• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.141.4-141
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• 2001

In this paper the Local Weighted Regression LWR technique is applied to the estimation of aircrcraft parameters. The method consists In improving the Local Weighted Regression LWR technique by adding a data Retention-and-Deletion RD strategy. The improvement comes with reduced computational effort since the two techniques can share their main computational procedures. The purpose of the study was to establish if the proposed algorithm could provide fast and reliable real-time estimations, with accuracy comparable to other well-known off-line identification schemes. The algorithm was tested using specific parameter estimation maneuvers and flight data of the NASA F/A-18 HARV. The results were compared with both the estimation obtained from ...

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.479-481
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• 1998

Noise가 있는 data에서 shape나 parameter를 찾았을 때 일반적으로 Hough transform이나 regression을 적용한다. Hough transform은 parameter space의 차수가 커지면 memory 문제가 존재하며, regression 모델은 한 개의 변수를 다른 변수의 함수로 가정하여 error를 최소화하여 데이터중 1 set의 parameter만 존재한다는 가정을 하여야 하는 문제점이 있다. 본 논문에서는 이러한 두 방법의 단점들을 보완하며, Fuzzy개념을 도입한 data fitting 방법을 제안하였다. 이 문제는 genetic algorithm을 도입하여 data를 Fuzzy membership을 갖는 것으로 가정한 최적화 문제로 해결하였다. 직선과 평면에 대한 실험 결과를 보인다.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.85-93
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• 1995

Hannan and Rissanen proposed an innovation regression method of ARMA modeling, which is composed of three stages. Its second-stage is to choose orders of the ARMA model using the BIC, which needs a lot of calculation to estimate several regression models. We are going to present a simple and efficient algorithm for the second stage using a special property of triangular Toeplitz matrices.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.2
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• pp.39-43
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• 1999

We consider generalized exponential regression model with randomly censored data and propose a modified Fisher scoring method which estimates the model parameters. For this, the likelihood equations are derived and then the estimating algorithm is developed. We illustrate the proposed method using a real data.

• Journal of the Korean Statistical Society
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• v.21 no.2
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• pp.201-207
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• 1992

The algorithm for obtaining the isotonic regression in simple tree order, the most basic and simplest model next to the simple order, is considered. We propose to call it "Pool-the-Maximum-Violators" algorithm (PMVA) in conjunction with the "Pool-Adjacent-Violators" algorithm (PAVA) in the simple order. The dual problem of obtaining the isotonic regression in simple tree order is our main concern. An intuitively appealing relation between the primal and the dual problems is demonstrated. The interesting difference is that in simple order the required number of pooling is at least the number of initial violating pairs and any path leads to the solution, whereas in the simple tree order it is at most the number of initial violators and there is only one advisable path although there may be some others leading to the same solution.o the same solution.

• Journal of Welding and Joining
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• v.24 no.5
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• pp.67-73
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• 2006

Laser welding is suitable for welding to the aluminum alloy sheet. In order to apply the aluminum laser welding to production line, parameters should be optimized. In this study, the optimal welding condition was searched through the genetic algorithm in laser welding of AA5182 sheet with AA5356 filler wire. Second-order polynomial regression model to estimate the tensile strength model was developed using the laser power, welding speed and wire feed rate. Fitness function for showing the performance index was defined using the tensile strength, wire feed rate and welding speed which represent the weldability, product cost and productivity, respectively. The genetic algorithm searched the optimal welding condition that the wire feed rate was 2.7 m/min, the laser power was 4 kW and the welding speed was 7.95 m/min. At this welding condition, fitness function value was 137.1 and the estimated tensile strength was 282.2 $N/mm^2$.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.2
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• pp.152-158
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• 2003

A machine-vision guided inspection system with go-no gauges for inspecting eggcrate assemblies in steam generators is considered. To locate the gauge at the right place, periodic corrective actions for its position and traveling direction are required. We present a machine vision algorithm for determining inserting position and traveling direction of the go-no gauge. The overall procedure of the algorithm is composed of camera calibration, eggcrate image preprocessing, grid-height adjustment, intersection point estimation between two intersecting grids, and adjustment of position and traveling direction of the gauge. The intersection point estimation is performed by using linear regression with a constraint. A test with a real eggcrate specimen shows the feasibility of the algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.93-101
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• 2007

To jointly optimize the spatial registration and the exposure compensation, an iterative registration algorithm, the Lucas-Kanade algorithm, is combined with an exposure compensation algorithm, which is based on the histogram transformation function. Based on a simple regression model, a nonparametric estimator, the empirical conditional mean, and its polynomial fitting are used as histogram transformation functions for the exposure compensation. Since the proposed algorithm is composed of separable optimization phases, the proposed algorithm is more advantageous than the joint approaches of Mann and Candocia in the aspect of implementation flexibility. The proposed algorithm performs a better registration for real images than the case of registration that does not consider the exposure difference.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.161-165
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• 1992

The important properties of industrial scale or weighing machine operated in production lines are quickness and precision. This paper presents an algorithm which meets the importance. The algorithm of Recursive Least Squares Regression is described for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions have been extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted realtime signal processing.

• Communications for Statistical Applications and Methods
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• v.14 no.1
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• pp.215-227
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• 2007

Variable selection algorithm for Sliced Inverse Regression using penalty function is proposed. We noted SIR models can be expressed as generalized eigenvalue decompositions and incorporated penalty functions on them. We found from small simulation that the HARD penalty function seems to be the best in preserving original directions compared with other well-known penalty functions. Also it turned out to be effective in forcing coefficient estimates zero for irrelevant predictors in regression analysis. Results from illustrative examples of simulated and real data sets will be provided.