• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1401-1408
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• 2000

Critical prediction models that determine whether a design entity is fault-prone or non fault-prone play an important role in reducing system development cost because the problems in early phases largely affected the quality of the late products. Real-time systems such as telecommunication system are so large that criticality prediction is more important in real-time system design. The current models are based on the technique such as discriminant analysis, neural net and classification trees. These models have some problems with analyzing cause of the prediction results and low extendability. In this paper, we propose a criticality prediction model using fuzzy rulebase constructed by genetic algorithm. This model makes it easy to analyze the cause of the result and also provides high extendability, high applicability, and no limit on the number of rules to be found.

• Korean Journal of Ecology and Environment
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• v.41 no.spc
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• pp.11-20
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• 2008

In this study, we applied a Particle Swarm Optimization (PSO) algorithm to predict the changes of chlorophyll-${\alpha}$ related to environmental factors in agricultural reservoirs in Korean national scale. Data were obtained from water quality monitoring networks of reservoirs operated by the Ministry of Agriculture and Forestry and the Ministry of Environment of Korea. From the database of the monitoring networks, 290 reservoirs were chosen with variables such as chlorophyll-${\alpha}$ and 13 environmental factors (COD, TN, TP, Altitude, Bank height, etc.) measured in 2002. Based on Carlson's trophic status index, reservoirs were divided into five groups, and most agricultural reservoirs $(TSI_{CHL}\;64.1%,\;TSI_{TP}\;75.5%)$ were in the eutrophic states. The groups were discriminated with environmental variables, showing that COD, DO, and TP were important factors to determine the trophic states. MLP-PSO (Multilayer perceptron (MLP) with PSO for the optimization) was applied for the prediction of chlorophyll-${\alpha}$ with environment factors, and showed high predictability (r=0.83, p<0.001). Additionally, the sensitivity analysis of the MLP-PSO model showed that COD had the strongest positive effects on the concentration of chlorophyll-${\alpha}$, and followed by TP, TN, DO, whereas altitude and bank height had negative effects on the concentration of chlorophyll-${\alpha}$.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.3
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• pp.281-301
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• 2024

The power cable tunnels which are part of the underground transmission line project, are constructed using the shield TBM method. The disc cutter among the shield TBM components plays an important role in breaking rock mass. Efficient tunnel construction is possible only when appropriate replacement occurs as the wear limit is reached or damage such as uneven wear occurs. A study was conducted to determine the wear conditions of disc cutter using a deep learning algorithm based on real-time measurement data of wear and rotation speed. Based on the results of full-scaled tunnelling tests, it was confirmed that measurement data was obtained differently depending on the wear conditions of disc cutter. Using real-time measurement data, an algorithm was developed to determine disc cutter wear characteristics based on a convolutional neural network model. Distributional patterns of data can be learned through CNN filters, and the performance of the model that can classify uniform wear and uneven wear through these pattern features.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.103-113
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• 2014

This study designed and implemented a query model for consecutive analyses of dynamic multivariate graph data. First, the query model consists of two procedures; setting the discriminant function, and determining an alteration method. Second, the query model was implemented as a query system that consists of a query panel, a graph visualization panel, and a property panel. A Node-Link Diagram and the Force-Directed Graph Drawing algorithm were used for the visualization of the graph. The results of the queries are visually presented through the graph visualization panel. Finally, this study used the data of worldwide import & export data of small arms to verify our model. The significance of this research is in the fact that, through the model which is able to conduct consecutive analyses on dynamic graph data, it helps overcome the limitations of previous models which can only perform discrete analysis on dynamic data. This research is expected to contribute to future studies such as online decision making and complex network analysis, that use dynamic graph models.

• The Journal of Engineering Research
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• v.2 no.1
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• pp.57-62
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• 1997

Two psychoacoustic models used in MPEG-1 employ different masking patterns, different masking indexes, and different computational procedures. As a result, Model 1 is inferior to Model 2 due to its worst case approach in computing the SMR even though it determines tonality and masking levels accurately. In this study, we investigate the performances of psychoacoustic models when we modify the MPEG-1 audio coder for variable bitrates. Simulation results show that Model 2 has a gain of 30 kbps in the dual channel mode and 20 kbps in the joint stereo mode. It is generally known that the joint stereo mode has a gain in bitrate compare to the dual channel mode. For signals with frequent attacks, this gain becomes larger in Model 1 than in Model 2. This is due to the fact that Model 1 uses the worst case approach in computing the SMR to reduce pre-echo

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.401-410
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• 2021

Recently, as cyber attacks targeting industrial control systems increase, various studies are being conducted on the detection of abnormalities in industrial processes. Considering that the industrial process is deterministic and regular, It is appropriate to determine abnormality by comparing the predicted value of the detection model from which normal data is trained and the actual value. In this paper, HAI Datasets 20.07 and 21.03 are used. In addition, an ensemble model is created by combining models that have applied different time steps to Gated Recurrent Units. Then, the detection performance of the single model and the ensemble recurrent neural networks model were compared through various performance evaluation analysis, and It was confirmed that the proposed model is more suitable for abnormal detection in industrial control systems.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.143-143
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• 2023

최근 대청댐('17), 평림댐('19) 등 광역 취수원에서 망간의 먹는 물 수질기준(0.05mg/L 이하) 초과 사례가 발생되어, 다수의 민원이 제기되는 등 취수원의 망간 관리 중요성이 부각되고 있다. 특히, 동절기 전도(Turn-over)시기에 고농도 망간이 발생되는 경우가 많은데, 현재 정수장에서는 망간을 처리하기 위해 유입구간에 필터를 설치하고 주기적으로 교체하는 방식으로 처리하고 있다. 그러나 단기간에 고농도 망간 다량 유입 시 처리용량의 한계 등 정수장에서의 공정관리가 어려워지므로 사전 예측에 의한 대응 체계 고도화가 필요한 실정이다. 본 연구는 광역취수원인 주암댐을 대상으로 망간 예측의 정확도 향상 및 예측기간 확대를 위해 다양한 머신러닝 기법들을 적용하여 비교 분석하였으며, 독립변수 및 초매개변수 최적화를 진행하여 모형의 정확도를 개선하였다. 머신러닝 모형은 수심별 탁도, 저수위, pH, 수온, 전기전도도, DO, 클로로필-a, 기상, 수문 자료 등의 독립변수와 화순정수장에 유입된 망간 농도를 종속변수로 각 변수에 해당하는 실측치를 학습데이터로 사용하였다. 그리고 데이터기반 모형의 정확도를 개선하기 위해서 성층의 수준을 판별하는 지표로서 PEA(Potential Energy Anomaly)를 도입하여 데이터 분석에 활용하고자 하였다. 분석 결과, 망간 유입률은 계절 주기에 따라 농도가 달라지는 것을 확인하였고 동절기 전도시점과 하절기 장마기간 난류생성 시기에 저층의 고농도 망간이 유입이 되는 것을 분석하였다. 또한, 두 시기의 망간 농도의 변화 패턴이 상이하므로 예측 모델은 각 계절별로 구축해 학습을 진행함으로써 예측의 정확도를 향상할 수 있었다. 다양한 머신러닝 모델을 구축하여 성능 비교를 진행한 결과, 동절기에는 Gradient Boosting Machine, 하절기에는 eXtreme Gradient Boosting의 기법이 우수하여 추론 모델로 활용하고자 하였다. 선정 모델을 통한 단기 수질예측 결과, 전도현상 발생 시기에 대한 추종 및 예측력이 기존의 데이터 모형만 적용했을 경우대비 약 15% 이상 예측 효율이 향상된 것으로 나타났다. 본 연구는 머신러닝 모델을 활용한 망간 농도 예측으로 정수장의 신속한 대응 체계 마련을 지원하고, 수처리 공정의 효율성을 높이는 데 기여할 것으로 기대되며, 후속 연구로 과거 시계열 자료 활용 및 물리모형과의 연결 등을 통해 모델의 신뢰성을 제고 할 계획이다.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.182-187
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• 2003

In this thesis, we propose the algorithm to improve the performance of speaker verification that is mapping feature parameters by using RBF neural network. There is a big difference between wire vector region and wireless one which comes from the same speaker. For wire/wireless speakers model production, speaker verification system should distinguish the wire/wireless channel that based on speech recognition system. And the feature vector of untrained channel models is mapped to the feature vector(LPC Cepstrum) of trained channel model by using RBF neural network. As a simulation result, the proposed algorithm makes 0.6%∼10.5% performance improvement compared to conventional method such as cepstral mean subtraction.

• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.176-185
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• 2003

The SCM is on the effective treatment solution that has process schedule, material supplying, inventory management for perfect product these days. The SCM is innovative process activity to attain effective whole. It depends on the structure of approach because supplying network is consist of organization, budgeting, responsibility and authority. The major objective of the thesis was to propose the integration model and structure method technique of the SCM. Thus, to implement strategy model, firstly, it is determined repairs and non-effectiveness of supplying network. secondly, to set up future vision and goal, it is considered success factor of supplying net. thirdly, no gaps introduce between present and future of supplying net fourthly as above-mentioned consequence, Alternative is to set up integration and implementing model according to enterprise administration strategy .

• KSCE Journal of Civil and Environmental Engineering Research
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• v.5 no.3
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• pp.13-20
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• 1985

An initial attempt to investigate the forced fortnightly water-level modulations in major tidal rivers in South Korea is described. Simplified one-dimensional hydrodynamic numerical models were established to reproduce the fortnightly tides in the Keum River and the Nakdong River respectively. The models were also used to identify the approximate locations of the reversal of MLWS and MLWN in the Keum River and the Nakdong River. The basic features of this forced fortnightly waves are explained through scaling arguments proposed by LeBlond. The objective of this initial study is to investigate the tidal dynamics of the major tidal rivers in South Korea.