• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.196-203
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• 2010

Make-to-forecast production is a way to realize high customization and fast responsiveness. This study firstly investigates the effect of introducing a common component in a make-to-forecast production environment. The common component can eliminate a modification step, which is a major cost component in make-to-forecast production. It is illustrated, however, that introducing a versatile component that merely covers several variants is unattractive, and thus adding values to the common component is inevitable in this environment. Secondly, an order-matching rule under the condition that two partially overlapped delivery lead time intervals exist is proposed. The rule considers the effect of matching orders to units that can cover both intervals. An alternative re-matching rule is also developed and examined. Numerical experiments clarify that the proposed rule generally realizes higher contribution ratio and lower percentages of orphans and rejected orders. The proposed re-matching rule increases the average contribution ratio at the expense of increased orphans and order rejections.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.249-255
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• 2000

HRIV(Hybrid Rule-Interval Variation) method is presented to stabilize a class of nonlinear systems, where SMC(Sliding Mode Control) and ADC (ADaptive Control) schemes are incorporated to overcome the unstable characteristics of a conventional FLC(Fuzzy Logic Control). HRIV method consists of two modes: I-mode (Integral Sliding Mode PLC) and R-mode(RIV method). In I-mode, SMC is used to compensate for MAE(Minimum Approximation Error) caused by the heuristic characteristics of FLC. In R-mode, RIV method reduces interval lengths of rules as states converge to an equilibrium point, which makes the defined Lyapunov function candidate negative semi-definite without considering MAE, and the new uncertain parameters generated in R-mode are compensated by SMC. In RIV method, the overcontraction problem that the states are out of a rule-table can happen by the excessive reduction of rule intervals, which is solved with a dynamic modification of rule-intervals and a transition to I-mode. Especially, HRIV method has advantages to use the analytic upper bound of MAE and to reduce Its effect in the control input, compared with the previous researches. Finally, the proposed method is applied to stabilize a simple nonlinear system and a modified inverted pendulum system in simulation experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1274-1276
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• 1993

We have designed a multiple-valued fuzzy Approximate Analogical-Reseaning system (AARS). The system uses a similarity measure of fuzzy sets and a threshold of similarity ST to determine whether a rule should be fired, with a Modification Function inferred from the Similarity Measure to deduce a consequent. Multiple-valued basic fuzzy blocks are used to construct the system. A description of the system is presented to illustrate the operation of the schema. The results of simulations show that the system can perform about 3.5 x 106 inferences per second. Finally, we compare the system with Yamakawa's chip which is based on the Compositional Rule of Inference (CRI) with Mamdani's implication.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.579-583
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• 1991

A fuzzy logic controller with rule modification capability is proposed to overcome the difficulty of obtaining control rules from the human operators. This new SOC algorithm modifies control rules by a fuzzy inference machine utilizing data base. Computer simulation results show good performances on both a linear system and a nonlinear system.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.1
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• pp.48-59
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• 2003

The purposes of this research lie in developing dress shirts pattern targeting adult males between 25-34 years of age and presenting the rules of grading according to the real circumstances of dress shirts industry. The findings of this research are as follows: 1. The surveyed companies kept different size systems ranged from 5 to 18. They kept different size systems each other, and the pattern making was conducted by modification of the collar size, chest size, etc of the pattern developed through each company's know-how. All the surveyed companies were using point method of grading. 2. The method of the research pattern was to adopt N/6+1(cm) for the width of the back of the neck. N/6 for the front neck, N/6+2 for the depth of the front neck, B/6+7 for the shoulder width, B/6+5.5 for the breast width, B/4+5 for the whole width (back), B/4+4 for the whole width (front), B/4+3.5 for the depth, AH/2+0.5 for the back arm hole, AH2+1 for the front arm hole. 3. The grading rule was made after classifying the sizes into 14 centered on the standard size 40. Through the wearing test of research grading rule, 1 found the suitability of grading size 36 and 43 satisfiable.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.633-642
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• 2004

This study tries to generalize the stream network by constructing rule-based modelling. A study on the map generalization tends to be concentrated on development of algorithms for modification of linear features and evaluations to the limited cartographic elements. Rule-based modelling can help to improve previous algorithms by application of generalization process with the results that analyzing mapping principles and spatial distribution patterns of geographical phenomena. Rule-based modelling can be applied to generalize various cartographic elements, and make an effective on multi-scaling mapping in the digital environments. In this research, nile-based modelling for stream network is composed of generalization rule, algorithm for centerline extraction and linear features. Before generalization, drainage pattern was analyzed by the connectivity with lake to minimize logical errors. As a result, 17 streams with centerline are extracted from 108 double-lined streams. Total length of stream networks is reduced as 17% in 1:25,000 scale, and as 29% in 1:50,000. Simoo algorithm, which is developed to generalize linear features, is compared to Douglas-Peucker(D-P) algorithm. D-P made linear features rough due to the increase of data point distance and widening of external angle. But in Simoo, linear features are smoothed with the decrease of scale.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.155-159
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• 2003

In order to compansate the problem of fragmentating data and disdaining small group of data in decision trees, a descriptive rule set discovery method is suggested. The principle of association rule finding algorithm is presented and a modified association nile finding algorithm for efficiency is applied to target database which has condition and decision attributes to see the effect of modification.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.2
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• pp.117-127
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• 2000

In this paper, we propose a new convex combination weight rule for the cross decomposition method which is known to be one of the most reliable and promising strategies for the large scale optimization problems. It is called generalized cross decomposition, a modification of linear mean value cross decomposition for specially structured linear programming problems. This scheme puts more weights on the recent subproblem solutions other than the average. With this strategy, we are having more room for selecting convex combination weights depending on the problem structure and the convergence behavior, and then, we may choose a rule for either faster convergence for getting quick bounds or more accurate solution. Also, we can improve the slow end-tail behavior by using some combined rules. Also, we provide some computational test results that show the superiority of this strategy to the mean value cross decomposition in computational time and the quality of bounds.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.587-592
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• 2004

Context-aware computing systems require real-time context reasoning process for context awareness. Context reasoning can be done by comparing input information from sensors with knowledge-base within system. This method is identical with it of rule-based systems. In this paper, we propose hardware rule-based system architecture which can process context reasoning in real-time. Compared to previous architecture, hardware rule-based system architecture can reduce the number of constraints on rule representations and combinations of condition terms in rules. The modified content addressable memory, crossbar switch network and pre-processing module are used for reducing constraints. Using SystemC for description can provide easy modification of system configuration later.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.25-33
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• 2012

In this paper, we propose a rule-based model to correct errors in a speech recognition result in the mobile device environment. The proposed model considers the mobile device environment with limited resources such as processing time and memory, as follows. In order to minimize the error correction processing time, the proposed model removes some processing steps such as morphological analysis and the composition and decomposition of syllable. Also, the proposed model utilizes the longest match rule selection method to generate one error correction candidate per point, assumed that an error occurs. For the purpose of deploying memory resource, the proposed model uses neither the Eojeol dictionary nor the morphological analyzer, and stores a combined rule list without any classification. Considering the modification and maintenance of the proposed model, the error correction rules are automatically extracted from a training corpus. Experimental results show that the proposed model improves 5.27% on the precision and 5.60% on the recall based on Eojoel unit for the speech recognition result.