• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.161-166
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• 2009

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a boiler unit, the effective operation is necessary. In this study, the supply water temperature algorithm of a condensing gas boiler was developed. This includes the setpoint algorithm and the control algorithm of the supply water temperature. The setpoint algorithm was developed by the fuzzy logic and the control algorithm was developed by the proportional integral algorithm. In order to analyse the performance of the supply water temperature algorithm, the dynamic model of a condensing gas boiler system was used. Simulation results showed that the supply water temperature algorithm developed for this study may be practically applied for the control of the condensing gas boiler.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.6
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• pp.441-448
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• 2011

The energy consumption of a condensing gas boiler may be greatly reduced by the effective operation of the unit. In this study, the supply water algorithm for a condensing gas boiler control was developed by using the fuzzy logic. This includes the supply water set temperature algorithm, and the control algorithms of a gas valve, a blower and a pump. For the set temperature algorithm, the outside air temperature and the return water temperature were used as input variables. The supply water temperature difference and its slope were used as input variables of the gas valve and blower control algorithm. And the supply water temperature and the return water temperature were used as input variables of the pump control algorithm. In order to analyse performances of these algorithms, the dynamic model of a condensing gas boiler was used. The initial start-up test, the supply water set temperature change test, the outside air temperature change test, and the return water temperature change test were performed. Simulation results showed that algorithms developed in this study may be practically applied for the effective control of a condensing gas boiler.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.1
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• pp.35-43
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• 2006

Concerns related to protecting, identifying, and isolating of subsystems of a water distribution network have led to the realization of the increased importance of valves in the system. The most important purpose of valves in water distribution systems is to isolate a subsystem due to breakage, maintenance activities, or contamination. A subsystem called segment is isolated by the closure of adjacent valves. Minimizing the pipe failure impact, an efficient algorithm is required to identify adjacent valves quickly. In this paper, an algorithm to identify adjacent valves to be closed to isolate a subsystem from the remainder of a network when a pipe failure is presented. The algorithm is operated on a matrix called the valve location matrix containing the information of valve locations. An application to an existing water distribution system demonstrates the developed algorithm efficiently locates the adjacent valves for the isolation of a broken pipe.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.173-180
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• 2012

This paper proposes a novel optimization algorithm inspired by water flowing and shaking behaviors in a vessel. Water drops in our algorithm flow to the gradient descent direction and are sometimes shaken for getting out of local optimum areas when most water drops fall in local optimum areas. These flowing and shaking operations allow our algorithm to quickly approach to the global optimum without staying in local optimum areas. We experimented our algorithm with four function optimization problems and compared its results with those of particle swarm optimization. Experimental results showed that our algorithm is superior to the particle swarm optimization algorithm in terms of the speed and success ratio of finding the global optimum.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.4
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• pp.453-460
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• 2004

The objective of this research is to develop the water quality management model to achieve the water quality goal and the minimization of the waste load abatement cost. Most of existing water quality management model can calculate BOD and DO. In addition to those variables, N and P are included in the management model of this study. With a genetic algorithm, calculation results from the mathematical water quality model can be used directly in this management model. Developed management model using genetic algorithm was applicated for the Youngsan River basin. To verify the management model, water quality and pollution source of the Youngsan River had been investigated. Treatment types and optimum treatment costs of the existing and planned WWTPs in the baisn were calculated from the model. The results of genetic algorithm indicate that Kwangju and Naju WWTP have to do the advanced treatment to achieve the water quality goal about BOD, DO and TP. Total annual treatment cost including the upgrade cost of existing WWTPs in the Youngsan River basin was about 50.3 billion Won.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.67-72
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• 2004

Many port states such as New Zealand, the USA, Australia and Canada have strict regulations to prevent ships which arrive in their port from discharging polluted ballast water which contain harmful aquatic organism and pathogens. They are notified that transfer of polluted ballast water can cause serious injury to public health and damage to property and environment. For this reason, they perceived that the ballast exchange in deep sea is the most effective method, together with submitting the ballast management plan which contains the effective exchange method, ballast system and safety consideration. In this study, we pursued both nautical engineering analysis and optimization of algorithm in order to generate the sequence of stability and rapidity. Heuristic Algorithm was chosen on the basis of optimality and applicability to a sequential exchange problem. We have built an optimized algorithm, for automatic exchange of ballast water, by redefining core elements of the $A^\ast$ algorithm, such as node, operator and evaluation function. Final version of the optimized algorithm has been applied to existing bulk carrier and the performance of the algorithm has been verified successfully.

• Journal of Ocean Engineering and Technology
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• v.18 no.4 s.59
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• pp.65-70
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• 2004

Many port states, such as New Zealand, U.S.A., Australia, and Canada, have strict regulations to prevent arriving ships from discharging polluted ballast water that contains harmful aquatic organisms and pathogens. They are notified that transfer of polluted ballast water can cause serious injury to public health and damage to property and environment. For this reason, ballast exchange in deep sea is perceived as the most effective method of emptying ballast water. The ballast management plan contains the effective exchange method, ballast system, and safety considerations. In this study, we pursued both nautical engineering analysis and optimization of the algorithm, in order to generate the sequence of stability and rapidity. A heuristic algorithm was chosen on the basis of optimality and applicability to a sequential exchange problem. We have built an optimized algorithm for the automatic exchange of ballast water, by redefining core elements of the A$\ast$ algorithm, such as node, operator, and evaluation function. The final version of the optimized algorithm has been applied to existing bulk carrier, and the performance of the algorithm has been successfully verified.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.203-206
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• 2001

Finding the optimal solution in the river water quality management system is very hard with the non-linearity of the water quality model. Many suggested methods for that using the linear programming, non-linear programming and dynamic programming, are failed to give an optimal solution of sufficient accuracy and satisfaction. We studied a method to find a solution optimizing the river water quality management in the aspect of the efficiency and the cost of the waste water treatment facilities satisfying the water Quality goals. In the suggested method, we use the QUAL2E water quality model and the genetic algorithm. A brief result of the project to optimize the water quality management in the Youngsan river is presented.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.307-312
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• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agency of Japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy-and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is as-sumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays vey similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.