• Proceedings of the IEEK Conference
• /
• 2003.11b
• /
• pp.227-230
• /
• 2003

We can not distinguish semantism of the feature of the current language “big”, “small”, “beautiful”. But we study artificial linguistic interface work and convert natural language to digital binary linguistic theory, we should define the basical conversion process. When we utilize the sum of product fuzzy theory and the visible numerical value, we can establish reasoning rule of input language. Fuzzy theory should be converted to general resulting rule.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.343-346
• /
• 2012

There are many realistic system necessities on the huge size of rule matrices with any Fuzzy Logical Inferences. This paper indicates the experimental design policy on the PCS design for the Platoon and AOS for the social application with some identical resemblances in between them so that we could use a design for two different usages feasibly.

• Proceedings of the KIEE Conference
• /
• 1991.07a
• /
• pp.703-707
• /
• 1991

During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for reaserch in the applications of fuzzy set theory. A key component of the fuzzy controller is a rule-based system which provides a linguistic description of control strategy. This strategy has the form of a collection of fuzzy conditional statements which are implemented and manipulated using fuzzy set theory. In this paper, we propose the rule-based controller for DC motor speed control. The result of performance compare with PID controller to verify the validity of proposed algorithm.

• Journal of the Korean Society for Precision Engineering
• /
• v.12 no.8
• /
• pp.92-98
• /
• 1995

The position control of flexible joint manipulator is investigated by applying the self-organizing fuzzy logic controller (SOC) proposed by Procyk and Mamdani. The SOC is a heuristic rule-based controller and a further extension of an ordinary fuzzy controller, which has a hierachy structrue which consists of an algorithm being identical to a fuzzy controller at the lower ollp and a learning algorithm accomodating the performance evalution and rule modification function at the upper ollp. This form of control can be used in those complex systems which have been too difficult to control or which in the past have had to rely on the experience of a human operator. Even though the significant dynamic coupling of the motors and links on the flexible joint manipulator, the performance of command-following is good by applying the proposed SOC.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1999.10a
• /
• pp.57-62
• /
• 1999

A disassembility assessment has mostly depend on the subjective decision making from the qualitative element. It is not useful in the practical assessement because it is not specified. The purpose of this paper is an assessmet based on Fuzzy-study-rule. This rule is definitely modified fromnon-fuzzy language of qualitative element. The new assessment method of design for disassembility assessment(DFDA) is practical to introduce the fuzzy number as the conversion of quantitative element from qualitative. It is appled to air-cleaner of passenger-vehicle for the usefulness.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.3 no.1
• /
• pp.44-51
• /
• 2003

Knowledge acquisition is a bottleneck in knowledge-based system implementation. Decision tree induction is a useful machine learning approach for extracting classification knowledge from a set of training examples. Many real-world data contain fuzziness due to observation error, uncertainty, subjective judgement, and so on. To cope with this problem of real-world data, there have been some works on fuzzy classification rule learning. This paper makes a survey for the kinds of fuzzy classification rules. In addition, it presents a fuzzy classification rule learning method based on decision tree induction, and shows some experiment results for the method.

• ETRI Journal
• /
• v.37 no.3
• /
• pp.502-511
• /
• 2015

Intrusion detection plays a key role in detecting attacks over networks, and due to the increasing usage of Internet services, several security threats arise. Though an intrusion detection system (IDS) detects attacks efficiently, it also generates a large number of false alerts, which makes it difficult for a system administrator to identify attacks. This paper proposes automatic fuzzy rule generation combined with a Wiener filter to identify attacks. Further, to optimize the results, simplified swarm optimization is used. After training a large dataset, various fuzzy rules are generated automatically for testing, and a Wiener filter is used to filter out attacks that act as noisy data, which improves the accuracy of the detection. By combining automatic fuzzy rule generation with a Wiener filter, an IDS can handle intrusion detection more efficiently. Experimental results, which are based on collected live network data, are discussed and show that the proposed method provides a competitively high detection rate and a reduced false alarm rate in comparison with other existing machine learning techniques.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1274-1276
• /
• 1993

We have designed a multiple-valued fuzzy Approximate Analogical-Reseaning system (AARS). The system uses a similarity measure of fuzzy sets and a threshold of similarity ST to determine whether a rule should be fired, with a Modification Function inferred from the Similarity Measure to deduce a consequent. Multiple-valued basic fuzzy blocks are used to construct the system. A description of the system is presented to illustrate the operation of the schema. The results of simulations show that the system can perform about 3.5 x 106 inferences per second. Finally, we compare the system with Yamakawa's chip which is based on the Compositional Rule of Inference (CRI) with Mamdani's implication.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1999.06a
• /
• pp.29-34
• /
• 1999

We present a practical method for removing biotches and restoring their mission data. To detect blotches, we employ a robust approach of local analysis of spatiotemporal anisotropic brightness continuity Our approach uses first-order spatiotemporal directional derivatives to select the smoothest direction for each examined pixel, and puts out the incorruption probability that he examined pixel may not be corrupted by blotches. As the restoration filter, were employ a spatiotemporal fuzzy filter whose response is adaptively controlled according to a fuzzy rule defined by the incorruption probability. The fuzzy filter is composed of the two different filter of the identity filter and the spatiotemporal directional-weighted-mean filter, and will put out an intermediate value between the original input brightness and the directional-weighted-mean brightness. We design the fuzzy rule in advance by a standard supervised learning fuzzy rule in advance by a standard supervised learning method. The computer simulations are presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.1072-1075
• /
• 1993

To design a fuzzy controller for DC servo-motor, a systematic procedure is proposed. Fuzzy rule base is simply designed through utilizing both the PID gain and the pole-zero cancelation. The results of simulation show that the control system has good performances.