• Journal of Korean Society of Water and Wastewater
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• v.32 no.2
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• pp.107-113
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• 2018

Maintaining adequate residual chlorine concentration is an important criteria to provide secure drinking water. The chlorine decay can be influenced by unstable flow due to the transient event caused by operation of hydraulic devices in the pipeline system. In order to understand the relationship between the transient event and the chlorine decay, the probability density function based on the water demand curve of a hypothetical water distribution system was used. The irregular transient events and the same number of events with regular interval were assumed and the fate of chlorine decay was compared. The chlorine decay was modeled using a generic chlorine decay model with optimized parameters to minimize the root mean square error between the experimental chlorine concentration and the simulated chlorine concentration using genetic algorithm. As a result, the chlorine decay can be determined through the number of transients regardless of the occurrence intervals.

• Journal of Korean Society on Water Environment
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• v.37 no.5
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• pp.335-343
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• 2021

Water quality prediction is essential for the proper management of water supply systems. Increased suspended sediment concentration (SSC) has various effects on water supply systems such as increased treatment cost and consequently, there have been various efforts to develop a model for predicting SSC. However, SSC is affected by both the natural and anthropogenic environment, making it challenging to predict SSC. Recently, advanced machine learning models have increasingly been used for water quality prediction. This study developed an ensemble machine learning model to predict SSC using the XGBoost (XGB) algorithm. The observed discharge (Q) and SSC in two fields monitoring stations were used to develop the model. The input variables were clustered in two groups with low and high ranges of Q using the k-means clustering algorithm. Then each group of data was separately used to optimize XGB (Model 1). The model performance was compared with that of the XGB model using the entire data (Model 2). The models were evaluated by mean squared error-ob servation standard deviation ratio (RSR) and root mean squared error. The RSR were 0.51 and 0.57 in the two monitoring stations for Model 2, respectively, while the model performance improved to RSR 0.46 and 0.55, respectively, for Model 1.

• International Journal of Air-Conditioning and Refrigeration
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• v.12 no.3
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• pp.123-130
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• 2004

Control algorithms for an absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. Simulation results showed energy savings and the effective controls of an absorption air conditioning system.

• International Journal of Ocean System Engineering
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• v.3 no.1
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• pp.44-48
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• 2013

This paper describes the design and implementation of a practical underwater positioning system, which is applicable for shallow water depth conditions. In this paper, two strategies are used to enhance the navigation performance. First, a low-cost acoustic-ranging-based precise navigation solution for shallow water is designed. Then, the outlier rejection algorithm is introduced by designing a velocity gate. The acoustic-ranging-based navigation is implemented by modifying the long base line solution. To enhance the tracking precision, the outlier rejection algorithm is introduced. The performance of the developed approach is evaluated using experiments. The results demonstrate that precise shallow water depth navigation can be implemented using the suggested approaches.

• Journal of Korean Society on Water Environment
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• v.40 no.4
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• pp.168-178
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• 2024

Wastewater treatment plants are constantly exposed to influent wastewater that is constantly changing. This poses a major challenge to the operation of the plants. It is crucial to have a rapid and accurate measurement of the influent concentrations of wastewater in order to maintain and optimize treatment performance, as well as to develop energy-saving strategies. While laboratory measurements provide the highest accuracy in determining influent water quality, they are inevitably time-consuming procedures. In order to cope with the ongoing disturbances from wastewater influent, absorption-based optical measuring instruments have been developed. These instruments can detect the influent water quality in a short amount of time, improving their practicality and reliability. However, when these optical measuring instruments malfunction, the accuracy of the measured values decreases, leading to unreasonable operation of the treatment plant. This paper proposes a method for detecting anomalies in optical water quality measurement devices. The Harmony Search algorithm is used to validate the measured water quality values and detect abnormalities such as contamination or physical anomalies in the measurement apparatus. To assess the performance of the developed algorithm in detecting anomalies, validation was conducted by installing it in a field-scale wastewater treatment plant. The results consistently showed that the developed fault detection method for optical water quality measurements equipment provided acceptable results for normal, temporary abnormal, and long-term abnormal conditions.

• International Journal of Fluid Machinery and Systems
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• v.9 no.4
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• pp.287-299
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• 2016

In China, agricultural irrigation water often contains a lot of suspended sediment which may cause the nozzle wear. In this study, a new numerical simulation combing the Discrete Phase Model and a remeshing algorithm was conducted. The geometric boundary deformation caused by the erosion wear, was considered. The weight loss of the nozzle, the node displacement and the flow field were investigated and discussed. The timestep sensitivity analysis showed that the timestep is very critical in the erosion modeling due to the randomness and the discreteness of the erosion behavior. Based on the simulation results, the major deformation of the boundary wall due to the erosion was found at the corners between outlet portion and contraction portion. Based on this remeshing algorithm, the simulated erosion weight loss of the nozzle is 4.62% less compared with the case without boundary deformation. The boundary deformation changes the pressure and velocity distribution, and eventually changes the sediment distribution inside the nozzle. The average turbulence kinetic energy at the outlet orifice is found to decrease with the erosion time, which is believed to change the nozzle's spray performance eventually.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.150-150
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• 2022

This study investigates the roles of decomposition methods on high accuracy in daily rainfall prediction from light gradient boosting machine (LightGBM) algorithm. Here, empirical mode decomposition (EMD) and singular spectrum analysis (SSA) methods were considered to decompose and reconstruct input time series into trend terms, fluctuating terms, and noise components. The decomposed time series from EMD and SSA methods were used as input data for LightGBM algorithm in two hybrid models, including empirical mode-based light gradient boosting machine (EMDGBM) and singular spectrum analysis-based light gradient boosting machine (SSAGBM), respectively. A total of four parameters (i.e., temperature, humidity, wind speed, and rainfall) at a daily scale from 2003 to 2017 is used as input data for daily rainfall prediction. As results from statistical performance indicators, it indicates that the SSAGBM model shows a better performance than the EMDGBM model and the original LightGBM algorithm with no decomposition methods. It represents that the accuracy of LightGBM algorithm in rainfall prediction was improved with the SSA method when using multivariate dataset.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.314-321
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• 2019

The Self-Adaptive Vision Correction Algorithm (SAVCA) developed in this study was suggested for improving usability by modifying four parameters (Modulation Transfer Function Rate, Astigmatic Rate, Astigmatic Factor and Compression Factor) except for Division Rate 1 and Division Rate 2 among six parameters in Vision Correction Algorithm (VCA). For verification, SAVCA was applied to two-dimensional mathematical benchmark functions (Six hump camel back / Easton and fenton) and 30-dimensional mathematical benchmark functions (Schwefel / Hyper sphere). It showed superior performance to other algorithms (Harmony Search, Water Cycle Algorithm, VCA, Genetic Algorithms with Floating-point representation, Shuffled Complex Evolution algorithm and Modified Shuffled Complex Evolution). Finally, SAVCA showed the best results in the engineering problem (speed reducer design). SAVCA, which has not been subjected to complicated parameter adjustment procedures, will be applicable in various fields.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.518-521
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• 2007

To retrieve Sea Surface Temperature(SST) from NOAA-AVHRR imagery the spilt window atmospheric correction algorithm is generally used. Recently, there have been various new algorithms developed to process these data, namely the variable-coefficient split-window, the R54 transmittance-ratio method, fixed-coefficient nonlinear algorithm, dynamic water vapour (DWV) correction method, Dynamic Water Vapour and Temperature algorithm (DWVT). We used MCSST (Multi-Channel Sea surface temperature) and NLSST(Non linear sea surface temperature) algorithms in this study. The study area is around the Korea sea area (Yellow Sea). We compared and analyzed with various methods by applying each Ocean in-situ data and satellite data. The primary aim of study is to verify and optimize algorithms. Finally, this study proposes an optimized algorithm for SST retrieval.

• Journal of Korea Water Resources Association
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• v.51 no.4
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• pp.281-291
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• 2018

Harmony search algorithm (HSA), developed by Hydrosystem lab. in Korea University in 2001, was a new meta-heuristic optimization algorithm inspired by the iterative improvision process of Jazz music players where the best harmony is eventually produced. HSA is now one of the most well-known meta-heuristic algorithms (as proven by its cited number of the first published paper more than 3,600 times as of January 11th 2018 based on Google Scholar citation) and has been applied to diverse research domains such as not only water resources and civil engineering but also in medical science, business, and humanities. This paper is a review article written with the wish for wider application of HSA and other optimization algorithms, especially in the domain of water resources engineering. Therefore, this paper first briefly introduces the mechanism and operators of HSA and then reviews its application area and citation frequency per research domain. In addition, recent globalization of HSA will be investigated and summarized by checking the current status of related international conferences and on-going research projects. After reviewing previous domestic papers with optimization algorithms specifically published in the water resources domain, this paper is finalized by delivering some suggestions to encourage the application of optimization algorithms including HSA.