• 한국지반공학회논문집
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• 제20권3호
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• pp.47-51
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• 2004

불포화 투수계수함수는 흙수분 특성곡선과 함께 불포화토를 이해 연구하는데 있어서 없어서는 안 될 중요한 요소이다. 일반적으로 불포화 투수계수함수를 직접 측정하기에는 많은 어려움이 있기에, 흙수분 특성곡선에 근거한 예측함수를 사용하여 불포화 투수계수함수를 구하곤 했다. 본 연구에서는 이러한 예측함수를 사용하지 않고, 피스톤 펌프기법과 역해석 기법을 이용한 불포화 투수계수함수를 구하는 방법을 제시한다. 이렇게 구해진 불포화 투수계수함수는 예측함수를 사용하지 많았기 때문에, 흙수분 특성곡선으로부터 독립적이며 예측함수를 사용한 경우보다 보다 정확한 불포화토의 특성을 보여준다.

• 한국컴퓨터정보학회논문지
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• 제8권3호
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• pp.113-123
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• 2003

본 논문에서는 주식의 종가, 거래량 기술적 지표인 MACD(Moving Average Convergence Divergence) 값과 투자 심리선값을 입력 패턴으로 사용하여 개별 금융지표지수에 대한 매도, 중립 및 매수 시점 예측을 수행하는 신경망 모델이 제안된다. 이 모델은 역전파 알고리즘을 이용한 시계열 예측 기능과 균등다층연산 기능을 갖는다. 학습 데이터의 수가 각 범주들(매도, 중립, 매수)에 균일하게 분포되어 있지 않을 경우 기존의 신경망은 가장 우세한 범주의 예측 정확성만을 향상시키는 문제점을 가지고 있다. 따라서, 본 논문에서는 신경망의 구조, 동작, 학습 알고리즘에 대해 표현한 후 다른 범주의 예측 정확성도 향상시키기 위해 각 범주의 중요성을 이용하여 학습 데이터의 수를 조절하는 균등다층연산 방법을 제안한다. 실험 결과, 균등다층연산 신경망을 이용한 금융지표지수 예측 방법이 기존의 신경망을 이용한 금융지표지수 예측 방법 보다 각 범주에 대해 높은 정확성 비율을 보임을 확인할 수 있었다.

• Journal of applied mathematics & informatics
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• 제28권1_2호
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• pp.439-450
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• 2010

In this paper, we propose a new idea to evaluate the prediction accuracy of user's preference generated by memory-based collaborative filtering algorithm before prediction process in the recommender system. Our analysis results show the possibility of a pre-evaluation before the prediction process of users' preference of item's transaction on the web. Classification functions proposed in this study generate a user's rating pattern under certain conditions. In this research, we test whether classification functions select users who have lower prediction or higher prediction performance under collaborative filtering recommendation approach. The statistical test results will be based on the differences of the prediction accuracy of each user group which are classified by classification functions using the generative probability of specific rating. The characteristics of rating patterns of classified users will also be presented.

• 통합자연과학논문집
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• 제12권4호
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• pp.105-115
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• 2019

In this paper, a prediction system is proposed to control the brightness of smart street lamps by predicting the moving path through the reduction of consumption power and information of pedestrian's past moving direction while meeting the function of existing smart street lamps. The brightness of smart street lamps is adjusted by utilizing the walk tracking vector and soft hand-off characteristics obtained through the motion sensing sensor of smart street lamps. In addition, the motion vector is used to analyze and predict the pedestrian path, and the GPU is used for high-speed computation. Pedestrians were detected using adaptive Gaussian mixing, weighted difference imaging, and motion vectors, and motions of pedestrians were analyzed using the extracted motion vectors. The preprocessing process using linear interpolation is performed to improve the performance of the proposed prediction system. Fuzzy prediction system and neural network prediction system are designed in parallel to improve efficiency and rough set is used for error correction.

• Genomics & Informatics
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• 제6권4호
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• pp.166-172
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• 2008

A multitude of protein-coding sequence variations (CVs) in the human genome have been revealed as a result of major initiatives, including the Human Variome Project, the 1000 Genomes Project, and the International Cancer Genome Consortium. This naturally has led to debate over how to accurately assess the functional consequences of CVs, because predicting the functional effects of CVs and their relevance to disease phenotypes is becoming increasingly important. This article surveys and compares variation databases and in silico prediction programs that assess the effects of CVs on protein function. We also introduce a combinatorial approach that uses machine learning algorithms to improve prediction performance.

• 소성∙가공
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• 제21권7호
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• pp.420-425
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• 2012

A new model is suggested for the prediction of radial displacements of a roll in order to analyze multi-high rolling mills. The model was developed from predictions based on finite element simulations. This model utilizes the compliance coefficient, which is expressed as a function of three dimensionless parameters, and is approximated by using the same interpolation function as used in the finite element method. The prediction accuracy of the model is demonstrated through comparison with the predictions from the FE model.

• The Korean Journal of Ecology
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• 제25권1호
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• pp.29-31
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• 2002

The purpose of this study is to estimate height growth patterns and site index cuties (base index age 50 years) for Japanese red cedar trees(Cryptomeria japonica D. Don) grown in southern regions of Korea. The Chapman-Richards growth function was selected for stand height prediction using on the results of stem analysis data sets. Anamorphic base age invariant site index cuties were presented based on this height prediction equation. The resulting site index prediction equation can provide an indication of the productivity of the site quality based on Japanese red cedar trees plantation ages planted in southern regions of Korea.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1995년도 가을 학술발표회 논문집
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• pp.124-128
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• 1995

It is the "maturity rule" that concrete of the same mix, at the same maturity, has the same strength. In this study, the Nurse-Saul function which was proposed to account for the effects of temperature and time on strength development is used in computing maturity. After existing various functions to relate concrete strength to the maturity value are considered, new strenth-maturity function is proposed. Tests are conducted in order to compare prediction value with measured concrete strength. The constants in proposed prediction equation are determined by standard specimens(cylinders) test, and the equation is adopted to predict strength of slab. The slab was cast in the laboratory from the same batch of mole, and cores are cut from slab in order to estimate the actual strength. Tehese values are used to compare with proposed equation. equation.

• 한국철도학회논문집
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• 제9권4호
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• pp.419-424
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• 2006

In this paper we study on a method to predict and to demonstrate the reliability of the Korea high speed train control system in quantitative point of view. For the prediction of the reliability in train control system which is composed of electronic parts, Relax Software 7.7 automation tool is employed and MIL-HDBK-217 Handbook that is a standard for the prediction of the failure rate in electronic components is used. Mean Time Between Failure (MTBF) is predicted based on the failure rate of the subsystems, State Modeling and Markov Modeling method is used to express a reliability function of the train control system composed by hardware redundancy as a function of time. We propose a Reliability Test which is performed on the level of the subsystems and Failure Report, Analysing, Correction action system which use the test operation data to prove the predicted reliability.

• Journal of Welding and Joining
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• 제31권3호
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• pp.44-48
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• 2013

Artificial neural network (ANN) model is applied to predict arc welding process window for automotive steel plate. Target weldment was various automotive steel plate combination with lap fillet joint. The accuracy of prediction was evaluated through comparison experimental result to ANN simulation. The effect of ANN variables on the accuracy is investigated such as number of hidden layers, perceptrons and transfer function type. A static back propagation model is established and tested. The result shows comparatively accurate predictability of the suggested ANN model. However, it restricts to use nonlinear transfer function instead of linear type and suggests only one single hidden layer rather than multiple ones to get better accuracy. In addition to this, obvious fact is affirmed again that the more perceptrons guarantee the better accuracy under the precondition that there are enough experimental database to train the neural network.