• Journal of Mechanical Science and Technology
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• v.16 no.4
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• pp.454-467
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• 2002

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. Toidentifythelocation and depth of a crack in a structure, a method is presented in this paper which uses neuro-fuzzy-evolutionary technique, that is, Adaptive-Network-based Fuzzy Inference System (ANFIS) solved via hybrid learning algorithm (the back-propagation gradient descent and the least-squares method) and Continuous Evolutionary Algorithms (CEAs) solving sir ale objective optimization problems with a continuous function and continuous search space efficiently are unified. With this ANFIS and CEAs, it is possible to formulate the inverse problem. ANFIS is used to obtain the input(the location and depth of a crack) - output(the structural Eigenfrequencies) relation of the structural system. CEAs are used to identify the crack location and depth by minimizing the difference from the measured frequencies. We have tried this new idea on beam structures and the results are promising.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.503-506
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• 2005

In this study, optimization design technique for control of solid-fluid coupled force (sloshing) using evolutionary method is suggested. Artificial neural networks(ANN) and genetic algorithm(GA) is employed as evolutionary optimization method. The ANN is used to analysis of the sloshing and the genetic algorithm is adopted as an optimization algorithm. In the creation of ANN learning data, the design of experiments is adopted to higher performance of the ANN learning using minimum learning data and ALE(Arbitrary Lagrangian Eulerian) numerical method is used to obtain the sloshing analysis results. The proposed optimization technique is applied to the minimization of sloshing of the water in the tank lorry with baffles under 2 second lane change.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.156-159
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• 2008

This paper introduces a remained tensile force estimation method using SI technique based on evolutionary algorithm for externally prestressed tendon. This paper applies the differential evolutionary scheme to SI technique. A virtual model test using ABAQUS 3 dimensional frame model has been made for this work The virtual model is added to the tensile force(28.5kN). Two set of frequencies are extracted respectively from the virtual test and the self-coding FEM 2 dimension model. The estimating tendon tension for the FEM model is 28.31kN. It is that the error in the tendon tension is 1% through the differential evolutionary algorithm. The errors between virtual model and the self-coding FEM model are assumed as the model error.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.317-322
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• 2002

The major operations of Evolutionary Computation include crossover, mutation, competition and selection. Although selection does not create new individuals like crossover or mutation, a poor selection mechanism may lead to problems such as taking a long time to reach an optimal solution or even not finding it at all. In view of this, this paper proposes a hybrid Evolutionary Programming (EP) algorithm that exhibits a strong capability to move toward the global optimum even when stuck at a local minimum using a synergistic combination of the following three basic ideas. First, a "local selection" technique is used in conjunction with the normal tournament selection to help escape from a local minimum. Second, the mutation step has been improved with respect to the Fast Evolutionary Programming technique previously developed in our research group. Finally, the crossover and mutation operations of the Genetic Algorithm have been added as a parallel independent branch of the search operation of an EP to enhance search diversity.

• Smart Structures and Systems
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• v.8 no.4
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• pp.343-365
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• 2011

Structural system identification (SSI) is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms which can cater to large size problems. In this paper, a parameter estimation technique based on evolutionary strategy is presented to overcome some of the difficulties encountered in using the traditional system identification methods in terms of convergence. In this paper, a non-traditional form of system identification technique employing evolutionary algorithms is proposed. In order to improve the convergence characteristics, it is proposed to employ immune algorithms which are proved to be built with superior diversification mechanism than the conventional evolutionary algorithms and are being used for several practical complex optimisation problems. In order to reduce the number of design variables, domain decomposition methods are used, where the identification process of the entire structure is carried out in multiple stages rather than in single step. The domain decomposition based methods also help in limiting the number of sensors to be employed during dynamic testing of the structure to be identified, as the process of system identification is carried out in multiple stages. A fifteen storey framed structure, truss bridge and 40 m tall microwave tower are considered as a numerical examples to demonstrate the effectiveness of the domain decomposition based structural system identification technique using immune algorithm.

• Food Science and Biotechnology
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• v.17 no.5
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• pp.899-903
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• 2008

This study was conducted in order to elucidate the optimum conditions for the extraction of clove that can be used to elicit antibacterial activity against Streptococcus mutans using the evolutionary operation (EVOP)-factorial design technique. Higher antibacterial activity was achieved in a higher extraction temperature of $80^{\circ}C$ ($r=0.7983^{**}$) and in a longer extraction time of 26 hr ($r=0.6867^*$). Antibacterial activity was not effected by differentiation of ethanol concentration in the extraction solvent (r=-0.0683). The maximum antibacterial activity of clove against S. mutans as determined by the EVOP-factorial design technique was obtained at an extraction temperature of $80^{\circ}C$, an extraction time of 26 hr and a 50% ethanol concentration. Furthermore, the population of S. mutans decreased from an initial concentration of 6.850 to 4.195 log CFU/mL in the third set that is more than 2.6 log cycles by EVOP-factorial design technique.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.893-896
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• 1998

A new evolutionary programming technique using multiple subpopulations with completely differnt evolution mechanisms is propsed to solve the optimization problems. Three subpopulations, each has different evolution charcteristics and uses different EP algorithms such as SAEP, AEP and FEP, are cooperating with synergy effect in which it increases the possibility to quickly find the global optimum of continuous optimization problems. Subpopulations evolve in differnt manner and the interaction among these leads to global minimum quickly.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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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.

• The Korean Journal of Food And Nutrition
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• v.31 no.2
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• pp.272-277
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• 2018

This research was conducted to elucidate the optimum conditions for the antibacterial activity of konjak jelly using the evolutionary operation-factorial design technique. In the first set of experiments, concentration of a coagulation agent, soaking liquid, and temperature of water were set to 0.4%, $0.6{\times}10^{-2}N$, and $65^{\circ}C$ as a central point, respectively. The highest antibacterial activity was acquired at E21, in which the number of bacteria was 1.25 log cfu/g. Because the code of changes in the main effect was (-), it could be decided that the central point of the first set was not the optimum point. Although antibacterial activity in the second set was improved, the values of the main effect were higher than that of changes in the mean effect. The central point of third set was concentration of coagulation agent 0.8%, concentration of soaking liquid $1.0{\times}10^{-2}N$, and temperature of water $65^{\circ}C$. It was found that the antibacterial activity of central point in the third set was highest among all the tested set. Further, all the necessary conditions were appropriate to reach the optimum condition. The antibacterial activity of the central point in third set was more than 1,000 times higher than that of E11, in first set.

• Journal of Microbiology and Biotechnology
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• v.17 no.11
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• pp.1880-1884
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• 2007

This study was conducted to find the optimum extraction condition of Gold-Thread for antibacterial activity against Streptococcus mutans using The evolutionary operation-factorial design technique. Higher antibacterial activity was achieved in a higher extraction temperature ($R^2=-0.79$) and in a longer extraction time ($R^2=-0.71$). Antibacterial activity was not affected by differentiation of the ethanol concentration in the extraction solvent ($R^2=-0.12$). The maximum antibacterial activity of clove against S. mutans determined by the EVOP-factorial technique was obtained at $80^{\circ}C$ extraction temperature, 26 h extraction time, and 50% ethanol concentration. The population of S. mutans decreased from 6.110 logCFU/ml in the initial set to 4.125 logCFU/ml in the third set.