• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.245-251
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• 2013

In this paper, the expert system to reduce the amount of food waste is proposed. The method of material flow analysis (MFA) is applied. Proper handling of waste beyond the terms of the need for proactive research been mentioned before, but actually cause the waste generator research focuses on consumer behavior and the business community to analyze the flow of materials within the study are insufficient. In this paper, the type of food consumption and food waste, look at the relationship between the occurrence of secondary schools in the diet is provided for students to examine the preferences of the target model diet expert system was reconfigured. Preference for leaving the food in the diet leads to the important information that is Each diet recipes that make up the target material flow analysis (MFA) was constructed to perform all the database. This database is currently being generated from the rain while cooking diet edible plants and materials to reflect the self-esteem following the recommended diet is used to create. Reducing food waste is actually being used currently in research knowledge to the knowledge base was constructed. Future Home Smart System was developed in conjunction with the system to the user, by providing guidelines for the utilization can be expected.

• The Journal of Society for e-Business Studies
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• v.12 no.1
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• pp.99-122
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• 2007

The rule based system is inference engine which can correspond quickly to new business model change and improvement requirement by dealing with the business know-how and expert knowledge as well as business process of enterprise and has been trying to apply to the various industries. As a part of application cases for rule-based system, we develop and implement the rule-based insurance product recommend and design system for the efficient decision making of insurance product in insurance industry which is sensitively affected by needs of customers, various kinds of product, and environment changes. The process of fuzzy inference of the developed system helps to recommend and design the proper Insurance product using the information of the present customer and the previous members. This approach is expected that it will be the core technology for the recommendation and design of the tailored insurance product by deciding and corresponding needs of various kinds of customer quickly in future insurance industry.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.49-57
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• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.370-374
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• 1993

This paper describes a study on the expert system based process planning of the block division process in shipbuilding. The prototype system developed deterines the block division line of the midship of crude-oil tanker. Case-based reasoning (CBR) approach relying on previous similar cases to solve the problem is applied instead of rule-based reasoning (RBR). Similar cases are retrieved from case base according to the similarity metrics between input problem and cases. The retrieved case with the highest priority is then adapted to fit to the input problem buy adaptation rules. The adapted solution is proposed as the division line for the input problem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.447-450
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• 2003

In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.75-80
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• 2005

A design for the front section of an excavator requires kinematic and kinetic mechanism consideration for several configurations. Key parameters for an appropriate configuration can be obtained through a mechanical verification and numerical formulation with a design expert's know-how. In this paper, we propose a knowledge-based system with an expert-shell(CATIA) and Visual Basic to assist for the design of the front section of an excavator. The designers can achieve more efficient design through a CAD model, implemented design knowledge, and a user friendly interface. The implemented design knowledge is retrieved through the whole design process from an early design stage to a detailed design stage based on the multiple levels of abstraction scheme.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.1-16
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• 2000

This paper analyzes the approaches of Web-based expert systems by comparing their pros and cons. and proposes a methodology of implementing the Web-based backward inference engines with reduced burden to Web servers. There are several alternatives to implement expert systems under the WWW environment : CGI, Web servers embedding inference engines external viewers Java Applets and HTML. Each of the alternatives have advantages and disadvantages of each own in terms of development and deployment testing scalability portability maintenance and mass service. Especially inference engines implemented using HTML possess relatively large number of advantages compared with those implemented using other techniques. This paper explains the methodology to present rules and variables for backward inference by HTML and JavaScript and suggests a framework for design and development of HTML-based Expert System. A methodology to convert a traditional rule base to an Experts Diagram and then generate a new HTML-based Expert System from the Experts Diagram is also addressed.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.15-27
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• 2000

The paper proposes a hybrid fire fighting control intelligent system(H-FFIS) using rules and cases to detect fire in Integrated Platform Management System. By far most conventional systems have been based on rule-based system in which expert knowledges are expressed with production rules. It is hard to express the knowledges to detect fire with production rules only. The knowledges of fire detection are often based on previously encountered situations of fires. For improvement of system capability renewing and adding of rules is needed in an already build-up system and such adding and renewing procedures could hinder users from fluent utilization of the system. We design and implement H-FFIS. Compared with rule-based FFIS(Fire Fighting control Intelligent System), H-FFIS extended with case-based reasoning shows that the system proposed here can lead to an improvement in fire detection rate.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.11-24
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• 1998

이 논문에서는 상황에 적합한 정보들을 선택하고 이를 해당되는 GUI (Graphic User Interface) 객체를 통해 사용자에게 제시하기 위한 규칙 기반의 지능적 사용적 인터페이스 구조를 제안하고, 이를 이용하여 실제로 군사 분야 정보 융합 시스템의 그래픽 사용자 인터페이스를 개발하였다. 군사분야와 같이 복잡하고 급변하는 상황에서는 상황에 따라 필요한 정보가 다를 뿐만 아니라, 불필요한 정보의 제시로 인해 오히려 사용자의 판단에 혼란을 초래할 수 있다. 이 논문에서는 이러한 점을 고려하여, 제시할 정보와 GUI 객체의 적절한 대응뿐만 아니라, 상황에 따라 사용자에게 필요한 정보를 해당분야의 전문가로부터 획득한 규칙에 의해 선택적으로 제시하도록 하기 위한 GUI 구조를 제안하였다. 개발한 GUI의 구조는 입력 해석, 제시할 정보의 선택, GUI 객체의 선택, GUI객체의 생성 및 속성 기정, GUI 객체의 배치 및 출력 단계들로 구성되며, 각각의 단계는 규칙에 의해 처리된다. 제안된 구조에 의해 공중 작전 수립을 위한 정보 융합 시스템의 사용자 인터페이스를 개발한 결과, 다양한 매체를 통해 많은 데이터가 들어오는 상황에서 필요한 정보만을 선택하여 적절히 제시해 줌으로써 사용자의 신속한 상황 판단과 결정 수립을 지원할 수 있었다.

• IE interfaces
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• v.2 no.2
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• pp.51-62
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• 1989

A computer-aided simulation modeling system has been developed to allow the automatic construction of complete discrete simulation models for queueing systems. Three types of knowledge are used in the specification and construction of a simulation modeling: Knowledge of queueing system, simulation modeling, and a target simulation language. This knowledge has been incorporated into the underlying rule base in the form of extraction and construction rule, and implemented via the expert system building tool, OPS5. This paper suggested a knowledge based approach for automatic programming to enable a user who lacks modeling knowledge and simulation language expertize to quickly build executable models.