the plant

  1. Expert systems - basic principles and possible applications in nuclear energy

    International Nuclear Information System (INIS)

    Cain, D.G.; Schmidt, F.

    1987-01-01

    One of the primary goals of the application of mathematical methods and computational techniques in reactor physics is the effective and accurate solution of the neutron diffusion equation under various conditions. To reach this goal still requires much skill, experience, knowledge and imagination as can be seen from various contributions at this and other conferences. Experts are necessary. Will expert systems replace them. We shall discuss this question by describing the basic principles of problem solving by expert systems as compared to problem solving by mathematical and computational methods. From this we shall identify areas of possible applications of the new techniques in nuclear energy and develop some thoughts on present limitations. As a result we conclude that expert systems will not be able to replace experts as long as the experts use the systems to improve their own expertise

  2. Fuzzy Logic Based Autonomous Parallel Parking System with Kalman Filtering

    Science.gov (United States)

    Panomruttanarug, Benjamas; Higuchi, Kohji

    This paper presents an emulation of fuzzy logic control schemes for an autonomous parallel parking system in a backward maneuver. There are four infrared sensors sending the distance data to a microcontroller for generating an obstacle-free parking path. Two of them mounted on the front and rear wheels on the parking side are used as the inputs to the fuzzy rules to calculate a proper steering angle while backing. The other two attached to the front and rear ends serve for avoiding collision with other cars along the parking space. At the end of parking processes, the vehicle will be in line with other parked cars and positioned in the middle of the free space. Fuzzy rules are designed based upon a wall following process. Performance of the infrared sensors is improved using Kalman filtering. The design method needs extra information from ultrasonic sensors. Starting from modeling the ultrasonic sensor in 1-D state space forms, one makes use of the infrared sensor as a measurement to update the predicted values. Experimental results demonstrate the effectiveness of sensor improvement.

  3. AN EXPERT SYSTEM FOR SUPPORTING THE PRODUCTION OF PLEASURE BOATS

    Directory of Open Access Journals (Sweden)

    Tomasz GONCIARZ

    2013-07-01

    Full Text Available Expert systems can be defined as computer programs, whose main task is to simulate a human expert, usually in a narrow field of expertise. Possible applications of modern information technology are very extensive, ranging from medicine, geology and technology to applications in the field of economic and financial decision support. The purpose of this paper is to present the practical application of an expert system that supports the process of managing the production of yachts and has a high suitability for use in this application. Using the expert system described in the paper reduces the time during the design and production preparation process.

  4. An improved fuzzy Kalman filter for state estimation of nonlinear systems

    International Nuclear Information System (INIS)

    Zhou, Z-J; Hu, C-H; Chen, L; Zhang, B-C

    2008-01-01

    The extended fuzzy Kalman filter (EFKF) is developed recently and used for state estimation of the nonlinear systems with uncertainty. Based on extension of the orthogonality principle and the extended fuzzy Kalman filter, an improved fuzzy Kalman filters (IFKF) is proposed in this paper, which is more applicable and can deal with the state estimation of the nonlinear systems better than the EFKF. A simulation study is provided to verify the efficiency of the proposed method

  5. Application of fuzzy inference system to increase efficiency of management decision-making in agricultural enterprises

    OpenAIRE

    Balanovskаya, Tetiana Ivanovna; Boretska, Zoreslava Petrovna

    2014-01-01

    Application of fuzzy inference system to increase efficiency of management decision- making in agricultural enterprises. Theoretical and methodological issues, practical recommendations on improvement of management decision-making in agricultural enterprises to increase their competitiveness have been intensified and developed in the article. A simulation example of a quality management system for agricultural products on the basis of the theory of fuzzy sets and fuzzy logic has been proposed...

  6. Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

    Science.gov (United States)

    Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

    2017-10-03

    This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

  7. Fuzzy Stabilization for Nonlinear Discrete Ship Steering Stochastic Systems Subject to State Variance and Passivity Constraints

    Directory of Open Access Journals (Sweden)

    Wen-Jer Chang

    2014-01-01

    Full Text Available For nonlinear discrete-time stochastic systems, a fuzzy controller design methodology is developed in this paper subject to state variance constraint and passivity constraint. According to fuzzy model based control technique, the nonlinear discrete-time stochastic systems considered in this paper are represented by the discrete-time Takagi-Sugeno fuzzy models with multiplicative noise. Employing Lyapunov stability theory, upper bound covariance control theory, and passivity theory, some sufficient conditions are derived to find parallel distributed compensation based fuzzy controllers. In order to solve these sufficient conditions, an iterative linear matrix inequality algorithm is applied based on the linear matrix inequality technique. Finally, the fuzzy stabilization problem for nonlinear discrete ship steering stochastic systems is investigated in the numerical example to illustrate the feasibility and validity of proposed fuzzy controller design method.

  8. Fuzzy Modeling and Synchronization of a New Hyperchaotic Complex System with Uncertainties

    Directory of Open Access Journals (Sweden)

    Hadi Delavari

    2015-07-01

    Full Text Available In this paper, the synchronization of a new hyperchaotic complex system based on T-S fuzzy model is proposed. First the considered hyperchaotic system is represented by T-S fuzzy model equivalently. Then by using the parallel distributed compensation (PDC method and by applying linear system theory and exact linearization (EL technique, a fuzzy controller is designed to realize the synchronization. Finally, simulation results are carried out to demonstrate the performance of our proposed control scheme, and also the robustness of the designed fuzzy controller to uncertainties.

  9. DESCRIBING FUNCTION METHOD FOR PI-FUZZY CONTROLLED SYSTEMS STABILITY ANALYSIS

    Directory of Open Access Journals (Sweden)

    Stefan PREITL

    2004-12-01

    Full Text Available The paper proposes a global stability analysis method dedicated to fuzzy control systems containing Mamdani PI-fuzzy controllers with output integration to control SISO linear / linearized plants. The method is expressed in terms of relatively simple steps, and it is based on: the generalization of the describing function method for the considered fuzzy control systems to the MIMO case, the approximation of the describing functions by applying the least squares method. The method is applied to the stability analysis of a class of PI-fuzzy controlled servo-systems, and validated by considering a case study.

  10. Integrated Knowledge Based Expert System for Disease Diagnosis System

    Science.gov (United States)

    Arbaiy, Nureize; Sulaiman, Shafiza Eliza; Hassan, Norlida; Afizah Afip, Zehan

    2017-08-01

    The role and importance of healthcare systems to improve quality of life and social welfare in a society have been well recognized. Attention should be given to raise awareness and implementing appropriate measures to improve health care. Therefore, a computer based system is developed to serve as an alternative for people to self-diagnose their health status based on given symptoms. This strategy should be emphasized so that people can utilize the information correctly as a reference to enjoy healthier life. Hence, a Web-based Community Center for Healthcare Diagnosis system is developed based on expert system technique. Expert system reasoning technique is employed in the system to enable information about treatment and prevention of the diseases based on given symptoms. At present, three diseases are included which are arthritis, thalassemia and pneumococcal. Sets of rule and fact are managed in the knowledge based system. Web based technology is used as a platform to disseminate the information to users in order for them to optimize the information appropriately. This system will benefit people who wish to increase health awareness and seek expert knowledge on the diseases by performing self-diagnosis for early disease detection.

  11. Expert finder systems – design and use

    DEFF Research Database (Denmark)

    Lykke, Marianne; Weidel, Eva

    2011-01-01

    The survey aimed at investigating how companies deal with the challenge of sharing of employees’ expert knowledge. We wanted to find out which tools are being used to register, communicate and search employees as a knowledge resource. Specifically, we wanted to know how service organizations use ...

  12. Temporal logics and real time expert systems

    NARCIS (Netherlands)

    Blom, J.A.

    1996-01-01

    This paper introduces temporal logics. Due to the eternal compromise between expressive adequacy and reasoning efficiency that must decided upon in any application, full (first order logic or modal logic based) temporal logics are frequently not suitable. This is especially true in real time expert

  13. Identifying the Effective Factors in Making Trust in Online Social Networks on the perspective of Iranian experts Using Fuzzy ELECTRE

    Directory of Open Access Journals (Sweden)

    Elham Haghighi

    2015-12-01

    Full Text Available this paper attempts to rank the effective factors in making trust in social networks to provide the possibility of attracting and increasing users’ trust on these social networks for providers and designers of online social networks. Identifying the effective factors in making trust in social networks is a multi-criteria decision making problem and most of effective factors are ambiguous and uncertain, thereby this article uses Fuzzy ELECTRE to rank them. By implementing Fuzzy ELECTRE on gathered data, respectively «usability factor», «supporting up to date technology factor», «integrity» and «the rate of ethics factor» are on the top of effective factors in making trust in users. In general, «web features» and «technology features» have a higher degree of importance than «security features», «individual-social features» and «cultural features». Ranking of Fuzzy ELECTRE comparison ranking of Fuzzy TOPSIS and Fuzzy ELECTRE method becomes validate because Spearman correlation coefficients is 0/867. Result of sensitivity analysis on changing weight of criteria shows that Fuzzy ELECTRE isn’t affected by ambiguity and uncertainty in inputs.

  14. Using system dynamics for simulation and optimization of one coal industry system under fuzzy environment

    Energy Technology Data Exchange (ETDEWEB)

    Xu, J.P.; Li, X.F. [Sichuan University, Chengdu (China)

    2011-09-15

    In this paper, we have developed a model that integrates system dynamics with fuzzy multiple objective programming (SD-FMOP). This model can be used to study the complex interactions in a industry system. In the process of confirming sensitive parameters and fuzzy variables of the SD model, we made use of fuzzy multi-objective programming to help yield the solution. We adopted the chance-constraint programming model to convert the fuzzy variables into precise values. We use genetic algorithm to solve FMOP model, and obtain the Pareto solution through the programming models. It is evident that FMOP is effective in optimizing the given system to obtain the decision objectives of the SD model. The results recorded from the SD model are in our option, reasonable and credible. These results may help governments to establish more effective policy related to the coal industry development.

  15. Toward the efficient implementation of expert systems in Ada

    Science.gov (United States)

    Lee, S. Daniel

    1990-01-01

    Here, the authors describe Ada language issues encountered during the development of ART-Ada, an expert system tool for Ada deployment. ART-Ada is being used to implement several expert system applications for the Space Station Freedom and the U.S. Air Force. Additional information is given on dynamic memory allocation.

  16. Expert systems as applied to bridges and pavements : an overview.

    Science.gov (United States)

    1986-01-01

    Expert systems is a rapidly emerging new application of computers to aid decision makers in solving problems. This report gives an overview of what expert systems are and of what use they may be to a transportation department. The focus of the applic...

  17. The Principles of Designing an Expert System in Teaching Mathematics

    Science.gov (United States)

    Salekhova, Lailya; Nurgaliev, Albert; Zaripova, Rinata; Khakimullina, Nailya

    2013-01-01

    This study reveals general didactic concepts of the Expert Systems (ES) development process in the educational area. The proof of concept is based on the example of teaching the 8th grade Algebra subject. The main contribution in this work is the implementation of innovative approaches in analysis and processing of data by expert system as well as…

  18. Realization of economic evaluation expert system for uranium mine project

    International Nuclear Information System (INIS)

    Wang Haifeng

    1993-01-01

    By studying the EVALUATOR, economic evaluation expert system of uranium mine project, the theoretical fundamentals of expert system, principle of inference mechanism, implementation of knowledge base, realization of explanation mechanism, acquisition of domain knowledge and representation of knowledge were described, especially the subjective Bayes approach for inexact reasoning problem used in EVALUATOR was discussed in detail

  19. The development of an expert system for arid rangeland ...

    African Journals Online (AJOL)

    Currently, the expert system uses wiki technology, as this allows a high level of interaction between user and administrator. The expert system includes embedded links to photographs and additional information. It allows easy updating of the knowledge base. An additional booklet was also developed, since access to ...

  20. Application of fuzzy logic control system for reactor feed-water control

    International Nuclear Information System (INIS)

    Iijima, T.; Nakajima, Y.

    1994-01-01

    The successful actual application of a fuzzy logic control system to the a nuclear Fugen nuclear power reactor is described. Fugen is a heavy-water moderated, light-water cooled reactor. The introduction of fuzzy logic control system has enabled operators to control the steam drum water level more effectively in comparison to a conventional proportional-integral (PI) control system

  1. Speed control for a two-mass drive system using integrated fuzzy estimator and hybrid fuzzy PD/PI controller

    International Nuclear Information System (INIS)

    Pai, N-S; Kuo, Y-P

    2008-01-01

    This paper presents a novel speed control scheme for a 2- mass motor drive system. The speed controller is based on the estimated state feedback compensation. The integrated fuzzy observer can give a fast and accuracy estimation of the unmeasured states. Two kinds of hybrid fuzzy proportional-derivative and proportional-integral (HF PD/PI) are proposed to cope with this speed control problem. The first is the static HF PD/PI controller and the second is the dynamic one. Simulation results show that the developed integrated fuzzy observer provide the better estimation performance than that of the Kalman filter and the proposed control schemes can effectively track the desired speed in the presence of load disturbance

  2. Acute asthma severity identification of expert system flow in emergency department

    Science.gov (United States)

    Sharif, Nurul Atikah Mohd; Ahmad, Norazura; Ahmad, Nazihah; Desa, Wan Laailatul Hanim Mat

    2017-11-01

    Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic.

  3. Local Model Predictive Control for T-S Fuzzy Systems.

    Science.gov (United States)

    Lee, Donghwan; Hu, Jianghai

    2017-09-01

    In this paper, a new linear matrix inequality-based model predictive control (MPC) problem is studied for discrete-time nonlinear systems described as Takagi-Sugeno fuzzy systems. A recent local stability approach is applied to improve the performance of the proposed MPC scheme. At each time k , an optimal state-feedback gain that minimizes an objective function is obtained by solving a semidefinite programming problem. The local stability analysis, the estimation of the domain of attraction, and feasibility of the proposed MPC are proved. Examples are given to demonstrate the advantages of the suggested MPC over existing approaches.

  4. Identification of Fuzzy Inference Systems by Means of a Multiobjective Opposition-Based Space Search Algorithm

    Directory of Open Access Journals (Sweden)

    Wei Huang

    2013-01-01

    Full Text Available We introduce a new category of fuzzy inference systems with the aid of a multiobjective opposition-based space search algorithm (MOSSA. The proposed MOSSA is essentially a multiobjective space search algorithm improved by using an opposition-based learning that employs a so-called opposite numbers mechanism to speed up the convergence of the optimization algorithm. In the identification of fuzzy inference system, the MOSSA is exploited to carry out the parametric identification of the fuzzy model as well as to realize its structural identification. Experimental results demonstrate the effectiveness of the proposed fuzzy models.

  5. H∞ Control of Polynomial Fuzzy Systems: A Sum of Squares Approach

    Directory of Open Access Journals (Sweden)

    Bomo W. Sanjaya

    2014-07-01

    Full Text Available This paper proposes the control design ofa nonlinear polynomial fuzzy system with H∞ performance objective using a sum of squares (SOS approach. Fuzzy model and controller are represented by a polynomial fuzzy model and controller. The design condition is obtained by using polynomial Lyapunov functions that not only guarantee stability but also satisfy the H∞ performance objective. The design condition is represented in terms of an SOS that can be numerically solved via the SOSTOOLS. A simulation study is presented to show the effectiveness of the SOS-based H∞ control designfor nonlinear polynomial fuzzy systems.

  6. GOTRES: an expert system for fault detection and analysis

    International Nuclear Information System (INIS)

    Chung, D.T.; Modarres, M.

    1989-01-01

    This paper describes a deep-knowledge expert system shell for diagnosing faults in process operations. The expert program shell is called GOTRES (GOal TRee Expert System) and uses a goal tree-success tree deep-knowledge structure to model its knowledge-base. To demonstrate GOTRES, we have built an on-line fault diagnosis expert system for an experimental nuclear reactor facility using this shell. The expert system is capable of diagnosing fault conditions using system goal tree as well as utilizing accumulated operating knowledge to predict plant causal and temporal behaviours. The GOTRES shell has also been used for root-cause detection and analysis in a nuclear plant. (author)

  7. Fuzzy-probabilistic multi agent system for breast cancer risk assessment and insurance premium assignment.

    Science.gov (United States)

    Tatari, Farzaneh; Akbarzadeh-T, Mohammad-R; Sabahi, Ahmad

    2012-12-01

    In this paper, we present an agent-based system for distributed risk assessment of breast cancer development employing fuzzy and probabilistic computing. The proposed fuzzy multi agent system consists of multiple fuzzy agents that benefit from fuzzy set theory to demonstrate their soft information (linguistic information). Fuzzy risk assessment is quantified by two linguistic variables of high and low. Through fuzzy computations, the multi agent system computes the fuzzy probabilities of breast cancer development based on various risk factors. By such ranking of high risk and low risk fuzzy probabilities, the multi agent system (MAS) decides whether the risk of breast cancer development is high or low. This information is then fed into an insurance premium adjuster in order to provide preventive decision making as well as to make appropriate adjustment of insurance premium and risk. This final step of insurance analysis also provides a numeric measure to demonstrate the utility of the approach. Furthermore, actual data are gathered from two hospitals in Mashhad during 1 year. The results are then compared with a fuzzy distributed approach. Copyright © 2012 Elsevier Inc. All rights reserved.

  8. Improved Polynomial Fuzzy Modeling and Controller with Stability Analysis for Nonlinear Dynamical Systems

    OpenAIRE

    Hamed Kharrati; Sohrab Khanmohammadi; Witold Pedrycz; Ghasem Alizadeh

    2012-01-01

    This study presents an improved model and controller for nonlinear plants using polynomial fuzzy model-based (FMB) systems. To minimize mismatch between the polynomial fuzzy model and nonlinear plant, the suitable parameters of membership functions are determined in a systematic way. Defining an appropriate fitness function and utilizing Taylor series expansion, a genetic algorithm (GA) is used to form the shape of membership functions in polynomial forms, which are afterwards used in fuzzy m...

  9. H∞ Control of Polynomial Fuzzy Systems: A Sum of Squares Approach

    OpenAIRE

    Bomo W. Sanjaya; Bambang Riyanto Trilaksono; Arief Syaichu-Rohman

    2014-01-01

    This paper proposes the control design ofa nonlinear polynomial fuzzy system with H∞ performance objective using a sum of squares (SOS) approach. Fuzzy model and controller are represented by a polynomial fuzzy model and controller. The design condition is obtained by using polynomial Lyapunov functions that not only guarantee stability but also satisfy the H∞ performance objective. The design condition is represented in terms of an SOS that can be numerically solved via the SOSTOOLS. A simul...

  10. Building reactor operator sustain expert system with C language integrated production system

    International Nuclear Information System (INIS)

    Ouyang Qin; Hu Shouyin; Wang Ruipian

    2002-01-01

    The development of the reactor operator sustain expert system is introduced, the capability of building reactor operator sustain expert system is discussed with C Language Integrated Production System (Clips), and a simple antitype of expert system is illustrated. The limitation of building reactor operator sustain expert system with Clips is also discussed

  11. Location-aware News Recommendation System with Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Mehdi Nejati

    2016-10-01

    Full Text Available with release of a huge amount of news on the Internet and the trend of users to Web-based news services.it is necessary to have a recommendation system. To grab attentions to news, news services use a number of criteria that called news values and user location is an important factor for it. In this paper, LONEF is proposed as a tow stage recommendation system. In first stage news are ranked by user’s locations and in second stage news are recommended by location Preferences, recency, Trustworthiness, groups priorities and popularity. To reduce ambiguity these properties is used tow Mamdani fuzzy interference and case-based decision systems. In Mamdani fuzzy interference system, it is tried to increase the system speed by optimizing selection of rules and membership functions and because of ambiguous feedback implementation, a decision making system is used to enable better simulation of user’s activities. Performance of our proposed approach is demonstrated in the experiments on different news groups.

  12. Hybrid Type II fuzzy system & data mining approach for surface finish

    Directory of Open Access Journals (Sweden)

    Tzu-Liang (Bill Tseng

    2015-07-01

    Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

  13. Two-Dimensional Fuzzy Sliding Mode Control of a Field-Sensed Magnetic Suspension System

    Directory of Open Access Journals (Sweden)

    Jen-Hsing Li

    2014-01-01

    Full Text Available This paper presents the two-dimensional fuzzy sliding mode control of a field-sensed magnetic suspension system. The fuzzy rules include both the sliding manifold and its derivative. The fuzzy sliding mode control has advantages of the sliding mode control and the fuzzy control rules are minimized. Magnetic suspension systems are nonlinear and inherently unstable systems. The two-dimensional fuzzy sliding mode control can stabilize the nonlinear systems globally and attenuate chatter effectively. It is adequate to be applied to magnetic suspension systems. New design circuits of magnetic suspension systems are proposed in this paper. ARM Cortex-M3 microcontroller is utilized as a digital controller. The implemented driver, sensor, and control circuits are simpler, more inexpensive, and effective. This apparatus is satisfactory for engineering education. In the hands-on experiments, the proposed control scheme markedly improves performances of the field-sensed magnetic suspension system.

  14. Expert system for quality control in the INIS database

    International Nuclear Information System (INIS)

    Todeschini, C.; Tolstenkov, A.

    1990-05-01

    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

  15. Expert system for quality control in the INIS database

    Energy Technology Data Exchange (ETDEWEB)

    Todeschini, C; Tolstenkov, A [International Atomic Energy Agency, Vienna (Austria)

    1990-05-01

    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.

  16. Stability Analysis of a Type of Takagi-Sugeno PI Fuzzy Control Systems Using Circle Criterion

    Directory of Open Access Journals (Sweden)

    Kairui Cao

    2011-04-01

    Full Text Available A type of Takagi-Sugeno (T-S Proportional-Integral (PI fuzzy controllers is studied. The T-S PI fuzzy controller is formed by a T-S Proportional-Derivative (PD fuzzy controller connected with an integrator. In this particular structure, the T-S PD fuzzy controller is a weighted sum of some linear PD sub-controllers. The mathematical properties of our T-S PI fuzzy controller are also investigated. Based on these properties, the global asymptotic stability of the fuzzy control systems, in which the T-S PI fuzzy controllers are employed, are analyzed by using the well-known circle criterion. A sufficient condition with an elegant graphical interpretation in the frequency domain is further derived to guarantee the global asymptotic stability of the above fuzzy control systems. Finally, two numerical examples are provided to demonstrate how to deploy this method in analyzing the T-S PI fuzzy control systems in the frequency domain with the aid of some simple graphs.

  17. Design of a self-adaptive fuzzy PID controller for piezoelectric ceramics micro-displacement system

    Science.gov (United States)

    Zhang, Shuang; Zhong, Yuning; Xu, Zhongbao

    2008-12-01

    In order to improve control precision of the piezoelectric ceramics (PZT) micro-displacement system, a self-adaptive fuzzy Proportional Integration Differential (PID) controller is designed based on the traditional digital PID controller combining with fuzzy control. The arithmetic gives a fuzzy control rule table with the fuzzy control rule and fuzzy reasoning, through this table, the PID parameters can be adjusted online in real time control. Furthermore, the automatic selective control is achieved according to the change of the error. The controller combines the good dynamic capability of the fuzzy control and the high stable precision of the PID control, adopts the method of using fuzzy control and PID control in different segments of time. In the initial and middle stage of the transition process of system, that is, when the error is larger than the value, fuzzy control is used to adjust control variable. It makes full use of the fast response of the fuzzy control. And when the error is smaller than the value, the system is about to be in the steady state, PID control is adopted to eliminate static error. The problems of PZT existing in the field of precise positioning are overcome. The results of the experiments prove that the project is correct and practicable.

  18. Wind farm fuzzy modelling for adequacy evaluation of power system

    Energy Technology Data Exchange (ETDEWEB)

    Moeini-Aghtaie, M.; Abbaspour, A.; Fotuhi-Firuzabad, M. [Sharif Univ. of Technology, Tehran (Iran, Islamic Republic of). Dept. of Electrical Engineering, Center of Excellence in Power System Management and Control

    2010-07-01

    This paper presented details of a fuzzy logic-based active learning method (ALM) designed to model variations in wind speed. A pattern-based approach was used to model system behaviour. The ALM was algorithmically modelled on the information-handling processes of the human brain. Wind data were gathered and projected on different data planes. The horizontal axis of each data plane was one of the inputs, while the vertical axis was the output. An ink drop spread (IDS) processing engine was used to look for behaviour curves on each data plane. A fuzzy interpolation method was used to derive a smooth curve among the data points. Sequential Monte Carlo simulations (MCS) were used to evaluate power systems based on hourly random simulations. After the hourly wind speed was generated, wind turbine generator outputs were calculated by considering the nonlinear relationship between the estimated wind speed and the wind turbine output. The developed algorithm was validated on a 6-bus reliability test system. Results of the study can be used by power system schedulers to develop power system reliability guidelines. 14 refs., 2 tabs., 11 figs.

  19. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

    Science.gov (United States)

    Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

    2016-07-26

    This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches.

  20. Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

    Directory of Open Access Journals (Sweden)

    Chien-Hao Tseng

    2016-07-01

    Full Text Available This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF and fuzzy logic adaptive system (FLAS for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF, unscented Kalman filter (UKF, and CKF approaches.