• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1159-1163
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• 2010

최근의 극심한 기상이변으로 인하여 발생되는 유출량의 예측에 관한 사항은 치수 이수는 물론 방재의 측면에서도 역시 매우 중요한 관심사로 부각되고 있다. 강우-유출 관계는 유역의 수많은 시 공간적 변수들에 의해 영향을 받기 때문에 매우 복잡하여 예측하기 힘든 요소이다. 과거에는 추계학적 예측모형이나 확정론적 예측모형 혹은 경험적 모형 등을 사용하여 유출량을 예측하였으나 최근에는 인공신경망과 퍼지모형 그리고 유전자 알고리즘과 같은 인공지능기반의 모형들이 많이 사용되고 있다. 하지만 유출량을 예측하고자 할 때 학습자료 및 검정자료로써 사용되는 유출량은 수위-유량 관계곡선식으로부터 구하는 경우가 대부분으로 이렇게 유도된 유출량의 경우 오차가 크기 때문에 그 신뢰성에 문제가 있을 것으로 판단된다. 따라서 본 논문에서는 선행우량 및 수위자료로부터 단시간 수위예측에 관해 연구하였다. 신경망은 과거자료의 입 출력 패턴에서 정보를 추출하여 지식으로 보유하고, 이를 근거로 새로운 상황에 대한 해답을 제시하도록 하는 인공지능분야의 학습기법으로 인간이 과거의 경험과 훈련으로 지식을 축적하듯이 시스템의 입 출력에 의하여 연결강도를 최적화함으로서 모형의 구조를 스스로 조직화하기 때문에 모형의 구조에 적합한 최적 매개변수를 추정할 수 있다. 따라서 정확한 예측이 어려운 하천수위를 과거의 자료로 부터 학습된 신경망의 수학적 알고리즘을 통해 유출량의 예측에 적용할 수 있을 것이다. 유전자 알고리즘은 적자생존의 생물학 원리에 바탕을 둔 최적화 기법중의 하나로 자연계의 생명체 중 환경에 잘 적응한 개체가 좀 더 많은 자손을 남길 수 있다는 자연선택 과정과 유전자의 변화를 통해서 좋은 방향으로 발전해 나간다는 자연 진화의 과정인 자연계의 유전자 메커니즘에 바탕을 둔 탐색 알고리즘이다. 즉, 자연계의 유전과 진화 메커니즘을 공학적으로 모델화함으로써 잠재적인 해의 후보들을 모아 군집을 형성한 뒤 서로간의 교배 혹은 변이를 통해서 최적 해를 찾는 계산 모델이다. 따라서 본 연구에서는 인공신경망의 가중치를 유전자 알고리즘에 의해 최적화시킨후 오류역전파알고리즘에 의해 신경망의 학습을 진행하는 모형으로 감천유역의 선산수위표지점의 수위를 1시간~6시간까지 예측하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2769-2774
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• 2013

The key of USN(Ubiquitous Sensor Network) technology is low power wireless communication technology and proper resource allocation technology for efficient routing. The distinguished resource allocation method is needed for efficient routing in sensor network. To solve this problems, we propose an algorithm that can be adopted in USN with making up for weak points of PQ and WRR in this paper. The proposed algorithm produces the control discipline by the fuzzy theory to dynamically assign the weight of WRR scheduler with checking the Queue status of each class in sensor network. From simulation results, the proposed algorithm improves the packet loss rate of the EF class traffic to 6.5% by comparison with WRR scheduling method and that of the AF4 class traffic to 45% by comparison with PQ scheduling method.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.105-120
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• 2007

The primary purpose of this study lies in developing an intelligence level measurement model which can be applied to information home appliances. To accomplish the study purpose, the literature on computer engineering and intelligence is comprehensively researched and critical elements necessary for measuring the intelligence of smart home appliances are extracted. Then an intelligence level measurement model is derived, and the model is validated by several academic and practical experts using Delphi technique. The measurement model developed in the study, on the one hand, can provide users with some objective standards to evaluate the intelligence level of smart home appliances. On the other hand, it can help home appliance product developers or related service providers decide the target intelligence level of the products or services more specifically. Consequently, the model can contribute to the revitalization of the smart home appliance industry as a whole.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.735-740
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• 2012

In this paper, we introduce design methodologies of polynomial radial basis function neural network classifier with the aid of Principal Component Analysis(PCA) and Linear Discriminant Analysis(LDA). By minimizing the information loss of given data, Feature data is obtained through preprocessing of PCA and LDA and then this data is used as input data of RBFNNs. The hidden layer of RBFNNs is built up by Fuzzy C-Mean(FCM) clustering algorithm instead of receptive fields and linear polynomial function is used as connection weights between hidden and output layer. In order to design optimized classifier, the structural and parametric values such as the number of eigenvectors of PCA and LDA, and fuzzification coefficient of FCM algorithm are optimized by Artificial Bee Colony(ABC) optimization algorithm. The proposed classifier is applied to some machine learning datasets and its result is compared with some other classifiers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1542-1550
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• 2019

Legacy studies for classifying arrhythmia have been studied to improve the accuracy of classification, Neural Network, Fuzzy, etc. Deep learning is most frequently used for arrhythmia classification using error backpropagation algorithm by solving the limit of hidden layer number, which is a problem of neural network. In order to apply a deep learning model to an ECG signal, it is necessary to select an optimal model and parameters. In this paper, we propose optimal parameter extraction method based on a deep learning. For this purpose, R-wave is detected in the ECG signal from which noise has been removed, QRS and RR interval segment is modelled. And then, the weights were learned by supervised learning method through deep learning and the model was evaluated by the verification data. The detection and classification rate of R wave and PVC is evaluated through MIT-BIH arrhythmia database. The performance results indicate the average of 99.77% in R wave detection and 97.84% in PVC classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.675-681
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated in various fields, interest in video processing, which is the basis for automation such as object recognition and object classification, is increasing. Various studies have been conducted on noise removal in the video processing process, which has a significant impact on image quality and system accuracy and reliability, but there is a problem that it is difficult to restore images for areas with high impulse noise density. In this paper proposes a filter algorithm based on partial mask and Lagrange interpolation to restore the damaged area of impulse noise in the image. In the proposed algorithm, the filtering process was switched by comparing the filtering mask with the noise estimate and the purge weight was calculated based on the low frequency component and the high frequency component of the image to restore the image.

• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.1
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• pp.81-91
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• 2010

IMO(International Maritime Organization) and the Shipping World rave complied with various kinds of international regulations for maritime safety and marine environmental protection, but the main reason of maritime accidents is that developing countries cannot implement maritime safety related regulations. Although Korea has been a member of the "A group" council of IMO, maritime technology transfer records of Korea are not good. To promote the project of official development assistance in Korea, it is required to select the technology which has a high degree of importance in the fields of maritime safety and has a high degree of demand on the transfer to developing countries, and to concentrate on the selected technology. So, it is necessary to draw valuation factors for maritime safety technology and to decide the priority in order among maritime safety technologies on the basis of valuation factors. Because the weights which show the degree of importance among valuation factors are different from factor to factor, interdependent relationship between factors should be considered on evaluation. In this study, the valuation factors were divided into three groups as the maturity of maritime safety technology, the promotion probability of projects and the degree of importance of technology, and the detailed factors of each group were drawn. A model which used Fuzzy AHP and limiting probability to consider the weights of importance and correlation among valuation factors was developed. To adopt this model, nine types of maritime safety technology in the field of maritime safety information were selected and points were scored for each technology through evaluation. In conclusion, first, ENC related technology was scored to be the highest as 0.0139. Second, the point of ship monitoring technology was scored as 0.0133. Last, oil spill response technology was scored as 0.0132.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.218-225
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• 2020

This study analyzed the priorities of the cross-compliance items of public-benefit direct payment using an Analytic Hierarchy Process and Fuzzy Decision Making Analysis. The valuation criteria are policy efficiency, farm acceptability, and feasibility, and the valuation targets are the basic and additional cross-compliance items. The survey was performed by targeting 50 experts from each class, and conducted for about a month starting from the beginning of July 2019. The results show that the weight of the valuation criteria is higher in the order of farm acceptability, feasibility, and policy efficiency. Compliance with PLS standards, compliance with disposal standards of waste vinyl and pesticides, soil testing, compliance with toxic substance standards, education, etc. are comparatively evaluated to be higher cross-compliance items in basic cross-compliance. Disposing of an abandoned well, jointly collecting and disposing of agricultural by-products, common area care and cleaning, maintenance of empty houses and poor facilities, growing green manure crops during the fallow period, etc. are comparatively evaluated to be higher cross-compliance items for the additional cross-compliance. The results of this study are expected to contribute to the government's policy related to the cross-compliance of public-benefit direct payment.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.97-109
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• 2017

Domestic vehicle penetration rate is growing at 3% per year, but consumers are increasingly buying used cars due to steady price hikes Nevertheless, the used car export market is expected to decline due to import regulations of major countries and the low grade environment of Used car export complex. Therefore, this study using Fuzzy-AHP was aimed to find operational factors of Used car logistics complex and establish a practical management plan of Used car logistic complex in incheon port. Fuzzy-AHP is the method that can be calculated weight of multi-level criteria and change linguistic ambiguity of human to Fuzzy Number. So it's able to propose the realistic decision making alternatives. As a result of the literacture reviews, present study focused on the analysis of the present situation of the logistics of the used car and the activation of the complex, suggested the activation plan and activation of the logistics complex. In the analysis of operational factors, logistic complex cost factors were found to be the most important factors by recording the weighted value of 0.306 in the above factors. The detailed factors were as follows: rent, accessibility, and logistics site size. It is necessary to compute competitive rent for the highly-advanced used car logistics complex, and to realize the rental support policy and to consider designating the free trade zone. In addition, it is necessary to expand the access infrastructure and secure the scale of the company for overseas buyers, and it is necessary to improve the overall government laws and introduce IT system for the future.

• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.113-133
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• 2013

Since 1995, Korean enterprises have been rapidly expanding their business, especially to Eastern European countries such as Poland, Slovakia, Czech Republic, Hungary and so on. After the establishment of Korea-EU FTA in 2011, close relationship between the two through economic cooperation has been maintained. To efficiently connect the seaport regions to inland factories located in Eastern European countries, researches on mode choice in the intermodal sector are needed to perform. However, there is a scant of research for mode choice factors on intermodal transportation service in Europe. Therefore, the aim of this research is to understand the current situation of intermodal transportation sector in Europe, identify key factors of mode choice, and weigh the importance among factors influencing intermodal selection in the perspective of Korean exporters or forwarders with overseas cargo to Europe. A survey and in-depth interviews to CEOs and executives who have more than 20 to 30 years of career in logistics sector were carried out from April 01 to May 01, 2013. Using the fuzzy theory as the methodology, 'Reliability of arrival time', 'Transit time', and 'Freight Rate' are equally ranked as the most important factor in the selection of intermodal transportation.