• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.203-207
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• 2018

This paper deals with the design and development of a lens system capable of imaging an infrared image of $3{\sim}5{\mu}m$ wavelength bands with a focal length of 24mm and good atmospheric transmission characteristics. The design used CodeV, a commercial design program, and the optimization is carried out with weighting to eliminate chromatic aberration, spherical aberration and distortion. The designed lens system consists of two lenses consisting of Si and Ge. Each lens has an aspherical surface on one side. And this optical system has the resolution of the characteristics that the MTF value is 0.40 at the line width of 29lp/mm and the MTF value is 0.25 at the line width of 20lp/mm. This optical system is considered to have the capability to be applied to the thermal imaging camera for MWIR using the $206{\times}156$ array infrared detector of $25{\mu}m$ pixels and the $320{\times}240$ array infrared detector of $17{\mu}m$ pixels.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.2 s.93
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• pp.120-127
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• 2005

The design method of the transversal filter using continuously cascaded directional couplers is presented. The coupler can be treated for a continuously varying nonuniform coupled transmission line. The design method is based on the optimum extraction of desired coupling factor by the control of null positions which are inherent to the coupling spectra pattern. In the optimization process, the improved Woodward-Lawson sampling method is applied to easily synthesize the distributed delay and weighting elements for transversal filter properties. For application, the microstrip transversal filter is fabricated and optimum dielectric overlay is introduced for the mode phase velocity compensation for non-TEM coupler nodes by using SDA(Spectral Domain Approach). Experiment results confirm the validity of the proposed method.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.358-366
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• 2011

Multi-criteria ABC inventory classification, which aims to classify inventory items by considering more than one criterion, is one of the most widely employed techniques for inventory control. The weighted linear optimization (WLO) model proposed by Ramanathan (2006) solves the problem of multi-criteria ABC inventory classification by generating a set of criterion weights for each inventory item and assigning a normalized score to the item for ABC analysis. However, the WLO model has some limitations. First, many inventory items can share the same optimal score, which can hinder a precise classification of inventory items. Second, the model allows too much flexibility in weighting multiple criteria; each item is allowed to choose its own weights so that it can maximize its score. As a result, if an item dominates the others in terms of a certain criterion, it may be classified into a higher class regardless of other criteria by assigning an overwhelming weight to the criterion. Consequently, an item with a high value in an unimportant criterion and low values in others may be inappropriately classified as class A, leading to an inaccurate classification of inventory items. To overcome these shortcomings, we extend the WLO model by using the cross-efficiency method in data envelopment analysis. We claim that the proposed model can provide a more reasonable and accurate classification of inventory items by mitigating the adverse effect of flexibility in the choice of weights and yielding a unique ordering of inventory items.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.2
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• pp.208-216
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• 2002

In this paper, the design method of a waveguide broad-wall longitudinal slot array monopulse antenna of X-type monopulse axes is presented, and the method is verified through manufacture and measurement. In the antenna design of this paper, the antenna size is small and the monopulse axes are X-type. Thus, the common continuous aperture distribution fuction is not suitable and the power balance among antenna quadrants should be considered. Also, since the waveguide height is reduced into 0.1 wavelength, the modelling of the slot characteristics is not simple. Thus, in this paper, the aperture distribution is optimized by using random number, and the balance among the quadrants is achieved by applying the quadrant weighting factor during the aperture optimization process. Also, the moment method procedure is accelerated by applying the interpolation technique to some part of the moment matrix, and the moment method procedure is added to the array synthesis program as a subroutine so that the slot characteristics can be calculated directly when it is required. Based on this method, a antenna of 28dBi is designed and manufactured. It is found that the antenna characteristics is similar to design data.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.555-565
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• 1999

The optimal identification algorithm of fuzzy systems is presented for rule-based fuzzy modeling of nonlinear complex systems. Nonlinear systems are expressed using the identification of structure such as input variables and fuzzy input subspaces, and parameters of a fuzzy model. In this paper, the rule-based fuzzy modeling implements system structure and parameter identification using the fuzzy inference methods and hybrid structure combined with two types of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. The proposed hybrid optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Here, a genetic algorithm is utilized for determining initial parameters of membership function of premise fuzzy rules, and the improved complex method which is a powerful auto-tuning algorithm is carried out to obtain fine parameters of membership function. Accordingly, in order to optimize fuzzy model, we use the optimal algorithm with a hybrid type for the identification of premise parameters and standard least square method for the identification of consequence parameters of a fuzzy model. Also, an aggregate performance index with weighting factor is proposed to achieve a balance between performance results of fuzzy model produced for the training and testing data. Two numerical examples are used to evaluate the performance of the proposed model.

• Journal of Environmental Impact Assessment
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• v.2 no.1
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• pp.39-55
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• 1993

The importance of urban and regional natural park increases because of the needs for preserving the natural resources and providing with natural recreation space in nature. This planning of natural park management should be established based on the research of the various natural resources in the park. But for the lack of effective data synthesizing methods and concepts, only some restricted factors for zoning plan are considered even though GIS computer system for large complex simulation is used. Therefore, in this study three ecological zoning models such as Basic Factor Model (BFM), Visual Landscape Model (VLM) and Comprehensive Ecological Model (CEM) are proposed and applied to Byounsan Peninsula Nature Park(BPNP) for comparison with the current natural park zoning. The BFM has three components -elevation, slope and vegetation. The VLM has applied with six components -elevation, slope, vegetation, road type, and the visual distance. Finally the CEM's modelling factors have included all of BFM, VLM components are added with the land use type, nature and historic resource factors. The zoning concept of BPNP was based on "Minimization" focused on the specific factors. But introduced modelling concept is "Optimization" based on the total ecological environment. So the result of the modelling has larger area for preservation and development zoning compared with the current zoning whose characteristics are ambiguous which allows the environmental destruction. The future study issues will be the determination of the weighting factor, component reconsideration based on the ground truth data and the agriculture residential area zoning.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.175-195
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• 2005

사례기반추론(case-based reasoning)은 사례간 유사도를 평가하여 유사한 이웃사례를 찾아내고, 이웃사례의 결과를 이용하여 새로운 사례에 대한 예측결과를 생성하는 전통적인 인공지능기법 중 하나다. 이러한 사례기반추론이 최근 적용이 쉽고 간단하다는 장점과 모형의 갱신이 실시간으로 이루어진다는 점 등으로 인해, 온라인 환경에서의 고객관계관리를 위한 도구로 학계와 실무에서 주목을 받고 있다 하지만, 전통적인 사례기반추론의 경우, 타 인공지능기법에 비해 정확도가 상대적으로 크게 떨어진다는 점이 종종 문제점으로 제기되어 왔다. 이에, 본 연구에서는 사례기반추론의 성과를 획기적으로 개선하기 위한 방법으로 유전자 알고리즘을 활용한 사례기반추론의 동시 최적화 모형을 제안하고자 한다. 본 연구가 제안하는 모형에서는 기존 연구에서 사례기반추론의 성과에 중대한 영향을 미치는 요소들로 제시된 바 있는 사례 특징변수의 상대적 가중치 선정(feature weighting)과 참조사례 선정(instance selection)을 유전자 알고리즘을 이용해 최적화함으로서, 사례간 유사도를 보다 정밀하게 도출하는 동시에 추론의 결과를 왜곡할 수 있는 오류사례의 영향을 최소화하고자 하였다. 제안모형의 유용성을 검증하기 위해, 본 연구에서는 국내 한 전문 인터넷 쇼핑몰의 구매예측모형 구축사례에 제안모형을 적용하여 그 성과를 살펴보았다. 그 결과, 제안모형이 지금까지 기존 연구에서 제안된 다른 사례기반추론 개선모형들은 물론, 로지스틱 회귀분석(LOGIT), 다중판별분석(MDA), 인공신경망(ANN), SVM 등 다른 인공지능 기법들에 비해서도 상대적으로 우수한 성과를 도출할 수 있음을 확인할 수 있었다.

• Journal of radiological science and technology
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• v.46 no.6
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• pp.509-517
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• 2023

This study analyzed imaging conditions and exposure index through clinical information collection and dose calculation programs in coronary angiography examinations. Through this, we aim to analyze the effective dose according to examination conditions and provide basic data for dose optimization. In this study, ALARA(As Low As Reasonably Achievable)-F(Fluoroscopy), a program for evaluating the radiation dose of patients and the collected clinical data, was used. First, analysis of imaging conditions and exposure index was performed based on the data of the dose report generated after coronary angiography. Second, after evaluating organ dose according to 9 imaging directions during coronary angiography, with the LAO fixed at 30°, dose evaluation was performed according to tube voltage, tube current, number of frames, focus-skin distance, and field size. Third, the effective dose for each organ was calculated according to the tissue weighting factors presented in ICRP(International Commission on Radiological Protection) recommendations. As a result, the average sum of air kerma during coronary angiography was evaluated as 234.0±112.1 mGy, the dose-area product was 25.9±13.0 Gy·cm², and the total fluoroscopy time was 2.5±2.0 min. Also, the organ dose tended to increase as the tube voltage, milliampere-second, number of frames, and irradiation range increased, whereas the organ dose decreased as the FSD increased. Therefore, medical radiation exposure to patients can be reduced by selecting the optimal tube voltage and field size during coronary angiography, maximizing the focal-skin distance, using the lowest tube current possible, and reducing the number of frames.

• Atmosphere
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• v.33 no.5
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• pp.519-530
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• 2023

Deep convection can make adverse effects on safe and efficient aviation operations by causing various weather hazards such as convectively-induced turbulence, icing, lightning, and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distribution of deep convective area near the airport and airspace. This study developed a new index, the Aviation Convective Index (ACI), for deep convection, using the operational global Unified Model of the Korea Meteorological Administration. The ACI was computed from combination of three different variables: 3-hour maximum of Convective Available Potential Energy, averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logic algorithm. In this algorithm, the individual membership function was newly developed following the cumulative distribution function for each variable in Korean Peninsula. This index was validated and optimized by using the 1-yr period of radar mosaic data. According to the Receiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimized ACI (ACI_YrOpt) based on the optimal weighting coefficients for 1-yr period shows a better skill than the no optimized one (ACI_NoOpt) with the uniform weights. In all forecast time from 6-hour to 48-hour, the AUC and TSS value of ACI_YrOpt were higher than those of ACI_NoOpt, showing the improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.