• 전기학회논문지
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• 제67권3호
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• pp.419-426
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• 2018

An useful and effective design method for the gas identification system is presented in this paper. The proposed gas identification system adopts hierarchical structure with two level rule base combining fuzzy sets with rough sets. At first, a hybrid genetic algorithm is used in grouping the array sensors of which the measured patterns are similar in order to reduce the dimensionality of patterns to be analyzed and to make rule construction easy and simple. Next, for low level identification, fuzzy inference systems for each divided group are designed by using TSK fuzzy rule, which allow handling the drift and the uncertainty of sensor data effectively. Finally, rough set theory is applied to derive the identification rules at high level which reflect the identification characteristics of each divided group. Thus, the proposed method is able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.438-447
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• 2006

Fuzzy controller's design depends mainly on the rule base and membership functions over the controller's input and output ranges. This paper presents two different approaches to deal with these design issues. A simple and efficient approach; namely, Fuzzy Subtractive Clustering is used to identify the rule base needed to realize Fuzzy PI and PD type controllers. This technique provides a mechanism to obtain the reduced rule set covering the whole input/output space as well as membership functions for each input variable. But it is found that some membership functions projected from different clusters have high degree of similarity. The number of membership functions of each input variable is then reduced using a similarity measure. In this paper, the fuzzy subtractive clustering approach is shown to reduce 49 rules to 8 rules and number of membership functions to 4 and 6 for input variables (error and change in error) maintaining almost the same level of performance. Simulation on a wide range of linear and nonlinear processes is carried out and results are compared with fuzzy PI and PD type controllers without clustering in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error (IAE) and integral-of-time multiplied absolute error (ITAE) and in each case the proposed schemes shows an identical performance.

• Structural Engineering and Mechanics
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• 제83권4호
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• pp.537-549
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• 2022

In this paper, a novel multi-feature model predictive control (MPC) framework with real-time and adaptive performances is proposed for intelligent structural control in which some drawbacks of the algorithm including, complex control rule and non-optimality, are alleviated. Hence, Linear Programming (LP) is utilized to simplify the resulted control rule. Afterward, the Whale Optimization Algorithm (WOA) is applied to the optimal and adaptive tuning of the LP weights independently at each time step. The stochastic control rule is also achieved using Kalman Filter (KF) to handle noisy measurements. The Extreme Learning Machine (ELM) is then adopted to develop a data-driven and real-time control algorithm. The efficiency of the developed algorithm is then demonstrated by numerical simulation of a twenty-story high-rise benchmark building subjected to earthquake excitations. The competency of the proposed method is proven from the aspects of optimality, stochasticity, and adaptivity compared to the KF-based MPC (KMPC) and constrained MPC (CMPC) algorithms in vibration suppression of building structures. The average value for performance indices in the near-field and far-field (El earthquakes demonstrates a reduction up to 38.3% and 32.5% compared with KMPC and CMPC, respectively.

• 음성과학
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• 제4권2호
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• pp.5-15
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• 1998

This paper proposes a speech state-dependent spectral subtraction method to regulate the blind spectral subtraction for improved enhancement. In the proposed method, a modified subtraction rule is applied over the speech selectively contingent to the speech state being voiced or unvoiced, in an effort to incorporate the acoustic characteristics of phonemes. In particular, the objective of the proposed method is to remedy the subtraction induced signal distortion attained by two state-dependent procedures, spectrum sharpening and minimum spectral bound. In order to remove the residual noise, the proposed method employs a procedure utilizing the masking effect. Proposed spectral subtraction including state-dependent subtraction and residual noise reduction using the masking threshold shows effectiveness in compensation of spectral distortion in the unvoiced region and residual noise reduction.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2013년도 제47차 동계학술대회논문집 21권1호
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• pp.291-294
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• 2013

연관 규칙 감축 기법은 대규모 데이터를 사용하는 Socially aware computing분야에서 매우 중요한 이슈이다. 본 논문에서는 수집된 각종 데이터들을 각 속성 기준에 따라 이진 변환한 후 가중치를 부여하고 논리식 감축 방법을 이용하여 신뢰성을 보장하는 규칙을 도출하는 새로운 데이터 감축 기법을 제안한다. 이는 컴퓨터 시뮬레이션 결과 기존의 방식들에 비해 지지도, 신뢰도, 규칙 감소율, 연관 규칙 추출 시간에 좋은 성능을 보였으며 이는 빠른 시간 내에 신뢰성 높은 대규모 데이터 처리가 필요한 Socially aware computing분야에 적합하다고 판단한다.

• 대한산업공학회지
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• 제16권2호
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• pp.63-70
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• 1990

This paper presents a new temporal reasoning scheme based on explicit expression of time intervals. The proposed scheme deals with the general problem of temporal knowledge representation and temporal reasoning and may be used in rule-based systems and qualitative models. Time intervals, not time points, are defined in terms of orders and/or numbers in a quantity space. As a result, the system behavior is represented in the form of partially ordered networks. Such explicit and qualitative description of temporal quantities enables both reduction of ambiguity and parsimonious used of temporal information. Based on the proposed temporal reasoning scheme, a new rule-based qualitative simulation system is being built and evaluated.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.2142-2143
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• 2006

Today any data storage system cannot satisfy all of these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanically actuating part therefore fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this research, to reduce errors of binary data stored in holographic data storage system, a new method for bit error reduction is suggested. Firstly, find fuzzy rule to use test bed system for Element of Holographic Digital Data System. Secondly, make fuzzy rule table using DNA coding method. Finally, reduce prior error element and recording digital data. Recording ratio and reconstruction ratio show good performance.

• International Journal of Quality Innovation
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• 제2권2호
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• pp.24-33
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• 2001

As we know, the quality of processes is technically depicted by variation, a product or process with the best quality must naturally require the variation as less as possible. The variation is usually reduced with many ways, say, by adjusting parameters settings under robust design with many turns expensive experiments. So ones are trying to reach the robustness by detecting cheap and simple methods. In this paper, a both practical and simple technique for quality improvement, namely reducing the variation, by data classification is studied. First, all possible system factors are included, which may dominate the variation law. And then we make use of the past observations and their classification as well as boxplot charts to find out the internal rule between the variation and the system factor. Next, adjust the location of the system factor according to the rule so that the variation could, to some extent, be lessened. Finally, two typical quality improvement cases based on data classification are presented.

• 한국지능시스템학회논문지
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• 제2권3호
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• pp.40-49
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• 1992

In this paper, an approach to identify fuzzy rules is proposed. The decision of the optimal number of fuzzy rule is made by means of fuzzy c-means clustering. The identification of the parameters of fuzzy implications is carried out by use of genetic algorithms. For the efficinet and fast parameter identification, the reduction thechnique of search areas of genetica algorithms is proposed. The feasibility of the proposed approach is evaluated through the identification of the fuzzy model to describe an input-output relation of Gas Furnace. Despite the simplicity of the propsed apprach the accuracy of the identified fuzzy model of gas furnace is superior as compared with that of other fuzzy modles.

• 한국방재학회 논문집
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• 제8권5호
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• pp.137-145
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• 2008

이 연구는 계획규모를 초과하는 홍수량으로 인하여 예상되는 하천범람피해를 경감하기 위한 지하방수로 계획에서의 적정 위치선정 및 규모를 결정하기 위한 기초분석기술에 대한 것으로서, 1998년과 2001년에 집중호우로 일부제방의 범람 및 붕괴에 의해 막대한 손실이 발생한 중랑천을 대상으로 하였다. 지하방수로의 유입부 위치는 200년 빈도홍수에 취약한 서울시경계, 당현천 합류부, 월계 1교, 묵동천 합류부의 4곳을 후보지로 선정하였고, 유출부는 국공유지로서 사용이 가능한 중랑천하구부와 한강의 반포대교 우안부을 선정하였다. 유입부의 월류고별 횡월류량을 산정하고 홍수저감효과를 분석하였다. 검토결과, 유입부의 위치는 당현천 합류부가 적정한 것으로 판단되었는바, 이곳에 지하방수로 유입부를 설치하였을 때 홍수저감효과가 가장 큰 것으로 나타났다. 지하방수로의 적정규모검토를 위해 방류구 운영규칙을 단순저류, 일정률, 일정량, 일정률+일정량의 혼합방류의 4가지 방식을 기본으로 하는, 총 8가지 경우를 적용하여 비교 분석하였다. 200년 규모의 홍수에 대응하는 지하방수로의 적정규모를 검토한 결과 방수로의 크기는 단순저류(Rule D)일때 가장 큰 규모인 직경 12 m로 분석되었고, 일정률 방류(Rule E)에서는50%방류에서 직경 9 m, 일정량 방류(Rule F)에서는 직경 8 m, 일정량 + 일정률 방류(Rule G)의 경우는 직경 7 m로 각각 산정하였다. 이 연구에서 제시한 검토과정은 하천제방의 범람으로 연안의 침수피해가 막대할 것으로 예상되는 경우에 EAP 차원에서의 방수로 건설 계획에 유용할 것으로 판단된다. 또한, 중랑천 방수로를 건기시에는 서울시와 의정부지역을 연결하는 지하 도로로 활용하는 방안을 함께 고려함으로써 방수로의 활용성을 크게 증대시킬 수 있을 것으로 판단된다.