• Journal of information and communication convergence engineering
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• 제20권2호
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• pp.137-142
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• 2022

Monolithic three-dimensional (M3D) logics such as M3D-NAND, M3D-NOR, M3D-buffer, M3D 2×1 multiplexer, and M3D D flip-flop, consisting of modularized M3D inverters (M3D-INVs), have been proposed. In the previous M3D logic, each M3D logic had to be designed separately for a standard cell library. The proposed M3D logic is designed by placing modularized M3D-INVs and connecting interconnects such as metal lines or monolithic inter-tier-vias between M3D-INVs. The electrical characteristics of the previous and proposed M3D logics were simulated using the technology computer-aided design and Simulation Program with Integrated Circuit Emphasis with the extracted parameters of the previously developed LETI-UTSOI MOSFET model for n- and p-type MOSFETs and the extracted external capacitances. The area, propagation delay, falling/rising times, and dynamic power consumption of the proposed M3D logic are lower than those of previous versions. Despite the larger space and lower performance of the proposed M3D logic in comparison to the previous versions, it can be easily designed with a single modularized M3D-INV and without having to design all layouts of the logic gates separately.

• 한국지능시스템학회논문지
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• 제18권6호
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• pp.842-848
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• 2008

본 논문에서는 비선형 모델의 설계를 위해 Type-2 퍼지 논리 집합을 이용하여 불확실성 문제를 다룬다. 제안된 모델은 규칙의 전 후반부가 Type-2 퍼지 집합으로 주어진 Type-2 퍼지 논리 시스템을 설계하고 불확실성의 변화에 대한 비선형 모델의 성능을 해석한다 여기서 규칙 전반부 멤버쉽 함수의 정점 선택은 C-means 클러스터링 알고리즘을 이용하고, 규칙 무반부 퍼지 집합의 정점 결정에는 경사 하강법(Gradient descent method)을 이용한 오류 역전파 알고리즘을 사용하여 학습한다. 또한, 제안된 모델에 관련된 파라미터는 입자 군집 최적화(Particle Swarm Optimization; PSO) 알고리즘으로 동조한다. 제안된 모델은 모의 데이터집합(Synthetic dadaset), Mackey-Glass 시계열 공정 데이터를 적용하여 논증되고, 기존 Type-1 퍼지 논리 시스템과의 근사화 및 일반화 능력에 대하여 비교 토의한다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권11호
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• pp.1560-1567
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• 2004

모델 체킹에서 고려해야 할 상태의 수는 모델의 크기에 따라 지수적으로 증가한다. 이것을 상태 폭발 문제라고 부르며 이를 해결하기 위한 방법으로 추상화, 반순서, 대칭성 등이 폭 넓게 사용되고 있다. 이들 방법들은 모델의 구조 정보를 이용하여 모델의 크기를 축소하는 데 목표를 두고 있다. 이와는 달리, 본 논문에서는 논리식을 순서적으로 분할하여 차례대로 모델 체킹을 수행하는 릴레이 모델 체킹을 제안한다. 그리고 기존 모델 체킹 기법으로 해결하지 못했던 상태 폭발 문제를 릴레이 모델 체킹으로 해결한 경험을 기술한다.

• Computers and Concrete
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• 제12권2호
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• pp.109-129
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• 2013

This work presents an approach to model concrete shrinkage. The goal is to permit the concrete industry's experts to develop independent prediction models based on a reduced number of experimental data. The proposed approach combines fuzzy logic and genetic algorithm to optimize the fuzzy decision-making, thereby reducing data collection time. Such an approach was implemented for an experimental data set related to self-compacting concrete. The obtained prediction model was compared against published experimental data (not used in model development) and well-known shrinkage prediction models. The predicted results were verified by statistical analysis, which confirmed the reliability of the developed model. Although the range of application of the developed model is limited, the genetic-fuzzy approach introduced in this work proved suitable for adjusting the prediction model once additional training data are provided. This can be highly inviting for the concrete industry's experts, since they would be able to fine-tune their models depending on the boundary conditions of their production processes.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2064-2066
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• 2002

This paper proposes Model Reference Adaptive Fuzzy System(MRAFS) using Fuzzy Logic Controller(FLC) as a adaptive laws in Model Reference Adaptive System(MRAS) in order to realize the speed-sensorless control of an induction motor. MRAFS estimates the speed of an induction motor with a rotor flux of a reference model and adjustable model in MRAS. Fuzzy logic controller reduces the error of the rotor flux between the reference model and the adjustable model using the error and the change of error as the input of FLC. The computer simulation is executed to verify the propriety and the effectiveness of the proposed system.

• 한국조경학회지
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• 제24권4호
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• pp.96-111
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• 1997

This study was carried out to identify users' choice behavior of theme parks. overland. Lotte World, Seoul Land, Dreamland and Children's Grand Park were selected as study areas. Both multinomial logic model(MNL), nested logic model(NMNL) and joint logit model wet$.$e test using a choice-based sample collected on study areas. Hausman-McFadden test showed that the MNL is not appropriate because the IIA assumption is violated. To avoid the problematic IIA assumption, the NMNL was tested. It splits similar alternatives into groups and nests separate decisions into hierarchical order to avoid the IIA assumption. Cluster analysis and discriminant analysis were conducted to find applicable nest structures. The inclusive value coefficient was 0.7788. It meant that sufficient condition of this model is met and users' choice behavior can be better understood by NMNL than MNL. The $\rho$2 value and accuracy of prediction of this model were 0.402 and 46.33% , respectively. Several comments were suggested to make the NMNL to be more reliable for future research on users' choice behavior of theme park.

• 한국지능시스템학회논문지
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• 제5권2호
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• pp.79-85
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• 1995

In this paper, a fuzzy logic is applied to a model-following control(MFC) to form a fuzzy model following control(FMFC). The feedback gain the MFC is adjusted continuously through the fuzzy logic rule. The proposed fuzzy-MFC is applied to synthesize controllers for linear time inveriant(LTI) systems with parameter uncertainties, and the robustness results of the proposed designs are compared.

• 대한전자공학회논문지
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• 제26권10호
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• pp.1591-1597
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• 1989

Through the matematical alaysis of EX-NOR logic relation between the input vector and the memory matrix, we propose a new method for optical implementation of the bipolar Hopfield neural network model based on the optical vector-matrix multiplier.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.93.1-93
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• 2001

An evolutionary approach for the design of Fuzzy Logic Systems(FLSs) is proposed. Membership functions(MFs) in Takagi-Sugeno type fuzzy logic system is optimized through evolutionary process. Output singleton values are obtained through pseudo-inverse method. The proposed technique is unique for that, to prevent overfilling phenomenon, limited-level RBF membership functions are used and the new fitness function is invented. To show the effectiveness of the proposed method, some simulations results on model identification are given.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.56-61
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• 2001

Activated sludge processes are broadly used in the biological wastewater treatment processes. The activated sludge processes are complex systems because of the many factors such as the variation of influent flowrate and ingredients, the complexity of biological reactions, and the various operation conditions. The main motivation o this research is to develop an intelligent control strategy for activated sludge process (ASP). ASP is a complex and nonlinear dynamic system owing to the characteristic of wastewater, the change in influent flowrate, weather conditions, and so on. The mathematical model of ASP also includes the uncertainty which is a ignored or unconsidered factor from process designers. The ASP model based on Matlabⓡ/Simulinkⓡ is developed in this paper. And the model performance is examined by IWA (International Water Association) and COST (European Cooperation in the filed of Scientific and Technical Research) data. The model tests derive steady-state results of 14 days. In this paper, fuzzy logic control approach is applied to handle DO concentrations. The fuzzy logic controller includes two inputs and one output to adjust air flowrate. The objective function for the optimization, in the implemented evolutionary strategy, is formed with focusing on improving the effluent quality and reducing the operating cost.