• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.701-706
• /
• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• The KSFM Journal of Fluid Machinery
• /
• v.7 no.2 s.23
• /
• pp.7-13
• /
• 2004

In an attempt to solve multiobjective optimization problems, weighted sum method is most widely used for the advantage that a designer can consider the relative significance of each object functions by weight values but it can be highly sensitive to weight vector and occasionally yield a deviated optimum from the relative weighting values designer designated because the multiobjective function has the form of simple sum of the product of the weighting values and the object functions in traditional approach. To search the design solution agree well to the designer's weighting values, we proposed new multiobjective function which was the functional of each normalized objective functions and considered to find the design solution comparing the distance between the characteristic line and the ideal optimum. In this study, proposed multiobjective function was applied to design high efficiency and low noise axial flow fan and the result shows this approach is effective for the case that the quality of the design can be highly affected by the designer's subjectiveness represented as weighting values in multiobjective design optimization process.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.10
• /
• pp.1425-1435
• /
• 2013

The useful method for determining parameters of weighting functions used to design the $H_{\infty}$ current controller for attenuating the current ripple due to saliencies which SPMSM(Surface Permanent Magnet Synchronous Motor) also incorporates is described. To analyze the effect, the current ripple due to the structural and the saturation saliencies, the SPMSM model with nonlinear inductance function depending on the two independent variables, rotor position and stator current is simulated. After analysis, parameters of the weighting functions for $H_{\infty}$ current controller is selected to satisfy the robust stability, robust performance and specific performance in time and frequency domain by using the PSO(Particle Swarm Optimization) algorithm in the linear SPMSM model. Especially, the robust performance is proved that the selected weighting functions play a role in reducing the current ripple caused by the saliencies of SPMSM at the desired frequency range by the simple experiment.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.42 no.4 s.304
• /
• pp.43-50
• /
• 2005

This paper proposes a new pattern recognition system combining the new adaptive feature weighting based on the genetic algorithm and the modified KNN(K Nearest-Neighbor) rules. The new feature weighting proposed herein avoids the overfitting and finds the Proper feature weighting value by determining the middle value of weights using GA. New GA operators are introduced to obtain the high performance of the system. Moreover, a class dependent feature weighting strategy is employed. Whilst the classical methods use the same feature space for all classes, the Proposed method uses a different feature space for each class. The KNN rule is modified to estimate the class of test pattern using adaptive feature space. Experiments were performed with the unconstrained handwritten numeral database of Concordia University in Canada to show the performance of the proposed method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.16 no.6
• /
• pp.40-50
• /
• 2002

In this paper, we present a GA(Genetic Algorithm) approach to select weighting matrices of an optimal LQ(Linear Quadratic) controller for SVC(Static VAR Compensator). A SVC, one of the FACTS(Flexible AC Transmission System), constructed by a FC(Fixed Capacitor) and a TCR(Thyristor Controlled Reactor), was designed and implemented to improve the damping of a synchronous generator, as well as to control the system voltage Also, a design of LQ controller depends on choosing weighting matrices. The selection of weighting matrices which is not a trivial solution is usually carried out by trial and error. We proposed an efficient method using GA of finding weighting matrices for optimal control law. Thus, we proved the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system by eigenvalues analysis and simulation.

• Journal of the Korean Society for information Management
• /
• v.25 no.1
• /
• pp.211-233
• /
• 2008

This study examines various weighting methods for improving the performance of automatic classification based on Rocchio algorithm on two collections(LISA, Reuters-21578). First, three factors for weighting are identified as document factor, document factor, category factor for each weighting schemes, the performance of each was investigated. Second, the performance of combined weighting methods between the single schemes were examined. As a result, for the single schemes based on each factor, category-factor-based schemes showed the best performance, document set-factor-based schemes the second, and document-factor-based schemes the worst. For the combined weighting schemes, the schemes(idf*cat) which combine document set factor with category factor show better performance than the combined schemes(tf*cat or ltf*cat) which combine document factor with category factor as well as the common schemes (tfidf or ltfidf) that combining document factor with document set factor. However, according to the results of comparing the single weighting schemes with combined weighting schemes in the view of the collections, while category-factor-based schemes(cat only) perform best on LISA, the combined schemes(idf*cat) which combine document set factor with category factor showed best performance on the Reuters-21578. Therefore for the practical application of the weighting methods, it needs careful consideration of the categories in a collection for automatic classification.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.15 no.1
• /
• pp.86-92
• /
• 2012

When missile is launched, a launcher needs to be leveled with accuracy to avoid the systems's instability. In general, a launcher is leveled by adjusting the stroke of leveling jacks; however, it is still challenge to control the leveling jacks fast and accurately. This paper thus proposed an innovative algorithm for compensating ground inclination of a missile launcher to expand operational field of a missile launcher. Using two inclinometers attached on a launcher, a base jack for leveling is selected and the mixed gradient where launcher stands on can be estimated. Due to the limited stroke, the launcher can compensate its ground inclination within maximum stroke margin. Then, the ground inclination of a launcher can be compensated by calculated angle using weighting factors. The effectiveness of proposed algorithm is proved with a prototype missile launcher.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.22-25
• /
• 2003

It is usually difficult for a single user to have all the essential knowledge on various Rapid Prototyping processes and techniques. It is therefore necessary to capture knowledge and experience of users of expert level into a decision-support system which provides quicker and more interactive way to select proper RP process and/or machine. rather than reading reports on benchmarking studies and comparing tables and graphs. In this paper two algorithms are presented, which may be used in such a decision-support system. together with its applications. The one is an extended PRES(Project Evaluation and Selection) algorithm which applies weighting factors of each attribute. The other is a LCE(Linear Confidence Equation) algorithm which is proposed to apply user's input requirements as well as weighting factors.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2232-2235
• /
• 2003

In speech communication systems where two different speech codecs are interoperated, transcoding algorithm is a good approach because of its low complexity and improved synthesized speech quality. This paper proposes an efficient method to further improve the performance of transcoding algorithms as well as to reduce the complexity. In the conventional transcoding algorithms. a post-filter and a perceptual weighting filter should be operated sequentially because both decoding and encoding processes are needed. This results in the redundancy of the processing in terms of complexity and perceptual quality. Using the fact that their filter structures are similar, we replaced the two filters with one. The proposed algorithm requires 72.8% lower complexity than the conventional transcoding algorithm when we compare only the complexity of the filtering processes. The results of both objective and subjective tests verify that the proposed algorithm has slightly better quality than the conventional one.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.3
• /
• pp.380-386
• /
• 2013

This paper represents an adaptive beamforming technique to suppress interference or jamming signals in wideband. In order to maintain low side lobe level(SLL) at an antenna element level, Taylor-weighting was used. Also, to make a nulling beam pattern toward jammer's directions in wideband, we used the modified Loaded Sample Matrix Inversion(LSMI) algorithm and Tapped Delay Line(TDL). To verify the proposed algorithm, we applied it to a rectangular array antenna. Finally, the results show beam pattern with low SLL and jammers suppression.