• Korean Chemical Engineering Research
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• v.45 no.1
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• pp.73-80
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• 2007

This article aims to optimize the nitrogen removal of a sequencing batch reactor (SBR) through the use of the activated sludge model and iterative dynamic programming (IDP). Using a minimum batch time and a maximum nitrogen removal for minimum energy consumption, a performance index is developed on the basis of minimum area criteria for SBR optimization. Choosing area as the performance index makes the optimization problem simpler and a proper weighting in the performance index makes it possible to solve minimum time and energy problem of SBR simultaneously. The optimized results show that the optimal set-point of dissolved oxygen affects both the total batch time and total energy cost. For two different influent loadings, IDP-based SBR optimizations suggest each supervisory control of batch scheduling and set-point trajectory of dissolved oxygen (DO) concentration, and can save 20% of the total energy cost, while meeting the treatment requirements of COD and nitrogen. Moreover, it shows that the re-optimization of IDP within a batch can solve the modelling error problem due to the influent loading changes, or the process faults.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.681-690
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• 2020

Generally, the design capacity of the rainwater harvesting unit is determined by trial and error method that is repeatedly calculating various analysis scenarios with capacity, reliability, and rainwater utilization ratio, etc. This method not only takes a lot of time to analyze but also involves a lot of calculations, so analysis errors may occur. In order to solve the problem, this study suggested a way to directly determine the minimum capacity to meet arbitrary target reliabilities using the global optimization method. The method was implemented by simulation model with particle swarm optimization (PSO) algorithms using Python language. The pyswarm that is provided as an open-source of python was used as optimization method, that can explore global optimum, and consider constraints. In this study, the developed program was applied to the design data for the rainwater harvesting constructed in Cheongna district 1 in Incheon to verify the efficiency, stability, and accuracy of the analysis. The method of determining the capacity of the rainwater harvesting presented in this study is considered to be of practical value because it can improve the current level of analytical technology.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.193-200
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• 2010

Structural design requires simultaneously to ensure safety by considering quantitatively uncertainties in the applied loadings, material properties and fabrication error and to maximize economical efficiency. As a solution, system reliability-based design optimization (SRBDO), which takes into consideration both uncertainties and economical efficiency, has been extensively researched and numerous attempts have been done to apply it to structural design. Contrary to conventional deterministic optimization, SRBDO involves the evaluation of component and system probabilistic constraints. However, because of the complicated algorithm for calculating component reliability indices and system reliability, excessive computational time is required when the large-scale finite element analysis is involved in evaluating the probabilistic constraints. Accordingly, an algorithm for SRBDO exhibiting improved stability and efficiency needs to be developed for the large-scale problems. In this study, a more stable and efficient SRBDO based on the performance measure approach (PMA) is developed. PMA shows good performance when it is applied to reliability-based design optimization (RBDO) which has only component probabilistic constraints. However, PMA could not be applied to SRBDO because PMA only calculates the probabilistic performance measure for limit state functions and does not evaluate the reliability indices. In order to overcome these difficulties, the decoupled algorithm is proposed where RBDO based on PMA is sequentially performed with updated target component reliability indices until the calculated system reliability index approaches the target system reliability index. Through a mathematical problem and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.331-337
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• 2023

In this paper, we propose a deep learning model to detect lumbar 3 (L3) CT images to determine the occurrence and degree of sarcopenia. In addition, we would like to propose an optimization technique that uses oversampling ratio and class weight as design parameters to address the problem of performance degradation due to data imbalance between L3 level and non-L3 level portions of CT data. In order to train and test the model, a total of 150 whole-body CT images of 104 prostate cancer patients and 46 bladder cancer patients who visited Gangneung Asan Medical Center were used. The deep learning model used ResNet50, and the design parameters of the optimization technique were selected as six types of model hyperparameters, data augmentation ratio, and class weight. It was confirmed that the proposed optimization-based L3 level extraction model reduced the median L3 error by about 1.0 slices compared to the control model (a model that optimized only 5 types of hyperparameters). Through the results of this study, accurate L3 slice detection was possible, and additionally, we were able to present the possibility of effectively solving the data imbalance problem through oversampling through data augmentation and class weight adjustment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.5 s.96
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• pp.472-481
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• 2005

This paper reports the design of RFID reader antennas working in UHF band. The reader antennas were designed using a Pareto Genetic Algorithm(Pareto GA). Antennas were optimized to have circular polarization(CP) with less than 3 dB axial ratio, impedance matching with less than VSWR=2 within the frequency range of UHF, an adequate readable range, a restricted size(kr<2.22) considering the practical condition. After Pareto GA optimization, we selected and built the most suitable antenna design and compared the measured results to the simulations. Operating principle of the antenna was explained by investigating the amplitude and the phase of the induced current on the antenna body. We also researched the stability of the antenna with respect to the manufacturing error and studied the critical design parameters by applying the random error method on the antenna bent points.

• The Journal of the Korea Contents Association
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• v.6 no.7
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• pp.69-78
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• 2006

In this paper, we presents the efficiency and a transmission quality of the system which is composed of the optical elements from physical layer of the active optical ring network. For a simulation it will use the Transmissionmaker WDM and it will be able to observation a optical transmission quality of the optical transmission system. The active optical network is composed of two rings(main ring and sub-ring). It measures the BER(Bit Error Rate) quality which it follows node number from the sub ring and physical distance of the node. Performance analysis from the physical layer becomes the standard of the plan for the efficiency optimization of the active optical ring network. Consequently it will be able to compose the efficient optical transmission system which reflects the physical distance, a traffic demand quantity of each node and a number of users from actual network.

• Journal of the Korean Society for Advanced Composite Structures
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• v.3 no.1
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• pp.16-20
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• 2012

During construction of the cable-stayed bridge, not only shape of deck and pylon but also cable forces are main factors for geometry control. Especially, geometry control of deck must be controlled for adjusting design value of vertical and lateral alignment as well as closing of key segment. Also, both the deck level error and cable force error occur necessarily during the construction stage in cable stayed bridge. The errors are caused by different of material properties and computer modeling, and construction mistake, and so on. These causes bring about that the forces of cable and the displacement of deck show different tendency from the theoretical values. Therefore, these errors must necessarily be adjusted and can be improved through adjustment of cable length. In this study, a new optimization tool is proposed to adjust the errors of the second Dolsan cable-stayed bridge.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.11
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• pp.937-946
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• 2014

This paper presents system identification of a single tilt wing UAV. A Modified Equation Error Method(MEEM) and Extended Kalman Filter(EKF) are used for the identification of a single tilt wing UAV system in frequency-domain and time-domain, respectively. Simulated flight data is obtained from CNUX-3's vertical mode linear simulation with realistic sensor noise. System identification performance is analyzed with respect to a variety of design parameters of the MEEM. Also, High accuracy Fourier Transform(HFT) is applied to enhance the performance of MEEM. The results of the MEEM is compared with those of the EKF. Design parameters of the MEEM and initial conditions of the EKF are decided from optimization.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.4
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• pp.433-442
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• 2010

In this paper, self-calibration algorithm based on covariance matrix is proposed for compensating amplitude/phase mismatch in multi-baseline interferometer direction finding system. The proposed method is a solution to nonlinear constrained minimization problem which dramatically calibrate mismatch error using space sector concept with cost function as defined in this paper. This method, however, has a drawback that requires an estimated initial angle to determine the proper space sector. It is well known that this type of drawback is common in nonlinear optimization problem. Superior calibration capabilities achieved with this approach are illustrated by simulation experiments in comparison with interferometer algorithm for a varitiety of amplitude/phase mismatch error. Furthermore, this approach has been found to provide an exceptional calibration capabilities even in case amplitude and phase mismatch are more than 30 dB and over $5^{\circ}$, respectively, with sector spacing of less than $50^{\circ}$.