• Journal of the Korean Statistical Society
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• v.9 no.2
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• pp.135-144
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• 1980

A problem of choosing units for the series system and the 1-out-of-2 system from k available brands is treated from a decision-theoretic points of view. It is assumed that units from each brand have exponentially distributed life lengths, and that the loss functions are inversely proportional to the reliability of the system. For the series system the 'natural' rule is shown to be optimal. For the 1-out-of-2 system, the Bayes rule wrt the natural conjugate prior is derived and teh constants to implement the Bayes rule are given.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.27-32
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• 2003

The rule induction system generates a set of inductive rules, and the task of selecting an optimal rule subset is one of the important problem in the area of rule induction. This paper proposes a new learning method which combines rule induction system with the paradigm of genetic algorithm. This paper shows that genetic algorithm can be effectively applied to optimal rule selection problem. The proposed system was evaluated using a set of different machine learning data sets and, showed better performance in all cases than other traditional methods.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.488-492
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• 1991

This paper deals with modeling and scheduling for flexible manufacturing systems(FMS). In modeling extended Petri nets are used to describe various and complex properties. To resolve multiple conflict without predefined properties, such as part selection, machine selection, rule-based scheduling method is introduced. This structure have a capability of on-line scheduling with systematic modeling description.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.10
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• pp.483-488
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• 2016

In this paper, we propose a prototype-based classification learning by using the nearest-neighbor rule. The nearest-neighbor is applied to segment the class area of all the training data with hyperspheres, and a hypersphere must cover the data from the same class. The radius of a hypersphere is computed by the mid point of the two distances to the farthest same class point and the nearest other class point. And we transform the prototype selection problem into a set covering problem in order to determine the smallest set of prototypes that cover all the training data. The proposed prototype selection method is designed by a greedy algorithm and applicable to process a large-scale training set in parallel. The prediction rule is the nearest-neighbor rule and the new training data is the set of prototypes. In experiments, the generalization performance of the proposed method is superior to existing methods.

• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1763-1772
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• 1996

The conventional training set selection methods for the satellite image classification usually depend on the manual selection using data from the direct measurements of the ground or the ground map. However this task takes much time and cost, and some feature values vary in wide ranges even if they are in the same class. Such feature values can increase the robustness of the neural net but learning time becomes longer. In this paper,we propose anew training set selection algorithm using a rule-based method. By the technique proposed, the SPOT multispectral Imagery is classified in 3 bands, and the pixels which satisfy the rule are employed as the training sets for the neutralist classifier. The experimental results show faster initial convergence and almost the same or better classification accuracy. We also showed an improvement of the classification accuracy by using texture features and NDV1.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.261-264
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• 1992

In designing the fuzzy rule-based system, it has effected by the four significant factors such as the choice of membership function, scaling factor, the numbers of fuzzy control rule, the method of defuzzification. In this paper we design the fuzzy rule based system and evaluate by three factors, as followes reaching time, overshoot, and amplitude. And then we wiII show that the significant factors are the choice of scaling factor and the numbers of fuzzy control rule, and the system performance can be improved by the proper selection of the scaling factors.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.3
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• pp.58-64
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• 1999

Evolutionary programming is mainly characterized by two factors; one is the selection strategy and the other the mutation rule. In this paper, a new mutation rule that is the same form of well-known backpropagation learning rule of neural networks has been presented. The proposed mutation rule adapts the best individual's value as the target value at the generation. The temporal error improves the exploration through guiding the direction of evolution and the momentum speeds up convergence. The efficiency and robustness of the proposed algorithm have been verified through benchmark test functions.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.1
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• pp.41-50
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• 1989

This paper deals with the problem of space allocation of items within a warehouse. Recognizing the importance of weights associated with material handling, mathematical models are developed for two cases, out-and-back selection and storage retrieval interleaving. It is proved that the density order index rule we proposed generates an optimal solution for the first model. An example problem solved with the pairwise interchange method indicates that the rule is also fairly efficient for the second model. The proposed rule is compared with other assignment rules of warehouse space such as COI rule, space and popularity.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.453-463
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• 1997

Nonparametric kernel regression has recently gained widespread acceptance as an attractive method for the nonparametric estimation of the mean function from noisy regression data. Also, the practical implementation of kernel method is enhanced by the availability of reliable rule for automatic selection of the bandwidth. In this article, we propose a method for automatic selection of the bandwidth that minimizes the asymptotic mean square error. Then, the estimated bandwidth by the proposed method is compared with the theoretical optimal bandwidth and a bandwidth by plug-in method. Simulation study is performed and shows satisfactory behavior of the proposed method.

• The Korean Journal of Ecology
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• v.26 no.6
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• pp.341-347
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• 2003

Historical Documents on Proper Tree Selection System of Korea were collected in Japan and introduced in this review. Products of some pine species and fruit were used for laying a tribute to Kings in the Chosun dynasty. In this review, some case studies and implementation of proper tree selection system during the period of Japanese rule, the atlas of climatically favourable regions for the species of trees and bamboos in Korean peninsular, and the test results on regional afforestation, tree selection and proper tree selection of fast growing trees were introduced. Of these documents, especially, the atlas of climatically favourable regions of trees and bamboos growing in Korean peninsular is considered as a valuable document. It tis expected that these historical documents on proper tree selection system might be use as references for the researches on indigenous forest, forest resources development, afforestation of fire damaged areas, and the restoration project of North Korea by the time of reunification of Korea.