• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.333-336
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• 2002

In many cases, fuzzy modeling has a defect that the design procedure cannot be theoretically justified. To overcome this difficulty, we suggest a new design method for fuzzy model by combining genetic algorithm(GA) and mush set theory. GA, which has the advantages is optimization, and rule base. However, it is some what time consuming, so are introduce rough set theory to the rule reduction procedure. As a result, the decrease of learning time and the considerable rate of rule reduction is achieved without loss of useful information. The preposed algorithm is composed of three stages; First stage is quasi-optimization of fuzzy model using GA(coarse tuning). Next the obtained rule base is reduced by rough set concept(rule reduction). Finally we perform re-optimization of the membership functions by GA(fine tuning). To check the effectiveness of the suggested algorithm, examples for time series prediction are examined.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.6
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• pp.125-131
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• 2005

The purpose of this study is an optimization of gate valve made by forging method instead of welding method. In this study, we propose an optimal shape design to improve the mechanical efficiency of gate valve. In order to optimize more efficiently and reliably, the meta-modeling technique has been developed to solve such a complex problems combined with the DACE (Design and Analysis of Computer Experiments). The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Also, we prove reliability of the DACE model's application to gate valve by computer simulations using FEM(Finite Element Method).

• Journal of Power Electronics
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• v.5 no.2
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• pp.83-98
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• 2005

As wind turbine technology and control has advanced over the last decade, this has led to a high penetration of wind turbines into the power system. Whether it be for a large wind turbine or an offshore wind farm with hundreds of MW power capacity, the electrical system has become more and more important in controlling the interaction between the mechanical system of the wind turbine and the main power system. The presence of power electronics in wind turbines improves their controllability with respect not only to its mechanical loads but also to its power quality. This paper presents an overview of a developed simulation platform for the modeling, design and optimization of wind turbines. The ability to simulate the dynamic behavior of wind turbines and the wind turbine grid interaction using four simulation tools (Matlab, Saber, DIgSILENT and HAWC) is investigated, improved and extended.

• Computers and Concrete
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• v.19 no.5
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• pp.589-597
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• 2017

Strut-and-tie modeling method, which evolved on truss-model approach, has generally been preferred for the design of complex reinforced concrete structures and structural elements that have critical shear behavior. Some structural members having disturbed regions require exceptional detailing for all support and loading conditions, such as the beam-column connections, deep beams, short columns or corbels. Considering the general expectation of exhibiting brittle behavior, corbels are somewhat dissimilar to other shear critical structures. In this study, reinforcement layout of a corbel model was determined by the participation of structural optimization and strut-and-tie modeling methods, and an experimental comparison was performed against a conventionally designed model.

• Smart Structures and Systems
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• v.15 no.3
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• pp.609-625
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• 2015

Management of infrastructure stock is essential in sustainability of society, and its analysis and optimization are studied in the light of control system modeling in this paper. At the first part of the paper, cost of stock management is analyzed based on macroscopic statistics on infrastructure stock and economical growth. Stock management burden relative to economy is observed to become larger at low economic growth periods in developed economies. Then, control system modeling of stock management is introduced and by augmenting maintenance actions as control input, dynamic behavior of stock is simulated and compared with existing time history statistics. Assuming steady state conditions, applicability of the model to cross sectional data is also demonstrated. The proposed model is enhanced so that both preventive and corrective maintenance can be included as system inputs, i.e., feedforward and feedback control inputs. Optimal management strategy to achieve specified deteriorated stock level with minimal cost, expressed in terms of preventive and corrective maintenance actions, is derived based on estimated parameter values for corrosion of steel bridges. Relative cost effectiveness of preventive maintenance is shown when target deteriorated stock level is lower.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.537-547
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• 2001

The paper proposes the fuzzy logic global approximate optimization strategies in optimal sizing of automotive A-pillar trim with rib structures for occupant head protection. Two different strategies referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the inherent nonlinearity in analysis model should be accommodated over the entire design space and the training data is not sufficiently provided. The objective of structural design is to determine the dimensions of rib in A-pillar, minimizing the equivalent head injury criterion HIC(d). The paper describes the head-form modeling and head impact simulation using LS-DYNA3D, and the approximation procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and subsequently presents their generalization capabilities in terms of number of fuzzy rules and training data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.139-142
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• 2001

As microeletronics technology continues to progress, there is also a continuous demand on highly integration and miniaturization of systems. For example, it is desirable to package several integrated circuits together in multilayer structure, such as multichip modules, to achieve higher levels of compactness and higher performance. Passive components (i.e., capacitors, resistors, and inductors) are very important for many MCM applications. In addition, the low-temperature co-fired ceramic (LTCC) process has considerable potential for embedding passive components in a small area at a low cost. In this paper, we investigate a method of statistically modeling integrated passive devices from just a small number of test structures. A set of LTCC inductors is fabricated and their scattering parameters (5-parameters) are measured for a range of frequencies from 50MHz to 5GHz. An accurate model for each test structure is obtained by using a building block based modeling methodology and circuit parameter optimization using the HSPICE circuit simulator.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.4
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• pp.14-21
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• 2012

This paper study a method of modeling and simulation of LED driver circuit for a design optimization. Simplified LED modeling is introduced and a driver IC, HV9910, is modeled by implementing the major function blocks. Circuit of buck type converter is constructed for simulation. Simulation includes not only the internal function of IC but also the various performance results such as LED array current control and dimming. Experiment results are also shown to prove the verification of its usage. This results show that the simulation approach is valid for a circuit optimization and a reduction of development time.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.4
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• pp.344-348
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• 2002

As microelectronics technology continues to progress, there is also a continuous demand on highly integration and miniaturization of systems. For example, it is desirable to package several integrated circuits together in multilayer structure, such as multichip modules, to achieve higher levels of compactness and higher performance. Passive components (i.e., capacitors, resistors, and inductors) are very important fort many MCM applications. In addition, the low-temperature co-fired ceramic (LTCC) process has considerable potential for embedding passive components in a small area at a low cost. In this paper, we investigate a method of statistically modeling integrated passive devices from just a small number of test structures. A set of LTCC inductors is fabricated and their scattering parameters (s-parameters) are measured for a range of frequencies from 50MHz to 5GHz. An accurate model for each test structure is obtained by using a building block based modeling methodology and circuit parameter optimization using the HSPICE circuit simulator.