• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.1-20
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• 2018

Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability across multiple Cloud providers. A new hybrid multi-objective evolutionary algorithm to perform the above task called LS-NSGA-II-DE is proposed, in which the differential evolution (DE) algorithm uses the adaptive mutation operator and crossover operator to replace the those of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to get the better convergence and diversity. At the same time, a Local Search (LS) method is performed for the Non-dominated solution set F{1} in each generation to improve the distribution of the F{1}. The simulation results show that our proposed algorithm performs well in terms of the solution distribution and convergence, and in addition, the optimality ability and scalability are better compared with those of the other algorithms.

• Advances in Computational Design
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• v.2 no.1
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• pp.29-42
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• 2017

This study presents algorithms for determining the fuzzy critical loads of planar steel frame structures with fixity factors of beam - column and column - base connections are modeled as triangular fuzzy numbers. The finite element method with linear elastic semi-rigid connection and Response Surface Method (RSM) in mathematical statistic are applied for problems with symmetric triangular fuzzy numbers. The ${\alpha}$ - level optimization using the Differential Evolution (DE) involving integrated finite element modeling is proposed to apply for problems with any triangular fuzzy numbers. The advantage of the proposed methodologies is demonstrated through some example problems relating to for the twenty - story, four - bay planar steel frames.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1964-1965
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• 2011

본 연구에서는 패턴분류를 위해 기존의 방사형 기저 함수 신경회로망(Radial Basis Funtion Neural Network)과 다항식 신경회로망(Polynomial Neural Network)을 결합한 다중 출력 방사형 기저 함수다항식 신경회로망 (Multi Output Radial Basis Funtion Polynomial Neural Network)의 분류기를 제안한다. 제안된 모델은 PNN을 기본 구조로 하여 1층에 기존의 다항식 노드 대신 다중 출력 형태의 RBFNN을 적용 한다. RBFNN의 은닉층에는 기존의 활성함수가 아닌 fuzzy 클러스터링을 사용하여 입력 데이터의 특성을 고려한 적합도를 사용하였다. PNN은 입력변수의 수와 다항식 차수가 모델의 성능을 결정함으로 최적화가 필요하며 본 논문에서는 Differential Evolution(DE)을 사용하여 모델의 구조 및 파라미터를 최적화시켜 모델의 성능을 향상시켰다. 패턴분류기로써의 제안된 모델을 평가하기 위해 pima 데이터를 이용하였다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1962-1963
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• 2011

본 연구에서는 패턴분류를 위해 최적화된 방사형 기저 함수 신경회로망(Radial Basis Function Neural Networks) 분류기를 제안한다. RBFNN은 입력층, 은닉층, 출력층의 3층 구조로 되어 있으며 Multi Dimension, Predictive ability, Robustness한 특징이 있다. RBFNN의 은닉층에는 기존의 활성함수가 아닌 Fuzzy C-means 클러스터링 알고리즘을 사용하여 입력 데이터의 특성을 고려한 적합도를 사용하였다. RBFNN은 은닉층의 노드수와 FCM 클러스터링의 퍼지화 계수, 연결가중치의 다항식 타입이 모델의 성능의 향상에 영향을 미치기 때문에 최적화가 필요하며 본 논문에서는 Differential Evolution(DE) 알고리즘을 사용하여 모델의 구조 및 파라미터를 최적화시켜 모델의 성능을 향상시켰다. 제안된 모델을 평가하기 위해 패턴분류에 많이 사용되는 Iris 데이터와 Wine 데이터를 이용하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.82-84
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• 2016

We propose a new reliable SVD-based watermarking scheme having high fidelity and strong robustness with no false-positive problem. Each column of the principal component of a watermark image is embedded into singular values of LL, LH, HL and HH sub-bands of cover image with different scale factors. Each scale factor is optimized by trading-off fidelity and robustness using Differential Evolution (DE) algorithm. The proposed scheme improves fidelity and robustness of existing reliable SVD based watermarking schemes without any false-positive problem. Index Terms - watermarking, reliable SVD, DWT, principal component, Differential Evolution.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1099-1109
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• 2018

For practical consideration, economic dispatch (ED) problems in power system have non-smooth cost functions with equality and inequality constraints that makes the problems complex constrained nonlinear optimization problems. This paper proposes a new constraint handling method for equality and inequality constraints which is employed to solve ED problems, where the incremental rate is employed to enhance the modification process. In order to prove the applicability of the proposed method, the study cases are tested based on the classical particle swarm optimization (PSO) and differential evolution (DE) algorithm. The proposed method is evaluated for ED problems using six different test systems: 6-, 15-, 20-, 38-, 110- and 140-generators system. Simulation results show that it can always find the satisfactory solutions while satisfying the constraints.

• Advances in Computational Design
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• v.4 no.3
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• pp.197-210
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• 2019

Motion generation of a four-bar linkage is a type of mechanism synthesis that has a wide range of applications such as a pick-and-place operation in manufacturing. In this research, the use of meta-heuristics for motion generation of a four-bar linkage is demonstrated. Three problems of motion generation were posed as a constrained optimization probably using the weighted sum technique to handle two types of tracking errors. A simple penalty function technique was used to deal with design constraints while three meta-heuristics including differential evolution (DE), self-adaptive differential evolution (JADE) and teaching learning based optimization (TLBO) were employed to solve the problems. Comparative results and the effect of the constraint handling technique are illustrated and discussed.

• Advances in Computational Design
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• v.8 no.4
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• pp.327-351
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• 2023

This article explores how multi-objective optimization techniques can be used to design cost-effective and structurally optimal spatial steel structures, highlighting that optimizing performance can be as important as minimizing costs in real-world engineering problems. The study includes the minimization of maximum horizontal displacement, the maximization of the first natural frequency of vibration, the maximization of the critical load factor concerning the first global buckling mode of the structure, and weight minimization as the objectives. Additionally, it outlines a systematic approach to selecting the best design by employing four different evolutionary algorithms based on differential evolution and a multi-criteria decision-making methodology. The paper's contribution lies in its comprehensive consideration of multiple conflicting objectives and its novel approach to simultaneous consideration of bracing system, column orientation, and commercial profiles as design variables.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.33.1-33.1
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• 2018

The differential rotational properties of early-type galaxies (ETGs) revealed by integral field spectroscopy surveys is arguably one of the most exciting findings in the galaxy evolution study during the past decade. Numerical studies have shown that galaxy mergers under various configurations can reproduce the observed distribution of ETG spin. However, we suggest an alternative scenario for the spin evolution of a large fraction of ETGs. Using the Horizon-AGN simulation, we follow the spin evolution of 10037 color-selected ETGs more massive than 1010 Msun that are divided into four groups: cluster centrals (3%), cluster satellites (33%), group centrals(5%), and field ETGs (59%). We find a strong mass dependence of the slow rotator fraction, fSR, and the mean spin of massive ETGs. Although the environmental dependence is not clear in the fSR, it is visible in the mean value of the spin parameter. The environmental dependence is driven by the satellite ETGs whose spin gradually decreases as their environment becomes denser. Galaxy mergers appear to be the main cause of total spin changes in 94% of central ETGs of halos with Mvir > 1012.5 Msun, but only 22% of satellite and field ETGs. We find that non-merger induced tidal perturbations better correlate with the galaxy spin-down in satellite ETGs than mergers. Given that the majority of ETGs are not central in dense environments, we conclude that non-merger tidal perturbation effects played a key role in the spin evolution of ETGs observed in the local (z < 1) universe.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.473-478
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• 2013

In this paper, we develop the Heavy Rain Advisory Decision Model based on intelligent neuro-fuzzy algorithm RBFNNs by using KLAPS(Korea Local Analysis and Prediction System) Reanalysis data. the prediction ability of existing heavy rainfall forecasting systems is usually affected by the processing techniques of meteorological data. In this study, we introduce the heavy rain forecast method using the pre-processing techniques of meteorological data are in order to improve these drawbacks of conventional system. The pre-processing techniques of meteorological data are designed by using point conversion, cumulative precipitation generation, time series data processing and heavy rain warning extraction methods based on KLAPS data. Finally, the proposed system forecasts cumulative rainfall for six hours after future t(t=1,2,3) hours and offers information to determine heavy rain advisory. The essential parameters of the proposed model such as polynomial order, the number of rules, and fuzzification coefficient are optimized by means of Differential Evolution.