• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.246-246
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• 2023

Multi-purpose dams are operated accounting for both physical and socioeconomic factors. This study aims to evaluate the utility of a deep learning algorithm-based model for three multi-purpose dam operation (Seomjin River dam, Juam dam, and Juam Control dam) in Seomjin River. In this study, the Gated Recurrent Unit (GRU) algorithm is applied to predict hourly water level of the dam reservoirs over 2002-2021. The hyper-parameters are optimized by the Bayesian optimization algorithm to enhance the prediction skill of the GRU model. The GRU models are set by the following cases: single dam input - single dam output (S-S), multi-dam input - single dam output (M-S), and multi-dam input - multi-dam output (M-M). Results show that the S-S cases with the local dam information have the highest accuracy above 0.8 of NSE. Results from the M-S and M-M model cases confirm that upstream dam information can bring important information for downstream dam operation prediction. The S-S models are simulated with altered outflows (-40% to +40%) to generate the simulated water level of the dam reservoir as alternative dam operational scenarios. The alternative S-S model simulations show physically inconsistent results, indicating that our deep learning algorithm-based model is not explainable for multi-purpose dam operation patterns. To better understand this limitation, we further analyze the relationship between observed water level and outflow of each dam. Results show that complexity in outflow-water level relationship causes the limited predictability of the GRU algorithm-based model. This study highlights the importance of socioeconomic factors from hidden multi-purpose dam operation processes on not only physical processes-based modeling but also aritificial intelligence modeling.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.56-61
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• 2001

Activated sludge processes are broadly used in the biological wastewater treatment processes. The activated sludge processes are complex systems because of the many factors such as the variation of influent flowrate and ingredients, the complexity of biological reactions, and the various operation conditions. The main motivation o this research is to develop an intelligent control strategy for activated sludge process (ASP). ASP is a complex and nonlinear dynamic system owing to the characteristic of wastewater, the change in influent flowrate, weather conditions, and so on. The mathematical model of ASP also includes the uncertainty which is a ignored or unconsidered factor from process designers. The ASP model based on Matlabⓡ/Simulinkⓡ is developed in this paper. And the model performance is examined by IWA (International Water Association) and COST (European Cooperation in the filed of Scientific and Technical Research) data. The model tests derive steady-state results of 14 days. In this paper, fuzzy logic control approach is applied to handle DO concentrations. The fuzzy logic controller includes two inputs and one output to adjust air flowrate. The objective function for the optimization, in the implemented evolutionary strategy, is formed with focusing on improving the effluent quality and reducing the operating cost.

• 한국CDE학회논문집
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• 제3권4호
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• pp.283-292
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• 1998

The engineering process including design, analysis/evaluation and manufacturing activities is becoming one of the key issues to embody a concurrent engineering concept. This paper proposes a framework to integrated the complicated engineering design and manufacturing processes under the concurrent engineering environment. The framework offers the following facilities: (1) to represent the complicated engineering process (2) to coordinate design activities and execute the process in a distributed environment (3) to support a communication among the related engineers. The engineering processes is depicted using process flow graphs that consist in tasks and the corresponding input and output data. The engineering activities in the defined processes can be executed in a distributed environment through process controller of the framework. Engineers can communicate to suggest their opinions and to exchange product information in the framework. We have conformed the CORBA standard to integrate various distributed engineering the and communicate among them, and used a Java to support the platform independent environment on the Internet. Since the proposed framework an be a formal approach to integrate the engineering processes by providing formalism, parallelism, reusability, and flexibility, it can be effectively applied to embody the concurrent engineering concept in a distributed environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1993-1998
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• 2004

This paper proposes a new framework for control system design, called the data-based control approach or data space approach, in which the input and output data of a dynamical system is directly and solely used to analyze or design a control system without the employment of any mathematical models like transfer functions, state space equations, and kernel representations. Since, in this approach, most of the analysis and design processes are carried out in the domain of the data space, we introduce some notions of geometrical objects, e.g., the openloop and closed-loop data spaces, which serve as the system representations in the data space. In addition, we establish a relationship between the open-loop and closed-loop data spaces that the closed-loop data space is contained in the open-loop data space as one of its subspaces. By using this relationship, we can derive the data-based stabilization condition for a linear time-invariant discrete-time system, which leads to a linear matrix inequality with a rank constraint.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.395-400
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• 2004

In most physical processes, the transfer function includes time-delay, and in the general distributed control system using computer network, there exists inherent time-delay caused by the spatial separation between controllers and actuators. This work deals with the synthesis of a discrete-time controller for a nonlinear system and proposes a new effective method to compensate the influence of input time-delay. The controller is synthesized by using input/output linearization. Under the circumstance that input time-delay exists, the system response has more overshoot and tends to diverge. For these reasons, the controller has to produce future input value that will be needed for the system. In order to calculate the future input value, some predictors are adopted. Using the discretization via Euler's method, numerical simulations about the Van der Pol system are performed to evaluate the performance of the proposed method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.448-451
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• 2000

Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, the tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper could control the system containing non-linearity and uncertainty because it is designed based on the input-output data and experimental knowledge obtained by trials.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.588-590
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• 1999

In this paper the design method of a fuzzy logic controller with a genetic algorithm is proposed. Fuzzy logic controller is based on linguistic descriptions(in the form of fuzzy IF-THEN rules) from human experts. The auto-tuning method is presented to automatically improve the output performance of controller utilizing the genetic algorithm. The GA algorithm estimates automatically the optimal values of scaling factors and membership function parameters of fuzzy control rules. Controllers are applied to the processes with time-delay and the DC servo motor. Computer simulations are conducted at the step input and the output performances are evaluated in the ITAE.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.548-552
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• 2005

In most physical processes, the transfer function includes a time-delay, and in the general distributed control system using a computer network, an inherent time-delay exists due to the spatial separation between controllers and actuators. Under the circumstance where an input time-delay exits, the system response overshoots and tends to diverge. For this reasons described above, a controller design method is proposed for a discrete nonlinear system including input time-delay, which adopts the time-discretization using Taylor series. Controllers are synthesized using an input/output linearization method. Finally, several cases of the computer simulations were conducted, and the results validate the proposed methods.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2009년도 추계학술대회 논문집
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• pp.387-389
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• 2009

PV module is manufactured by several steps such as cell sort, tabbing & string, lay-up, lamination processes. In oder to manufacture PV module, solar cell must be placed in high temperature. Soldering Process in high temperature is important because it directly influences electric output performance changes of solar cell in solar cell module. We consider applying momentary high temperature, while soldering solar cell, and expect change electric characteristics of PV module. In this paper, we measure electric output characteristics of solar cells after those are applied with high temperature changes for two seconds. From these results, we confirm with application of high temperature, $I_{sc}$ increase and $V_{oc}$ slightly decreases.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.239-246
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• 2003

Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.