• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.746-752
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• 2006

This paper presents a scheme for the parameter estimation and stabilization of unstable systems, such as inverted pendulum systems. First a stable feedback loop is constructed for an inverted pendulum system and then its parameters are estimated based on input-output data, a real-coded genetic algorithm(RCGA) and the model adjustment technique. Then, a PI-type LQ control scheme is designed based on the estimated model. The performance of the proposed algorithm is demonstrated through a set of simulation and experiment.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.5
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• pp.137-144
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• 2016

This paper aims to ensure describe the a spring-back prevention technique for improving shape fixability by using an ultra-high strength steel sheet with 980 MPa to develop a lightweight seat rail parts. Ultra-high strength steel gives a potential for considerable weight reduction and a cost-effective way to produce energy efficient vehicles. The influence of a spring-back of seat rail parts on the shape fixability in forming processes was investigated to be solved by an adjustment of the appropriate tool design and process parameters. The computed results for improving shape fixability were in good agreement with the experimental results.

• Journal of the Korean Geophysical Society
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• v.9 no.1
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• pp.7-19
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• 2006

Laser scanning is a new technology for obtaining Digital Surface Models(DSM) of the earth surface.It is a fast method for sampling the earth surface with high density and high point accuracy. This paper is for buildings extraction from LiDAR points data. The core part of building construction is based on a parameters filter for distinguishing between terrain and non-terrain laser points. The 3D geometrical properties of the building facades are obtained based on plane fitting using least-squares adjustment. The reconstruction part of the procedure is based on the adjacency among the roof facades. Primitive extraction and facade intersections are used for building reconstruction. For overcome the difficulty just reconstruct of laser points data used with digital camera images. Also, 3D buildings of city area reconstructed using digital map. Finally, In this paper show 3D building Modeling using digital map and LiDAR data.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.321-327
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• 2013

Bayesian and empirical Bayesian methods have become quite popular in the theory and practice of statistics. However, the objective is to often produce an ensemble of parameter estimates as well as to produce the histogram of the estimates. For example, in insurance pricing, the accurate point estimates of risk for each group is necessary and also proper dispersion estimation should be considered. Well-known Bayes estimates (which is the posterior means under quadratic loss) are underdispersed as an estimate of the histogram of parameters. The adjustment of Bayes estimates to correct this problem is known as constrained Bayes estimators, which are matching the first two empirical moments. In this paper, we propose a way to apply the constrained Bayes estimators in insurance pricing, which is required to estimate accurately both location and dispersion. Also, the benefit of the constrained Bayes estimates will be discussed by analyzing real insurance accident data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.404-407
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• 2001

In this paper, hydro-turbine system is modelled. Real input and output signals are acquired from the hydro-turbine system and the parameters of the model are estimated using input-output data, the model adjustment technique and a genetic algorithm(GA). To verify feasibility of the propose(1 model, computer simulations using GA have been carried out. The results show excellent characteristics of the proposed modeling and identification of the hydro-turbine system.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.4
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• pp.404-413
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• 1997

Direct-drive robots are suitable to position and force control with high accuracy, but it is difficult to design a controller which gives satisfactory perfonnance because of the system's nonlinearity and link-interactions. This paper is concerned with the force control of direct-drive robots. The pro¬posed algorithm consists of feedback controllers and a neural network. Mter the completion of learning, the outputs of feedback controllers are nearly equal to zero, and the neural network con¬troller plays an important role in the control system. Therefore, the optimum adjustment of parameters of feedback controllers is unnecessary. In other words, the proposed algorithm does not need any knowledge of the controlled system in advance. The effectiveness of the proposed algo¬rithm is demonstrated by the experiment on the force control of a parallelogram link-type direct¬drive robot.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.3
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• pp.221-226
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• 2002

The SGR system which is the basis for setting Medicare conversion factor updates was enacted since 1992. The SGR sets a target rate of spending growth based on factors influencing medical costs. In our situation of Fee Contracts in Korea, there exist much conflicts with SGR. This article seeks how we can implement the SGR system successfully in Korea. The major points are estimation of real economic parameters, adjustment of prior estimation, consideration of important factors influencing medical costs.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1237-1253
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• 2018

Harmony search algorithm is an emerging meta-heuristic optimization algorithm, which is inspired by the music improvisation process and can solve different optimization problems. In order to further improve the performance of the algorithm, this paper proposes an improved harmony search algorithm. Key parameters including harmonic memory consideration (HMCR), pitch adjustment rate (PAR), and bandwidth (BW) are optimized as the number of iterations increases. Meanwhile, referring to the genetic algorithm, an improved method to generate a new crossover solutions rather than the traditional mechanism of improvisation. Four complex function optimization and pressure vessel optimization problems were simulated using the optimization algorithm of standard harmony search algorithm, improved harmony search algorithm and exploratory harmony search algorithm. The simulation results show that the algorithm improves the ability to find global search and evolutionary speed. Optimization effect simulation results are satisfactory.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.80-87
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• 1998

This paper presents and online scheme for fuzzy modelling of nonlinear systems, based on the model adjustment technique and the genetic algorithm technique. The fuzzy model is characterized by fuzzy "if-then" rules which represent locally linear input-output relations whose consequence parts are defined as subsystems of a nonlinear sysem. The discrete-time model for each subsystem is obtained to deal with initalization and unmeasurable signal problems in online estimation and the final output of the fuzzy model is computed from the outputs of the discrete-time models. Then, the parameters of both the premise and consequence parts of the fuzzy model are adjusted by a genetic algorithm. A set of simulation works is carried out to demonstrate the effectiveness of the proposed method.ed method.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.431-431
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• 2000

The modeling of 5-bar linkage robot manipulator dynamics by means of a mathematical and neural architecture is presented. Such a model is applicable to the design of a feedforward controller or adjustment of controller parameters. The inverse model consists of two parts: a mathematical part and a compensation part. In the mathematical part, the subsystems of a 5-bar linkage robot manipulator are constructed by applying Kawato's Feedback-Error-Learning method, and trained by given training data. In the compensation part, MLP backpropagation algorithm is used to compensate the unmodeled dynamics. The forward model is realized from the inverse model using the inverse of inertia matrix and the compensation torque is decoupled in the input torque of the forward model. This scheme can use tile mathematical knowledge of the robot manipulator and analogize the robot characteristics. It is shown that the model is reasonable to be used for design and initial gain tuning of a controller.