• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.107-110
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• 2000

In this paper, we propose a method of constructing neural networks using bio-inspired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants. Here is, we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting mechanism. The DNA coding method has no limitation in expressing the production rule of L-system. Evolutionary algorithms motivated by Darwinian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it to one step ahead prediction of Mackey-Glass time series.

• Journal of the Korea Society for Simulation
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• v.14 no.1
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• pp.9-18
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• 2005

Attempts to attack hosts in the network have become diverse, due to crackers developments of new creative attacking methods. Under these circumstances the role of intrusion detection system as a security system component gets considerably importance. Therefore, in this paper, we have suggested multiple intrusion detection system based on the contract net protocol which provides the communication among multiple agents. In this architecture, fuzzy rule based system has been applied for agent selection among agents competing for being activated. The simulation models are designed and implemented based on DEVS formalism which is theoretically well grounded means of expressing discrete event simulation models.

• The KIPS Transactions:PartC
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• v.12C no.2 s.98
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• pp.191-200
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• 2005

The brilliant achievements in computers and the internet technology make it easy for users to get useful information. But at the same time, the damages caused by intrusions and denial of service attacks are getting more worse. Specially because denial of service attacks by internet worm incapacitate computers and networks, we should draw up a disposal plan against it. So far many rule-based intrusion detection systems have been developed, but these have the limits of these ability to detect new internet worms. In this paper, we propose a system to detect intrusion and generate detection rule against scan-based internet worm, paying attention to the fact that internet worms scan network to infect hosts. The system detects internet worms using detection rule. And if it detects traffic causing by a new scan-based internet worm, it generates new detection nile using traffic information that is gathered. Therefore it can response to new internet worms early. Because the system gathers packet payload, when it is being necessary only, it can reduce system's overhead and disk space that is required.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.781-788
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• 2005

MTF message is the normalized and standardized format which is used in the time when it tries to transmit data to other systems or exchanges needed information in defense message systems. XML can support variety of search functionality and is estimated to be the best way from the view of efficient presentation and exchange in internet based environment, based on advantage which is independent of hardware and software. US army brought in XML-MTF combining with XML based technology, but we do not contain such a MTF system, and necessity of MTF is increasing for combined operation between ROK and US as a lot of C4I system were transferred to Web based systems. In this paper, we make analysis of fundamental structure, organization of paragraph, witting regulation of MTF message. We present the rule of naming element and fundamental mapping rule for transformation of its XML based on it. Also, we prove that MTF message can be transformed to XML document by trying to transforming sample documents to XML document applying presented mapping rule, creating MTF message based on it and implement program which can automatically transform them to XML-MTF.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.81-86
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• 2002

In current CBR(Case-Based Reasoning) systems, the case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck similar to those found in traditional expert system design. In this thesis, 1 present a model for learning method of case adaptation knowledge using case base. The feature difference of each pair of cases are noted and become the antecedent part of an adaptation rule, the differences between the solutions in the compared cases become the consequent part of the rule. However, the number of rules that can possibly be discovered using a learning algorithm is enormous. The first method for finding cases to compare uses a syntactic measure of the distance between cases. The threshold fur identification of candidates for comparison is fixed th the maximum number of differences between the target and retrived case from all retrievals. The second method is to use similarity metric since the threshold method may not be an accurate measure. I suggest the elimination method of duplicate rules. In the elimination process, a confidence value is assigned to each rule based on its frequency. The learned adaptation rules is applied in riven target Problem. The basic. process involves search for all rules that handle at least one difference followed by a combination process in which complete solutions are built.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.792-797
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• 2011

This paper discusses the application of a hybrid discretiziation method for the discretization procedure that needs to be included in discrete particle swarm optimization (DPSO) for the problem of allocating PV (photovoltaic) systems onto distribution power systems. For this purpose, this paper proposes a rule-based expert system considering the objective function value and its optimizing speed as the input parameters and applied it to the PV allocation problem including discrete decision variables. For multi-level discretization, this paper adopts a hybrid method combined with a simple rounding and sigmoid funtion based 3-step and 5-step quantization methods, and the application of the rule based expert system proposing the adequate discretization method at each PSO iteration so that the DPSO with the hybrid discretization can provide better performance than the previous DPSO.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.42-48
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• 2003

In general many engineers can diagnose the fault condition using the abnormal ones among data monitored from a diesel engine, but they don't need the system modelling or identification for the work. They check the abnormal data and the relationship and then catch the fault condition of the engine. This paper proposes the construction of a fault diagnosis engine through malfunction data gained from the data fault detection system of neural networks for diesel generator engine, and the rule inference method to induce the rule for fuzzy inference from the malfunction data of diesel engine like a site engineer with a fuzzy system. The proposed fault diagnosis system is constructed in the sense of the Malfunction Diagnosis Engine(MDE) and Hierarchy of Malfunction Hypotheses(HMH). The system is concerned with the rule reduction method of knowledge base for related data among the various interactive data.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.59-65
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• 2002

Recently, lots of researchers work focused on the intrusion detection system. Pattern matching technique is commonly used to detect the intrusion in the system, However, the method requires a lot of time to match between systems rule and inputted packet data. This paper proposes a new intrusion detection system based on the pattern matching technique. Proposed system reduces the required time for pattern matching by using classified system rule. The classified rule is implemented with a general tree for efficient pattern matching. Thereby, proposed system could perform network intrusion detection efficiently.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.11a
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• pp.59-65
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• 2002

Recently, lots of researchers work focused on the intrusion detection system. Pattern matching technique is commonly used to detect the intrusion in the system, However, the method requires a lot of time to match between systems rule and inputted packet data. This paper proposes a new intrusion detection system based on the pattern matching technique. Proposed system reduces the required time for pattern matching by using classified system rule. The classified rule is implemented with a general tree for efficient pattern matching. Thereby, proposed system could perform network intrusion detection efficiently.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.436-438
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• 1993

A rule based fuzzy expert system in self-tune PID controllers is presented in this paper. The rule base. the core of the expert system, is extracted from the Wills' tuning map and the author's knowledge about the implicit relations between PID gains and controlled output response. The overall control system consists of the relay feedback scheme and the expert system, where the one is responsible for initial tuning and the other for subsequent tuning. The PID control system with the proposed fuzzy expert system, shows better convergence rate and control performances than those of a Litt in spite of the fact that the two rule bases are extracted from the same maps provided by Wills.