• Earthquakes and Structures
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• 제11권2호
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• pp.347-369
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• 2016

The main objective of this paper is the robust multi-objective optimization design of semi-active tuned mass damper (STMD) system using genetic algorithms and fuzzy logic. For optimal design of this system, it is required that the uncertainties which may exist in the system be taken into account. This consideration is performed through the robust design optimization (RDO) procedure. To evaluate the optimal values of the design parameters, three non-commensurable objective functions namely: normalized values of the maximum displacement, velocity, and acceleration of each story level are considered to minimize simultaneously. For this purpose, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solutions. The torsional effects due to irregularities of the building and/or unsymmetrical placements of the dampers are taken into account through the 3-D modeling of the building. Finally, the comparison of the results shows that the probabilistic robust STMD system is capable of providing a reduction of about 52%, 42.5%, and 37.24% on the maximum displacement, velocity, and acceleration of the building top story, respectively.

• 한국전자통신학회논문지
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• 제12권5호
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• pp.797-804
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• 2017

소셜네트웍은 네트워크와 이터레이션의 특성을 모두 가지는 대표적인 소셜 사이언스 환경이다. 이번 연구는 소셜네트웍에 프로모션이나 인센티브 같은 입력을 주었을 때, 각 노드들이 어떻게 반응하는지에 대한 반응분석 모델을 제시한다. 또한, 각 노드의 반응을 살피면서 특정 노드의 설정 값을 변경한다. 그리고 연관된 노드들의 반응을 파악해 본다. 반응 분석 모델은 단방향, 퍼지집합, 가중치 부여, 순환 피드백 등 다양한 기법을 적용하여 구성되었으므로 실무의 복잡한 환경을 수용할 수 있다. 마지막으로 구현하는 모델은 반복적인 입력, 실시간으로 설정 값을 변경, 노드간의 연관성에 대한 분석을 필요로 하므로 넷로고 보다는 Vensim을 활용하여 구현하였다.

• Journal of Welding and Joining
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• 제14권1호
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• pp.57-67
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• 1996

With an expansion in automation of welding processes, emphasis has been shifted from other welding processes to the GMA welding. However, there is a problem with this process that the spatter occurs very frequently. In GMA welding, there are several types in the way of metal transfer from the electrode wire to the weld pool, which have a close relatonship with the spatter genetration. This study was concerned with the spatter occurring in the short-circuiting transfer. In welding with short-circuiting, the electromagnetic force formed by the welding current facilitatics the rupture of the metal bridge between the wire and workpiece and ensures the normal process of the welding process. However, the spatter can be genetrated from the droplet because of the upward magnetic force, when the droplet contacts with the weld pool. The passage of current through the bridge results in the accumulation of the thermal energy, which causes the bridge to explode in the final stage of short-circuiting, thus forming the spatter. Based on the above phenomena in conjunction with other experimental results published, the physical phenomenon related with the occurrence of spatter was modeled and the current waveform was investigated to reduce the spatter. Finally, the fuzzy rule based method was proposed to predict the time of short-circuiting and arcing in the metal transfer.

• 제어로봇시스템학회논문지
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• 제8권7호
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• pp.589-598
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• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.113-116
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• 2001

이 논문에서는 음악을 시계열 자료로 해석하고 시계열 자료의 퍼지 로직에 기반한 모델링에 대해 설명한다. 음악은 음악적 기호들인 보표, 악센트, 오선, 박자표, 음표, 쉼표 등등과 같은 유한개의 음악적 표기법들로 구성된다. 악보는 음악 해석에 필요한 리듬, 멜로디, 화음등과 달은 다양한 특성을 표현하기 위해 음악적 기호들을 사용한다. 본 논문에서는 각각의 시간에서 소리나는 음들의 비트와 높낮이로 인식한다는 관점에서 음악에서의 비트와 음의 높낮이를 시계열 자료로 표현하는 것이 가능하다. 악보의 규정된 특징들을 바탕으로, 악보를 시계열 자료로 표현하고 시계열을 예측하기 위해 퍼지 로직에 기반한 모델로 구성한다. 제안한 방법의 타당성으로 보이기 위해 몇 가지 예를 제시한다.

• Structural Engineering and Mechanics
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• 제47권3호
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• pp.401-419
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• 2013

In this study, the efficiency of adaptive neuro-fuzzy inference system (ANFIS) and genetic expression programming (GEP) in predicting the effects of infill walls on base reactions and roof drift of reinforced concrete frames were investigated. Current standards generally consider weight and fundamental period of structures in predicting base reactions and roof drift of structures by neglecting numbers of floors, bays, shear walls and infilled bays. Number of stories, number of bays in x and y directions, ratio of shear wall areas to the floor area, ratio of bays with infilled walls to total number bays and existence of open story were selected as parameters in GEP and ANFIS modeling. GEP and ANFIS have been widely used as alternative approaches to model complex systems. The effects of these parameters on base reactions and roof drift of RC frames were studied using 3D finite element method on 216 building models. Results obtained from 3D FEM models were used to in training and testing ANFIS and GEP models. In ANFIS and GEP models, number of floors, number of bays, ratio of shear walls and ratio of infilled bays were selected as input parameters, and base reactions and roof drifts were selected as output parameters. Results showed that the ANFIS and GEP models are capable of accurately predicting the base reactions and roof drifts of RC frames used in the training and testing phase of the study. The GEP model results better prediction compared to ANFIS model.

• 대한전기학회논문지:전력기술부문A
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• 제48권9호
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• pp.1147-1153
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• 1999

The attitude control of a double inverted pendulum with a periodical disturbance at link top is dealt in this paper. The proposed system is consisted of the double inverted pendulum and a disturbing link; a triple inverted pendulum with two motors. The lower link is hinged on the plate to free for rotation in the vertical plane. The upper link is connected to the lower link through a DC motor. The DC motor is used to control the posture of the pendulum by adjusting the position of the upper link. The periodical disturbance can be generated by the additional like attached at the end of link 2 through another DC motor, which is the modeling of a posture for a biped supporting with one leg. The motor for the joint simulates the knee joint(or hip joint) and the disturbance for the legs moving in air. The algorithm for controlling the proposed inverted pendulum which is regarded as a virtual double inverted pendulum with a periodic disturbance, is consisted of a state feedback control and a fuzzy logic controller connected in parallel. The fuzzy controller keeps the center of gravity of the biped within the specified range through the nonlinear feedback compensator. The state feedback control takes over the role to maintain a desired posture regardless the disturbance at the link top. Simulations with a mathematical model and experiments are conducted to show the validity of the proposed controller.

• 한국정밀공학회지
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• 제25권12호
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1997년도 가을 학술발표회 논문집
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• pp.24-31
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• 1997

Recently, in Korea, demand for establishment of systematic risk assessment techniques for construction projects has increased, especially after the large construction failures occurred during construction such as New Haengju Bridge construction projects, subway construction projects, gas explosion accidents etc. Most of existing risk analysis modeling techniques such as Event Tree Analysis and Fault Tree Analysis may not be available for realistic risk assessment of construction projects because it is very complex and difficult to estimate occurrence frequency and failure probability precisely due to a lack of data related to the various risks inherent in construction projects like natural disasters, financial and economic risks, political risks, environmental risks as well as design and construction-related risks. Therefor the main objective of this paper is to suggest systematic probabilistic risk assessment model and demonstrate an approach for probabilistic risk assessment using advanced Event Tree Analysis introducing Fuzzy set theory concepts. It may be stated that the Fuzzy Event Tree AnaIysis may be very usefu1 for the systematic and rational risk assessment for real constructions problems because the approach is able to effectively deal with all the related construction risks in terms of the linguistic variables that incorporate systematically expert's experiences and subjective judgement.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.47-50
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• 2000

In this paper, an optimal identification method using Multi-FNN(Fuzzy-Neural Network) is proposed for model ins of nonlinear complex system. In order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM clustering algorithm which carry out the input-output data preprocessing function and Genetic Algorithm which carry out optimization of model. The proposed Multi-FNN is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. HCM clustering method which carry out the data preprocessing function for system modeling, is utilized to determine the structure of Multi-FNN by means of the divisions of input-output space. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model, To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.