• International Journal of Safety
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• v.6 no.2
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• pp.27-32
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• 2007

For last several decades with the achievement of fast economic development, the electrical fires occupies over 30 percent of total fire incidents almost every year in Korea and not decreased in spite of much times and efforts. Electrical fire cause diagnostics are to confirm a cause for the fire by examination of fire scene. Cause diagnosis methods haven't been systematized yet, because of limits for available information, investigator's biased knowledge, etc. Therefore, in order to assist the investigators and to find out the exact causes of electrical fires, required is research for an electrical fire cause diagnosis system using DB, computer programming and some mathematical tools. The electrical fire cause diagnosis system has two functions of DB and electrical fire cause diagnosis. The cause diagnosis is conducted by a case-based reasoning on a case base and rule-based reasoning on a rule base. For the diagnosis with high reliability, a mixed reasoning approach of a case-based reasoning and fuzzy rule-based reasoning has been adopted. The electrical fire cause diagnosis system proposes the electrical fire causes inferred from the diagnosis processes, and possibility of the causes as well.

• International journal of advanced smart convergence
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• v.7 no.2
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• pp.47-54
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• 2018

This paper is a study on implementation of the golf play advice system which provides advice to golfers through mobile devices. The system consists of a mobile unit consisting of a GPS receiver, a data transmitter and receiver, and a display unit, and a server unit composed of a database and advice generator. The advice generator that provides advices to the users, generates advices with IF-THEN rule-based reasoning method. The reasoning module utilizes golfer's personal records and various information in the database of the server unit. This system provides the advice to the users who play on the golf course through mobile devices, so that it is possible to provide various information similar to the screen golf using the computer simulating technology in the outdoor golf course.

• Journal of KIISE
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• v.43 no.9
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• pp.963-973
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• 2016

Providing a semantic knowledge system using media ontologies requires not only conventional axiom reasoning but also knowledge extension based on various types of reasoning. In particular, spatio-temporal information can be used in a variety of artificial intelligence applications and the importance of spatio-temporal reasoning and expression is continuously increasing. In this paper, we append the LOD data related to the public address system to large-scale media ontologies in order to utilize spatial inference in reasoning. We propose an RDFS/Spatial inference system by utilizing distributed memory-based framework for reasoning about large-scale ontologies annotated with spatial information. In addition, we describe a distributed spatio-temporal SPARQL parallel query processing method designed for large scale ontology data annotated with spatio-temporal information. In order to evaluate the performance of our system, we conducted experiments using LUBM and BSBM data sets for ontology reasoning and query processing benchmark.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.511-515
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• 2001

Many intelligent agent systems are known to incorporate BDI architecture for cognitive reasoning. Since this architecture contains all the knowledge of world model and reasoning rule, it is very complex and difficult to handle. This paper describes a methodology to design and implement BDI architecture, BDIAXml based on XML for multi-agent systems. This XML-based BDI architecture is smaller than any other BDI architecture because it separates knowledge for reasoning from domain knowledge and enables knowledge sharing using XML technology. Knowledge for BDI mental state and reasoning is composed of specific XML files and these XML files are stored into a specific knowledge server. Most systems using BDIAxml architecture can access knowledge from this server. We apply this BDIAXml system to domain of Hospital Information System and show that this architecture performs more efficiently than other BDI architecture system in terms of knowledge sharing, system size, and ease of use.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1275-1280
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• 2004

This paper presents the construction of an active suspension system of a one-wheel car model by using fuzzy reasoning. The car model is approximately described by a nonlinear two degrees freedom system subject to excitation from a road profile, and the active control force is constructed by actuating a pneumatic actuator, and the degradation of the performance due to the delay of the pneumatic actuator is improved by inserting a compensator. The fuzzy control is obtained by single input rule modules fuzzy reasoning, and the excitation from the road profile is estimated by using a disturbance observer. The experimental result shows that the proposed active suspension system much improves the performance in the vibration suppression of the car model.

• Korean Journal of Cognitive Science
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• v.15 no.4
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• pp.15-20
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• 2004

To develop a cognitive system with the flexibility and breadth of human, it's very important to construct a large scale knowledge base which include commonsense knowledge as well as expert knowledge. Efficient knowledge representation and reasoning techniques will play a key role for this. This paper introduce a cognitive system which is based on Cyc knowledge base and augmented with our work on qualitative and spatial representation and reasoning. Our system has been implemented and tested on various examples.

• The Journal of the Korea Contents Association
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• v.1 no.1
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• pp.51-58
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• 2001

Electronic commerce system must provide convenient interface, easy and fast searching function, and production information satisfying customers. To do this, many kinds of studies are being advanced actively about electronic commerce system using intelligent agent electronic This paper suggests 2-tier electronic commerce system using intelligent multi agent. We propose a combined reasoning agent system which provides production information satisfying customer's needs using both case-based reasoning and rule-based reasoning. And this system distribute network and sewer system load based on load balancing and 2-tier agent structure. This system can find production information through teaming of rule-based reasoning method and case-based reasoning method. This system can provide the best suitable production information to customers by using combined reasoning agent system. And we can prevent customer's unexpected long waiting causes by network traffic and server load.

• Journal of Korean Medical classics
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• v.32 no.2
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• pp.1-16
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• 2019

Objectives : In this paper, characteristics of research methodology used in the field of Korean Medical Classics and its application was studied, with a focus on abductive reasoning that takes place in such methodology. Methods : First, the properties of the Korean Medical knowledge system, production, circulation and consumption of Korean Medical knowledge, methodology of knowledge production, reasoning of hypothesis, Medical Classics research methodology and its examples were examined. Afterwards, the relationship between Medical Classics research and Korean Medical Doctors's competence was studied. Results : The knowledge system of Korean Medicine, formed by a knowledge production group changes continuously not unlike a living organism. Knowledge is produced through Sang (象) within human consciousness that lies in an existential relationship between the knowledge producer and subject, through means of abductive reasoning. Conclusions : Creative knowledge production through abductive reasoning in the field of Korean Medical Classics will hopefully contribute to production of highly useful knowledge in clinical settings, complement and make change in the current Korean Medical knowledge system. Various teaching methods based on this research methodology will contribute to strengthening Korean Medical Doctors's competence as well.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.553-561
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• 2018

To easily understand and systematically express the behaviors of the industrial systems, various system modeling techniques have been developed. Particularly, the importance of system modeling has been greatly emphasized in recent years since modern industrial systems have become larger and more complex. Multilevel flow modeling (MFM) is one of the qualitative modeling techniques, applied for the representation and reasoning of target system characteristics and phenomena. MFM can be applied to industrial systems without additional domain-specific assumptions or detailed knowledge, and qualitative reasoning regarding event causes and consequences can be conducted with high speed and fidelity. However, current MFM techniques have a limitation, i.e., the dynamic features of a target system are not considered because time-related concepts are not involved. The applicability of MFM has been restricted since time-related information is essential for the modeling of dynamic systems. Specifically, the results from the reasoning processes include relatively less information because they did not utilize time-related data. In this article, the concepts of time-to-detect and time-to-effect were adopted from the system failure model to incorporate time-related issues into MFM, and a methodology for enhancing MFM-based reasoning with time-series data was suggested.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.97-101
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• 1997

In recent years, there have been a number of applications of fuzzy logic in fuzzy reasoning system. The main objective of these applications is to approximate a decision making using the fuzzy reasoning system. This paper designs a fuzzy reasoning model for the decision making of registration fee at a private school, implements it applying for linguistic variables and fuzzy rules, and evaluates the practical availability of the model. The system accepts fuzzy rules, the type of membership functions, the domain of fuzzy sets and hedge, and fuzzifies the linguistic variables to generates fuzzy sets. The fuzzy sets generated are combined to constructs a solution fuzzy set. Finally, the system defuzzifies the solution fuzzy set to calculate a scalar value which is used for decision making.