• Industrial Engineering and Management Systems
• /
• v.15 no.3
• /
• pp.231-238
• /
• 2016

Traditional acceptance sampling plans have focused on the proportion of nonconforming items as an attribute criterion for quality. In today's modern quality management under high quality production environments, the reduction of the deviation from a target value in a quality characteristic has become the most important purpose. In consequence, various inspection plans for the purpose of reducing the deviation from the target value in the quality characteristic have been investigated. In this case, a concept of the quality loss evaluated by the deviation from the target value has been accepted as the variable evaluation criterion of quality. Further, some quality measures based on the quality loss have been devised; e.g. the process loss and the process capability index. Then, as one of inspection plans based on the quality loss, the rigorous design procedure for the variable sampling plan having desired operating characteristics (VS-OC plan) indexed by the quality loss has been proposed by Yen and Chang in 2009. By the way, since the estimator of the quality loss obeys the non-central chi-square distribution, the rigorous design procedure for the VS-OC plan indexed by the quality loss is complicated. In particular, the rigorous design procedure for the VS-OC plan requires a large number of the repetitive and complicated numerical calculation about the non-central chi-square distribution. On the other hand, an approximate design procedure for the VS-OC plan has been proposed before the proposal of the above rigorous design procedure. The approximate design procedure for the VS-OC plan has been constructed by combining Patnaik approximation relating the non-central chi-square distribution to the central chi-square distribution and Wilson-Hilferty approximation relating the central chi-square distribution to the standard normal distribution. Then, the approximate design procedure has been devised as a convenient procedure without complicated and repetitive numerical calculations. In this study, through some comparisons between the rigorous and approximate design procedures, the applicability of the approximate design procedure has been confirmed.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.1087-1094
• /
• 2005

e-insensitive support vector regression(e-SVR) is capable of providing more complete description of the linear and nonlinear relationships among random variables. In this paper we propose an iterative reweighted least squares(IRWLS) procedure to solve the quadratic problem of e-SVR with a modified loss function. Furthermore, we introduce the generalized approximate cross validation function to select the hyperparameters which affect the performance of e-SVR. Experimental results are then presented which illustrate the performance of the IRWLS procedure for e-SVR.

• Korean Management Science Review
• /
• v.17 no.2
• /
• pp.1-12
• /
• 2000

In this study, we deals with the implementation of an optimal basis identification procedure for interior point methods. Our implementation is based on Megiddo’s strongly polynomial algorithm applied to Andersen and Ye’s approximate LP construction. Several techniques are explained such as the use of effective indicator for obtaining optimal partition when constructing the approximate LP, the efficient implementation of the problem reduction technique proposed by Andersen, the crashing procedure needed for fast dual phase of Megiddo’s algorithm and the construction of the stable initial basis. By experimental comparison, we show that our implementation is superior to the crossover scheme implementation.

• Journal of the Korean Data and Information Science Society
• /
• v.17 no.3
• /
• pp.905-912
• /
• 2006

Support vector classification(SVC) provides more complete description of the linear and nonlinear relationships between input vectors and classifiers. In this paper we propose to solve the optimization problem of SVC with a modified hinge loss function, which enables to use an iterative reweighted least squares(IRWLS) procedure. We also introduce the approximate cross validation function to select the hyperparameters which affect the performance of SVC. Experimental results are then presented which illustrate the performance of the proposed procedure for classification.

• Proceedings of the KIEE Conference
• /
• 1999.11c
• /
• pp.472-474
• /
• 1999

The design procedure originally proposed by Manabe is involved, because experiences and manual skills are necessary, especially, in the case of designing low fixed-order controllers for high-order plants, and the concept of manual skills are not clearly defined. So we propose a concept and a design procedure of Approximate Pole Placement that substitute for the manual skills. And the validity of the procedure is shown by example problems. Moreover, we also propose a procedure of adding the role of improving transient response performance to the feedforward compensator that previously has only the role of tracking in steady-state the validity of the procedure is also shown by example problems.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.1045-1052
• /
• 2005

This paper deals with the estimations of kernel ridge regression when the responses are subject to randomly right censoring. The weighted data are formed by redistributing the weights of the censored data to the uncensored data. Then kernel ridge regression can be taken up with the weighted data. The hyperparameters of model which affect the performance of the proposed procedure are selected by a generalized approximate cross validation(GACV) function. Experimental results are then presented which indicate the performance of the proposed procedure.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.356-356
• /
• 2000

For irregular nonlinear systems, switching controlk form is proposed recently. This control law is designed to overcome the singularities through the scheme that switches between an approximate tracking law close to the singularities, and an exact tracking law away from the singularities. But, that form has problems which may break the system's stability through unstable control input value at switching procedure. In this paper, We propose new switching control law which supervises approximate tracking control law and exact tracking control law by fuzzy rules to overcome unstability problem in switching procedure.

• Journal of Korean Society for Quality Management
• /
• v.10 no.1
• /
• pp.7-12
• /
• 1982

Arvesen (1969) has shown a procedure which produces an approximate confidence interval for a variance component in unbalanced one-way classification model. In this paper, his work is extended to the case when the model of interest is unbalanced two-way classification. Following the procedure described in this paper, approximate confidence intervals are computed by a Monte Carlo simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.1
• /
• pp.19-30
• /
• 2013

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

• Industrial Engineering and Management Systems
• /
• v.4 no.2
• /
• pp.123-128
• /
• 2005

The author derives a general explicit formula and presents an heuristic algorithm for solving Baker’s model. The examples show that this new approximate solution procedure for determining near optimum inspection intervals is more accurate than the ones suggested by Chung (1993) and Vaurio (1994), and is more efficient computationally than the one suggested by Hariga (1996). The construction and solution of the simplest profit model for an exponential failure distribution were presented in Baker (1990), and approximate analytical results were obtained by Chung (1993) and Vaurio (1994). The author will therefore mainly devote the following discussion to the problem of further approximating optimum inspection intervals.