• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.426-431
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• 1998

We propose a fuzzy rule based method for structure preserving dimensionality reduction. This method selects a small representative sample and applies Sammon's method to project it. The input data points are then augmented by the corresponding projected(output) data points. The augmented data set thus obtained is clustered with the fuzzy c-means(FCM) clustering algorithm. Each cluster is then translated into a fuzzy rule for projection. Our rule based system is computationally very efficient compared to Sammon's method and is quite effective to project new points, i.e., it has good predictability.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1171-1177
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• 2010

This paper presents a robust design procedure for minimizing warpage in plastic injection-molded products, where the Pick-the-Winner rule based on Taguchi's Orthogonal Array experiments and the Design Space Reduction Method are integrated for optimization. Two-step optimization approach is applied to reduce warpage in the part design stage and additionally to minimize the warpage in the process conditions design stage. Taguchi's S/N ratio is introduced as a design metric to evaluate robustness against process variations. The effectiveness of proposed optimization process is shown with an example of warpage minimization problem.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.483-490
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• 2002

This paper presents the results of a comparative study between FEM and LEM on slope stability analysis. For validation, factors of safety were compared between FEM and LEM. The results from the two methods were in good agreement suggesting that the FEM with the shear strength reduction method can be effectively used on slope stability analyses. A series of analysis were then performed using the FEM for various constitutive laws, slope angles, flow rules, and the finite element discretizations. Among the findings, the finite element method in conjunction with the shear strength reduction method can provide reasonable results in terms of factor of safety. Also revealed is that the results of FEM can be significantly affected by the way in which the type of constitutive law and flow rule are selected.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.8
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• pp.1164-1171
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• 2012

Recently, machine olfactory systems as an artificial substitute of the human olfactory system are being studied actively because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. Even though dimensionality reduction is the very important part, in pattern analysis, We handled effectively the dimensionality reduction by grouping the sensors of which the measured patterns are similar each other, where genetic algorithms were used for combination optimization. To identify the gas type, we constructed the hierarchical rule base with two frames by using rough set theory. The first frame is to accept measurement characteristics of each sensor and the other one is to reflect the identification patterns of each group. Thus, the proposed methods was able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.284-292
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• 2011

This paper presents a load-shedding scheme using the Talmud rule in islanded microgrid operation based on a multiagent system. Load shedding is an intentional load reduction to meet a power balance between supply and demand when supply shortages occur. The Talmud rule originating from the Talmud literature has been used in bankruptcy problems of finance, economics, and communications. This paper approaches the load-shedding problem as a bankruptcy problem. A load-shedding scheme is mathematically expressed based on the Talmud rule. For experiment of this approach, a multiagent system is constructed to operate test islanded microgrids autonomously. The suggested load-shedding scheme is tested on the test islanded microgrids based on the multiagent system. Results of the tests are discussed.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.521-524
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• 2002

This paper deals with the rule generation from data for control system and data mining using rough set. If the cores and reducts are searched for without consideration of the frequency of data belonging to the same equivalent class, the unnecessary attributes may not be discarded, and the resultant rules don't represent well the characteristics of the data. To improve this, we handle the inconsistent data with a probability measure defined by support, As a result the effect of uncertainty in knowledge reduction can be reduced to some extent. Also we construct the rule base in a hierarchical structure by applying core as the classification criteria at each level. If more than one core exist, the coverage degree is used to select an appropriate one among then to increase the classification rate. The proposed method gives more proper and effective rule base in compatibility and size. For some data mining example the simulations are performed to show the effectiveness of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.205-210
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• 2004

This paper deals with rule extraction from data using rough set theory. We construct the rule base in a hierarchical granulation structure by applying core as a classification criteria at each level. When more than one core exist, the coverage is used for the selection of an appropriate one among them to increase the classification rate and accuracy. In Addition, a probabilistic approach is suggested so that the partially useful information included in inconsistent data can be contributed to knowledge reduction in order to decrease the effect of the uncertainty or vagueness of data. As a result, the proposed method yields more proper and efficient rule base in compatability and size. The simulation result shows that it gives a good performance in spite of very simple rules and short conditionals.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.96.3-96
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• 2001

In this paper the self-organized and fuzzy inference used stochastic gradient ascent method is proposed. Fuzzy rule and fuzzy set increase as occasion demands autonomously according to the observation information. And two rules(or two fuzzy sets)becoming to be similar each other as progress of learning are unified. This unification causes the reduction of a number of parameters and learning time. Using fuzzy inference and making a rule with an appropriate state division, our proposed method makes it possible to construct a robust reinforcement learning system.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.846-858
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• 1997

Despite elaegant semantics and a lot of features, pure functional programming languages do not provide an affcient way of represnting states.Many researches have been done to resolve the problem, however, another problem arises that it is hard to implement becaese of the complex type system and redujction rule.Therefore, the scheme which simplifies the reduction rule and maintains states effciently is needed to have the implemen-taiton dffetive.This paper proposes st-calculus, the excution model of a functinal language with states and proves that the proposed model satistiies the church-Rosser theorem.It has simple reduction rules and the ability of rerpresenting states without, and the difficulties with implementation may be reduced by simplifving the reduction rules.