• Journal of the Society of Naval Architects of Korea
• /
• v.30 no.4
• /
• pp.1-7
• /
• 1993

This paper describes development of a knowledge-based system for main engine selection of ships using general purpose expert system development tool, Nexpert Object. Developed system consist of ship performance estimation module such as resistance and propulsion, data base for main engine, knowledge base for main engine selection in Nexpert Object and graphic user interface.

• KEPCO Journal on Electric Power and Energy
• /
• v.7 no.1
• /
• pp.79-84
• /
• 2021

The fundamental element to be kept for big data analysis, artificial intelligence technologies and asset management system is a data quality, which could directly affect the entire system reliability. For this reason, the momentum of data cleaning works is recently increased and data cleaning methods have been investigating around the world. In the field of electric power, however, asset data cleaning methods have not been fully determined therefore, automatic cleaning algorithm of asset data for transmission cables has been studied in this paper. Cleaning algorithm is composed of missing data treatment and outlier data one. Rule-based and expert opinion based cleaning methods are converged and utilized for these dirty data.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1995.10a
• /
• pp.1146-1149
• /
• 1995

The CAD/CAM System for deep drawing transfer die in mechanical press proess has been developed. The developed CAD system can generate the drawing of drawing of transfer die in mechanical press. Using these results from CAD system, it can generate the NC data to machine die's elements on the CAD system. This system can reduce design man-hours and human errors. In order to construct the system, it is used to automate the design process using knowledge base system. The developed system is based on the knowledge base system which is involved a lot of expert's technology in the practice filed. Using AutoLISP language under the AutoCAD system, CTK customer language of SmartCAM is used as the overall CAD/CAM environment. Results of this system will be provide effective aids to the designer and mannufacturer in this field.

• Structural Engineering and Mechanics
• /
• v.51 no.6
• /
• pp.973-988
• /
• 2014

This paper presents a factor-analysis based questionnaire categorization method to improve the reliability of the evaluation of working conditions without influencing the completeness of the questionnaire both in Taiwanese and Chinese construction enterprises for structural engineering applications. The proposed approach springs from the AI application and expert systems in structural engineering. Questions with a similar response pattern are grouped into or categorized as one factor. Questions that form a single factor usually have higher reliability than the entire questionnaire, especially in the case when the questionnaire is complex and inconsistent. By classifying questions based on the meanings of the words used in them and the responded scores, reliability could be increased. The principle for classification was that 90% of the questions in the same classified group must satisfy the proposed classification rule and consequently the lowest one was 92%. The results show that the question classification method could improve the reliability of the questionnaires for at least 0.7. Compared to the question deletion method using SPSS, 75% of the questions left were verified the same as the results obtained by applying the classification method.

• Management & Information Systems Review
• /
• v.2
• /
• pp.169-193
• /
• 1998

Case- based reasoning(CBR) offers a new approach for developing knowledge based systems. Unlike the rule-based paradigm, in which domain knowledge is encoded in the form of production rules, in the case-based approach the problem solving experience of the domain expert is encoded in the form of cases stored in a casebase(CB). CBR allows a reasoner (1) to propose solutions in domains that are not completely understood by the reasoner, (2) to evaluate solutions when no algorithmic method is available for evaluation, and (3) to interprete open-ended and ill-defined concepts. CBR also helps reasoner (4) take actions to avoid repeating past mistakes, and (5) focus its reasoning on important parts of a problem. Owing to the above advantages, CBR has successfully been applied to many kinds of problems such as design, planning, diagnosis and instruction. In this paper, I propose case-based DSS(CBDSS). CBDSS is an intelligent DSS using CBR technique. CBDSS consists of interface, case-based reasoner, maintainer, casebase management system, domain dependent CB, domain independent CB, and so on.

• Journal of Intelligence and Information Systems
• /
• v.7 no.2
• /
• pp.83-93
• /
• 2001

Prediction of corporate failure using past financial data is well-documented topic. Early studies of bankruptcy prediction used statistical techniques such as multiple discriminant analysis, logit and probit. Recently, however, numerous studies have demonstrated that artificial intelligence such as neural networks (NNs) can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. Although numerous theoretical and experimental studies reported the usefulness or neural networks in classification studies, there exists a major drawback in building and using the model. That is, the user can not readily comprehend the final rules that the neural network models acquire. We propose a genetic algorithms (GAs) approach in this study and illustrate how GAs can be applied to corporate failure prediction modeling. An advantage of GAs approach offers is that it is capable of extracting rules that are easy to understand for users like expert systems. The preliminary results show that rule extraction approach using GAs for bankruptcy prediction modeling is promising.

• Science of Emotion and Sensibility
• /
• v.5 no.1
• /
• pp.17-24
• /
• 2002

This research was the first step to develop Expert System for Evaluation of Human Sensibility, where human sensibility can be inferred from objective physiological signals. The study aim was to develop an algorithm in which human arousal level can be judged using measured physiological signals. Fuzzy theory was applied for mathematical handling of the ambiguity related to evaluation of human sensibility, and the degree of belonging to a certain sensibility dimension was quantified by membership function through which the sensibility evaluation was able to be done. Determining membership function was achieved using results from a physiological signal database of arousal/relaxation that was generated from imagination. To induce one final result (arousal level) based on measuring the results of more than 2 physiological signals and the membership function of each physiological signal, Dempster-Shafer's Rule of Combination in Evidence was applied, through which the final arousal level was inferred.

• Transactions of Materials Processing
• /
• v.8 no.6
• /
• pp.591-603
• /
• 1999

A computer-aided process planning system for rotationally symmetric deep drawing products has been developed. The application for non-axisymmetric components, however, has been reported yet. Therefore, this study investigates process sequence design in deep drawing process and constructs a computer-aided process planning system for non-axisymmetric motor frame products with elliptical shape. The system developed consists of three modules. The first one os a 3-dimensional modeling module to calculate surface area for non-axisymmetric products. The second one is a blank design module that creates an oval-shaped blank with the identical surface area. The third one is a process planning module based on production rules that play the best important roles in an expert system for manufacturing. The production rules are generated and upgraded by interviewing with field engineers. Especially, drawing coefficient, punch and die radii are considered as main design parameters. The constructed system for elliptical deep drawing products would be very useful to reduce lead time and improve accuracy for production.

• Korean Journal of Cognitive Science
• /
• v.10 no.4
• /
• pp.51-62
• /
• 1999

This paper proposes a fuzzy Petri net representation to represent the fuzzy production rules of a rule-based expert system. Based on the fuzzy Petri net representation. we present a fuzzy reasoning algorithms which consist of forward and b backward reasoning algorithm. The proposed algorithms. which use the proper belief evaluation functions according to fuzzy concepts in antecedent and consequent of a fuzzy production rule. are more closer to human intuition and reasoning than other methods. The forward reasoning algorithm can be represented by a reachability tree as a kind of finite directed tree. The backward reasoning algorithm generates the backward reasoning path from the goal to the initial nodes and then evaluates the belief value of the goal node using belief evaluation functions.

• Proceedings of the KSR Conference
• /
• 2007.11a
• /
• pp.1529-1532
• /
• 2007

Failure Mode, Effects, and Criticality Analysis (FMECA) is an extension of FMEA which includes a criticality analysis. The criticality analysis is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. However, there are several limitations. Measuring severity of failure consequences is subjective and linguistic. Since The result of FMECA only gives qualitative and quantitative informations, it should be re-analysed to prioritize critical units. Fuzzy set theory has been introduced by Lotfi A. Zadeh (1965). It has extended the classical set theory dramatically. Based on fuzzy set theory, fuzzy logic has been developed employing human reasoning process. IF-THEN fuzzy rule based assessment approach can model the expert's decision logic appropriately. Fault tree analysis (FTA) is one of most common fault modeling techniques. It is widely used in many fields practically. In this paper, a simple fault tree analysis is proposed to measure the severity of components. Fuzzy rule based assessment method interprets linguistic variables for determination of critical unit priorities. An rail-way transforming system is analysed to describe the proposed method.