• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.68-77
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• 1997

The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine the weighting parameters of the LQR system. This optimizing tool provides a more systematic approach in designing the LQR system. Since it can be easily incorporated with any forms of the cost function, it also provides the great flexibility in the optimization problems.

• Journal of Korea Water Resources Association
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• v.41 no.8
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• pp.807-823
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• 2008

This paper presents a technique for estimating discharge rating curve parameters. In typical practical applications, the original non-linear rating curve is transformed into a simple linear regression model by log-transforming the measurement without examining the effect of log transformation. The model of pseudo-likelihood estimation is developed in this study to deal with heteroscedasticity of residuals in the original non-linear model. The parameters of rating curves and variance functions of errors are simultaneously estimated by the pseudo-likelihood estimation(P-LE) method. Simulated annealing, a global optimization technique, is adapted to minimize the log likelihood of the weighted residuals. The P-LE model was then applied to a hypothetical site where stage-discharge data were generated by incorporating various errors. Results of the P-LE model show reduced error values and narrower confidence intervals than those of the common log-transform linear least squares(LT-LR) model. Also, the limit of water levels for segmentation of discharge rating curve is estimated in the process of P-LE using the Heaviside function. Finally, model performance of the conventional log-transformed linear regression and the developed model, P-LE are computed and compared. After statistical simulation, the developed method is then applied to the real data sets from 5 gauge stations in the Geum River basin. It can be suggested that this developed strategy is applied to real sites to successfully determine weights taking into account error distributions from the observed discharge data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.2
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• pp.303-310
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• 2017

Evapotranspiration is a significant hydrologic quantity for understanding the amount of available water resource evaluation, water balance analysis, water circulation and energy circulation. Various methods have been developed for estimating the evapotranspiration using data observed at meteorological observatories. Especially, the focus of methods has been on the complementary relationship that the actual evapotranspiration is equal to the difference between the twice of evapotranspiration in the wet condition and the potential evapotranspiration. The Granger and Gary (GG) method is an empirical formula that can be used to estimate the evapotranspiration using only empirical parameters based on the complementary relationship and using only the net radiation and temperature of the region. In this study, we compared the evapotranspiration data observed at 10 sites in Asia within the dataset of FLUXNET2015, with the evapotranspiration calculated by GG method. The evapotranspiration in inland area was estimated more accurately than that of coastal area. Simulated Annealing (SA) was used for the coastal area to modify the parameters. Using the modified GG method, we could improve the statistics such as root mean square error, the coefficient of determination ($R^2$), and the mean absolute ${\mid}BIAS{\mid}$ of the evapotranspiration estimation in coastal area.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.748-753
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• 2005

Among processes to manufacture parts from footwear materials like upper leathers, one of the most essential processes is the cutting one optimally arranging lots of parts on raw footwear materials and cutting. A new nesting strategy was proposed for the 2-dimensional part layout by using a two-stage approach, where which can be effectively used for water jet cutting. In the initial layout stage, a SOAL(Self-Organization Assisted Layout) based on the combination of FCM(Fuzzy C-Means) and SOM was adopted. In the layout improvement stage, SA(Simulated Annealing) based approach was adopted for a finer layout. The proposed approach saves much CPU time through a two-stage approach scheme, while other annealing-based algorithm so far reported fur a nesting problem are computationally expensive. The proposed nesting approach uses the stochastic process, and has a much higher possibility to obtain a global solution than the deterministic searching technique. We developed the automatic nesting software of NST(ver.1.1) software for footwear industry by implementing of these proposed algorithms. The NST software was applied by the optimized automatic arrangement algorithm to cut without the loss of leathers. if possible, after detecting damage areas. Also, NST software can consider about several features in not only natural loathers but artificial ones. Lastly, the NST software can reduce a required time to implement generation of NC code. cutting time, and waste of raw materials because the NST software automatically performs parts arrangement, cutting paths generation and finally NC code generation, which are needed much effect and time to generate them manually.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.3
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• pp.187-195
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• 2017

The operation planning of transports used to move blocks is the one of key factors. Furthermore, reducing the running time through the effective plan contributes to pulling forward the whole logistic process of the shipyard and substantially saving the fuel consumption of itself as well. The past researches of the transporter focused on finding only the shortest distances, so called, Manhattan distance. However, these searching approaches cannot help having the significant difference in the real operational time and distance with the minimum cost approach which considers the speed retardation for turns or safety at the intersection. This study suggests the noble transporter's operational model which could take account of the consuming operational time around the crossroads on the shipyard. Concretely, the proposed method guarantees the minimization of transporters' turns and passage number which are huge burdensome to the operation time and the whole planning of transports with the given period. Resultantly, this paper is willing to explain the appropriateness of our approach, compared with the previous ones.

• Korean Journal of Optics and Photonics
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• v.14 no.4
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• pp.377-382
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• 2003

We propose a new optical watermarking method, which can protect the copyright of digital data, using a binary phase hologram and a Mach-Zehnder interferometer. Using a simulated annealing algorithm, the binary phase hologram of the mark image to be hidden is designed. We obtained a watermarked image by linearly superposing the hologram, which is the watermark, in the original image. The extraction processing of the mark image from the watermarked image is achieved by placing the phase-modulated watermarked image on a LCD in one path and the phase-modulated original image on another LCD in the other path in the Mach-Zehnder interferometer. The mark image was obtained by inverse Fourier transforming the phase modulated interference intensity. We confirmed that the proposed method is robust for the cropped images through computer simulation, and we implemented it optically using LCDs which are phase modulation devices.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.49-56
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• 2008

Reliability has been considered as an important design measure in various industrial systems. We discuss a reliability optimization problem with component choices (ROP-CC) subject to a budget constraint. This problem has been known as a NP-hard problem in the reliability design fields. Several researchers have been working to find the optimal solution through different heuristic methods. In this paper, we describe our development of simulated annealing (SA) and tabu search (TS) algorithms and a reoptimization procedure of the two algorithms for solving the problem. Experimental results for some examples are shown to evaluate the performance of these methods. We compare the results with the solutions of a previous study which used ant system (AS) and the global optimal solution of each example obtained through an optimization package, CPLEX 9.1. The computational results indicate that the developed algorithms outperform the previous results.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2166-2176
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• 2017

Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.6
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• pp.133-149
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• 2017

As cities face increasing problems such as aging, environmental pollution and growth limits, we have been trying to incorporate sustainability into urban planning and related policies. However, it is very difficult to generate a 'sustainable spatial plans' because there are trade-offs among environmental, society, and economic values. This is a kind of non-linear problem, and has limitations to be solved by existing qualitative expert knowledge. Many researches from abroad have used the meta heuristic optimization algorithms such as Genetic Algorithms(GAs), Simulated Annealing(SA), Ant Colony Optimization(ACO) and so on to synthesize competing values in spaces. GAs is the most frequently applied theory and have been known to produce 'good-enough plans' in a reasonable time. Therefore we collected the research on 'spatial optimization model based GAs' and analyzed in terms of 'study area', 'optimization objective', 'fitness function', and 'effectiveness/efficiency'. We expect the results of this study can suggest that 'what problems the spatial optimization model can be applied to' and 'linkage possibility with existing planning methodology'.

• Advances in Computational Design
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• v.1 no.4
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• pp.315-327
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• 2016

Damage detection and localisation in structures is essential since it can be a means for preventive maintenance of those structures under service conditions. The use of structural modal data for detecting the damage is one of the most efficient methods. This paper presents comparative performance of various state-of-the-art meta-heuristics for use in structural damage detection based on changes in modal data. The metaheuristics include differential evolution (DE), artificial bee colony algorithm (ABC), real-code ant colony optimisation (ACOR), charged system search (ChSS), league championship algorithm (LCA), simulated annealing (SA), particle swarm optimisation (PSO), evolution strategies (ES), teaching-learning-based optimisation (TLBO), adaptive differential evolution (JADE), evolution strategy with covariance matrix adaptation (CMAES), success-history based adaptive differential evolution (SHADE) and SHADE with linear population size reduction (L-SHADE). Three truss structures are used to pose several test problems for structural damage detection. The meta-heuristics are then used to solve the test problems treated as optimisation problems. Comparative performance is carried out where the statistically best algorithms are identified.