• 교육녹색환경연구
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• 제11권3호
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• pp.46-54
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• 2012

The accuracy of cost estimation at an early stage in school building project is one of the critical factors for successful completion. So various of techniques are developed to predict the construction cost accurately and expeditely. Among the techniques, Support Vector Machine(SVM) has an excellent ability for generalization performance. Therefore, the purpose of this study is to construct the prediction model for construction cost of educational building project using support vector machine technique. And to verify the accuracy of prediction model for construction cost. The performance data used in this study are 217 school building project cost which have been completed from 2004 to 2007 in Gyeonggi-Do, Korea. The result shows that average error rate was 7.48% for SVM prediction model. So using SVM model on predicting construction cost of educational building project will be a considerably effective way at the early project stage.

• Smart Structures and Systems
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• 제29권6호
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• pp.799-805
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• 2022

Permanent magnet synchronous motors (PMSMs) are widely used in systems requiring high control precision, efficiency, and reliability. Predicting the remaining useful life (RUL) with health monitoring of PMSMs prevents catastrophic failure and ensures reliable operation of system. In this study, a model-based method for predicting the RUL of PMSMs using phase current and vibration signals is proposed. The proposed method includes feature selection and RUL prediction based on a particle filter with a degradation model. The Paris-Erdogan model describing micro fatigue crack propagation is used as the degradation model. An experimental set-up to conduct accelerated life test, capable of monitoring various signals was designed in this study. Phase current and vibration data obtained from an accelerated life test of the PMSMs were used to verify the proposed approach. Features extracted from the data were clustered based on monotonicity and correlation clustering, respectively. The results identify the effectiveness of using the current data in predicting the RUL of PMSMs.

• Agricultural and Biosystems Engineering
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• 제4권1호
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• pp.34-38
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• 2003

A mathematical model was developed for estimating the mechanical interrelation between characteristics of soil and main design factors of a tracked vehicle, and predicting the tractive performance of the tracked vehicle. Based on the mathematical model, a computer simulation program (TPPMTV) was developed in the study. The model considered the continuous change in tension for the whole track of a tracked vehicle, the analysis of shape and tension of the track segment between sprocket and first roadwheel, and the side thrust on both sides of grouser by the active earth pressure theory in predicting the tractive performance of a tracked vehicle. Also, the model contained not only sinkage depth of the track but the pressure distribution under the track in analyzing the side thrust. The effectiveness of the developed model was verified by performing the draw bar pull tests with a tracked vehicle reconstructed for test in loam soil with moisture content of 18.92％. The predicted drawbar pulls by the model were well matched to the measured ones. Such results implied that the model developed in the study could estimate the drawbar pulls well at various soil conditions, and would be very useful as a simulation tool for designing a tracked vehicle and predicting its tractive performance.

• Geomechanics and Engineering
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• 제10권1호
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• pp.49-57
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• 2016

The high permeability-high strength concrete belongs to the typical of porous materials. It is mainly used in underground engineering for cold area, it can act the role of heat preservation, also to be the bailing and buffer layer. In order to establish a suitable model to predict the thermal conductivity and directly applied for engineering, according to the structure characteristics, the thermal conductivity predicting model was built by resistance network model of parallel three-phase medium. For the selected geometric and physical cell model, the thermal conductivity forecast model can be set up with aggregate particle size and mixture ratio directly. Comparing with the experimental data and classic model, the prediction model could reflect the mixture ratio intuitively. When the experimental and calculating data are contrasted, the value of experiment is slightly higher than predicting, and the average relative error is about 6.6%. If the material can be used in underground engineering instead by the commonly insulation material, it can achieve the basic requirements to be the heat insulation material as well.

• 대한산업공학회지
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• 제33권4호
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• pp.402-409
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• 2007

Markov Chains has proven to be effective in predicting human behaviors in the areas of web site assess, multimedia educational system, and driving environment. In order to extend an application area of predicting human behaviors using Markov Chains, this study was conducted to investigate whether Markov Chains could be used to predict human behavior in selecting mobile phone menu item. Compared to the aforementioned application areas, this study has different aspects in using Markov Chains : m-order 1-step Markov Model and the concept of Power Law of Learning. The results showed that human behaviors in predicting mobile phone menu selection were well fitted into with m-order 1-step Markov Model and Power Law of Learning in allocating history path vector weights. In other words, prediction of mobile phone menu selection with Markov Chains was capable of user's actual menu selection.

• 한국산림과학회지
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• 제99권1호
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• pp.57-61
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• 2010

본 연구는 난대산림연구소의 제주시험림에 있는 붉가시나무(Quercus acuta)에 대한 개체목의 수간곡선식 추정 및 간재적을 추정하기 위하여 수행되었다. 최적의 추정식을 선택하기 위하여 Max and Burkhart식, Kozak식 및 Lee식을 적용하여 각 식의 직경 추정에 대한 검정 통계량 및 실측치와 추정치간의 오차분포를 검증하였다. 그 결과 Max and Burkhart식 및 Lee식이 특정 구간에서 과대치 또는 과소 추정치를 보인데 반하여 Kozak식은 전구간에서 고른 분포를 보였다. 추정력이 가장 좋은 Kozak식을 활용하여 수피포함 재적표를 작성하였다.

• 설비공학논문집
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• 제12권11호
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• pp.1038-1047
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• 2000

The objective of this study is to develop an optimized Artificial Neural Network(ANN) model to predict the descending time of room air temperature. For this, program for predicting room air temperature and ANN program using generalized delta rule were collected through simulation for predicting room air temperature. ANN was trained and the ANN model having the optimized values-learning rate, moment, bias, number of hidden layer, and number of neuron of hidden layer was presented.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 추계학술대회 논문집
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• pp.121-126
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• 2003

This paper is concerns with the development of the formulae to predict deformation of curved plate due to line heating. For this purpose thermal elasto-plastic analysis has been carried out for both flat and curved plate models with varying parameters which affect the result of line heating. based on the results of numerical analysis, the formulae for predicting angular deformation has been derived through the regression analysis, which. It has been seen that the present model well agrees with the numerical analysis results and can reflect the curvature effect of plate to be heated. This paper ends with some comments on this formulae.

• Tribology and Lubricants
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• 제25권3호
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• pp.150-156
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• 2009

Precise leakage prediction for annular type seals of turbomachinery is necessary for enhancing their efficiency and various prediction methods have been developed. As the seal passage is designed intricately, the analysis based on Bulk-flow concept which has been mainly used in predicting seal leakage is limited. In order to improve the seal leakage prediction, full Navier-Stokes Equations with turbulent model derived in the seal flow passage have to be solved. In this study, 3D CFD (Computational Fluid Dynamics) analysis has been performed for predicting leakage of various non-contact type anular seals using FLUENT. Compared to the results by Bulk-flow model analysis, experiment, and 2D CFD analysis, the result of 3D CFD analysis shows improvement in predicting seal leakage, especially for the parallel grooved pump seal.

• 대한조선학회 특별논문집
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• 대한조선학회 2005년도 특별논문집
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• pp.177-184
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• 2005

This paper is concerns with the development of the formulae to predict deformation of curved plate due to line heating. For this purpose thermal elasto-plastic analysis has been carried out for both flat and curved plate models with varying parameters which affect the result of line heating. based on the results of numerical analysis, the formulae for predicting angular deformation has been derived through the regression analysis, which. It has been seen that the present model well agrees with the numerical analysis results and can reflect the curvature effect of plate to be heated. This paper ends with some comments on this formulae.