• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.8
• /
• pp.561-570
• /
• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• International Journal of High-Rise Buildings
• /
• v.5 no.4
• /
• pp.251-262
• /
• 2016

Tall Buildings have been one of the most prominent symbols of economic growth for nearly a century. Yet, in the aftermath of the tragedies of September 11, "signature" Tall buildings have become the focus of much debate. The structural systems today are undergoing a major evolution to address the ability of providing flexibility in the design and use of the building together with sustainability (Green) and cost-effective system. This paper describes a new invented structural system, evolutionary structural analysis and design of Tall buildings, which involves the entire analysis process, including conceptual and design stages and comparison with the existing Tall building. This study presents an new innovative structural system, Beehive (Hexagrid), for Tall buildings. The final results are achieved by modeling an 80 story Tall building with the optimized angle and topology of hexagon members by using a computer analysis, ETABS finite element analysis. The objective function of this system is to use one structural system in order to both maximize Eigen frequency for resisting dynamic responses and minimize mean compliance for static responses. Finite element analysis is carried out by using standardized materials. Optimal Hexagrid topologies with the highest stiffness are finally determined to resist both static and dynamic behaviors. Holistic design integration approaches between structures and facades to save energy for environmental control are studied. Innovative design ideas to control structural motion as well as to utilize that motion to harness energy are discussed. Considering abundant emergence of tall buildings all over the world in recent years, the importance of the studies presented in this paper cannot be overemphasized for constructing more sustainable built environments.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1870-1873
• /
• 2004

The objective of this study is to investigate the possibility of chemical process synthesis purely based on mathematical programming when given an objective, feed conditions, product specifications, and model equations for available process units. A method based on a state space approach is proposed, and applied to an example problem with a reactor, a heat exchanger, and a separator. The results indicate that a computer can automatically synthesize an optimal process without any heuristics or expertise in process design provided that global optimization techniques are improved to be suitable for large problems.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.28 no.6
• /
• pp.726-731
• /
• 2004

This paper suggests a material mixing method to mix several materials in a structure. This method is based on ESO(Evolutionary Structural Optimization), which has been used to optimize topology of only one material structure. In this study, two criterions for material transformation and element removal are implemented for mixing several materials in a structure. Optimal topology for a multiple material structure can be obtained through repetitive application of the two criterions at each iteration. Two practical design examples of a short cantilever are presented to illustrate validity of the suggested material mixing method. It is found that the suggested method works very well and a multiple material structure has more stiffness than one material structure has under the same mass.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.340-342
• /
• 2004

In this paper, we introduce a new category of fuzzy inference systems baled on information granulation to carry out the model identification of complex and nonlinear systems. Informal speaking, information granules are viewed as linked collections of objects(data, in particular) drawn together by the criteria of proximity, similarity, or functionality. Granulation of information with the aid of Hard C-Means(HCM) clustering algorithm help determine the initial parameters of fuzzy model such as the initial apexes of the membership functions and the initial values of polyminial functions being used in the premise and consequence part of the fuzzy rules. And the initial parameters are tuned effectively with the aid of the genetic algorithms(GAs) and the least square method. The proposed model is contrasted with the performance of the conventional fuzzy models in the literature.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2004.07b
• /
• pp.619-622
• /
• 2004

본 논문에서는 진화 전략 알고리즘(Evolution Strategy Algorithm)를 이용한 L1B4 선형 초음파 모터(L1B4-USM)의 최적 설계 기법을 제시하고자 한다. 유한요소법(Finite Element Method)을 정식화 하였고, 2차원 유한요소법을 L1B4-USM의 임피던스와 모드의 해석을 통해 검증 하였다. 검증된 2차원 유한 요소 해석을 통한 선형 초음파 모터의 임피던스 해석, mode 해석 및 최적 모드의 탐색 프로그램, 자동 요소분할 프로그램 그리고 진화 전략 알고리즘을 수행하였다. 이를 통해 선형 초음파 모터의 L1모드, B4 모드 각각이 발생하는 공진주파수를 일치시키며, 최대 속도를 얻기 위한 최적 설계기법을 완성 하였고, 최적화된 형상의 L1B4-USM를 설계하였다.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.10a
• /
• pp.259-264
• /
• 2003

This paper suggests a material mixing method to mix several materials in a structure. This method is based on ESO(Evolutionary Structural Optimization), which has been used to optimize topology of only one material structure. In this study, two criterions for material transformation and element removal are implemented for mixing several materials in a structure. Optimal topology for a multiple material structure can be obtained through repetitive application of the two criterions at each iteration. Two practical design examples of a short cantilever are presented to illustrate validity of the suggested material mixing method. It is found that the suggested method works very well and a multiple material structure has more stiffness than one material structure has under the same mass.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.5
• /
• pp.624-636
• /
• 2006

This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

• Smart Structures and Systems
• /
• v.26 no.6
• /
• pp.797-807
• /
• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.37 no.4
• /
• pp.537-545
• /
• 2013

The elastic recovery of a metal seal is a factor that can be used to assess its sealing performance. In this study, a compliant mechanism topology optimization has been performed to find a structure of a metal O-ring seal that can maintain excellent sealing performance with a maximized elastic recovery over extended operation. An evolutionary structural optimization (ESO) was used as a topology optimization algorithm with two different types of objective functions considering both flexibility and stiffness. In particular, a circular design domain was adopted to consider the outer shape of the metal O-ring seal. The elastic recovery of the optimal topology was calculated and compared to that of a commercial product.