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

• 한국농공학회논문집
• /
• 제54권4호
• /
• pp.65-71
• /
• 2012

The objective of this study was to estimate surface runoff from rice paddy plots using an artificial neural network (ANN). A field experiment with three treatment levels was conducted in the NICS saemangum experimental field located in Iksan, Korea. The ANN model with the optimal network architectures, named Paddy1901 with 19 input nodes, 1 hidden layer with 16 neurons nodes, and 1 output node, was adopted to predict surface runoff from the plots. The model consisted of 7 parameters of precipitation, irrigation rate, ponding depth, average temperature, relative humidity, wind speed, and solar radiation on the daily basis. Daily runoff, as the target simulation value, was computed using a water balance equation. The field data collected in 2011 were used for training and validation of the model. The model was trained based on the error back propagation algorithm with sigmoid activation function. Simulation results for the independent training and testing data series showed that the model can perform well in simulating surface runoff from the study plots. The developed model has a main advantage that there is no requirement for any prior assumptions regarding the processes involved. ANN model thus can be a good tool to predict surface runoff from rice paddy fields.

• 정보처리학회논문지D
• /
• 제11D권7호
• /
• pp.1451-1458
• /
• 2004

Gompertz 성장곡선에 기반한 기존의 소프트웨어 신뢰성 성장모델들은 모두 대수형이다. 대수형 Gompertz 성장 곡선에 기반한 소프트웨어 신뢰성 성장 모델들은 모수 추정에 어려움을 갖고 있다. 그러므로 본 논문은 로지스틱형 Gompertz 성장곡선에 기반한 신뢰성 성장 모델을 제안한다. 13개의 다른 소프트웨어 프로젝트로부터 얻은 고장 데이터를 분석하여 그 유용성을 검토하였다. 모델의 모수들은 변수변환을 통한 선형희귀분석과 Virence의 방법으로 추정되었다. 제안된 모델은 평균 상대 예측 오차에 기반하여 성능을 비교하였다. 실험 결과 제안된 모델은 대수형 Gompertz 성장 곡선에 기반한 모델보다 좋은 성능을 보였다.

• ETRI Journal
• /
• 제19권1호
• /
• pp.1-12
• /
• 1997

In this paper, we present an improved multicarrier direct sequence (DS) code division multiple access (CDMA) scheme by modifying the system originally proposed by Kondo and Milstein [13]. In this modified system, different spreading sequences multiplied by a data sequence modulate different carriers. This is to prevent the multiple access capability from reducing when the fading characteristics of different carrier frequencies are highly correlated. We have derived a formula which determines the mean values of the relative received signal strength in a single carrier DS CDMA rake system and in a multicarrier DS-CDMA system. We present results on the comparison of the bit error rate (BER) performance of the two systems including the effect of correlation between fading characteristics of different frequencies under various multipath fading conditions. The results indicate that with 50 users the modified multicarrier DS CDMA system can achieve an uncoded irreducible BER of $1.7{\times}10^{-3}$ with an average received signal-to-noise ratio per bit of 10dB, which is better that $3.0{\times}10^{-3}$ achieved by the single carrier DS CDMA rake system, and also show that if multicarrier CDMA system is used with respect to single carrier CDMA system, the SNR gain is up to 4.5 dB for the uncode BER of $10^{-3}$ being achieved.

• Wind and Structures
• /
• 제22권1호
• /
• pp.17-41
• /
• 2016

To address the uncertainty of the flight trajectories caused by the turbulence and gustiness of the wind field over the roof and in the wake of a building, a 3-D probabilistic trajectory model of flat-type wind-borne debris is developed in this study. The core of this methodology is a 6 degree-of-freedom deterministic model, derived from the governing equations of motion of the debris, and a Monte Carlo simulation engine used to account for the uncertainty resulting from vertical and lateral gust wind velocity components. The influence of several parameters, including initial wind speed, time step, gust sampling frequency, number of Monte Carlo simulations, and the extreme gust factor, on the accuracy of the proposed model is examined. For the purpose of validation and calibration, the simulated results from the 3-D probabilistic trajectory model are compared against the available wind tunnel test data. Results show that the maximum relative error between the simulated and wind tunnel test results of the average longitudinal position is about 20%, implying that the probabilistic model provides a reliable and effective means to predict the 3-D flight of the plate-type wind-borne debris.

• 한국지능시스템학회논문지
• /
• 제16권4호
• /
• pp.416-422
• /
• 2006

소프트웨어 개발 인력 프로파일에 대한 현존하는 모든 통계적 모델들은 소프트웨어 사용과 개발 프로세스의 가정에 기반을 두고 있어 일반적으로 적용 가능한 추정과 예측 모델이 없는 실정이다. 본 논문은 예측필터를 적용하여 소프트웨어 개발 투입 인력 프로파일을 예측하였다. 먼저 소프트웨어 개발 인력분포를 살펴보고, 예측필터를 적용하기 위해 모델의 입력 -출력, 모수를 결정하는 방법을 제시하였다. 이어서 제안된 모델의 유용성은 실제 개발된 소프트웨어 프로젝트로부터 획득된 데이터 분석으로 경험적으로 검증되었다. 평균 상대오차와 Pred(0.25)에 기반하여 제안된 예측필터는 잘 알려진 통계적 추정 모델들과 비교되었다. 검증 결과 예측필터는 단순한 구조를 갖고 있으면서도 소프트웨어 인력분포를 적절히 표현하는 결과를 보였다.

• 한국태양에너지학회 논문집
• /
• 제37권2호
• /
• pp.1-11
• /
• 2017

The investigation on reliability of ERA-Interim reanalysis wind data was conducted using wind data from the five met masts measured at inland and coastal areas, Jeju island. Shinchang, Handong, Udo, Susan and Cheongsoo sites were chosen for the met mast location. ERA-Interim reanalysis data at onshore and offshore twenty points over Jeju Island were analyzed for creating Wind Statistics using WindPRO software. Reliability of ERA-Interim reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those predicted at the interest point using the Wind Statistics. The relative errors were calculated for annual average wind speed and annual energy production. In addition, the trend of the error was analyzed with distance from met mast. As a result, ERA-Interim reanalysis wind data was more suitable for offshore wind resource assessment than onshore.

• 한국측량학회지
• /
• 제30권3호
• /
• pp.323-332
• /
• 2012

항공라이다 시스템은 대상지역의 자료를 취득하기 위하여 여러번 경로 관측을 수행하게 되며, 이로 인해 취득된 데이터의 인접 경로간에 편차가 발생한다. 본 연구에서는 스트립 데이터의 비행경로간 관측값의 상대오차를 제거하고 기준 데이터에 절대보정하는 방법으로 수정된 ICP를 이용한 자동 오차보정 기법을 제안하였다. 항공라이다 데이터에 절대 자동보정을 수행하기 위하여 기존의 수치지형도에서 기준점 데이터를 추출하고, 수정된 ICP알고리즘을 적용하였다. 위의 과정을 통하여 항공라이다 데이터의 평균 점간 거리 이내로 스트립간 조정 정확도를 향상시킬 수 있었으며, 대축척 수치지형도를 이용한 절대보정 과정의 자동화 가능성을 확인하였다.

• 한국태양에너지학회 논문집
• /
• 제29권2호
• /
• pp.22-30
• /
• 2009

In order to clarify predictive accuracy for the wind resource predicted by running WindPRO(Ver. 2.5) which is software for wind farm design developed by EMD from Denmark, an investigation was carried out at the northeast region of Jeju island. The Hangwon, Susan and Hoichun sites of Jeju island were selected for this study. The measurement period of wind at the sites was for one year. As a result, when the sites had different energy roses, though the two Wind Statistics made by STATGEN module were used for the prediction, it was difficult to exactly predict the energy rose at a given site. On the other hand, when the two Wind Statistics were used to predict the average wind speed, the wind power density and the annual energy production, the relative error was under ${\pm}20%$ which improved more than that when using only one Wind Statistics.

• Computers and Concrete
• /
• 제16권3호
• /
• pp.343-356
• /
• 2015

1078 sets of mixtures in total that include fly ash, slag, and/or silica fume have been collected for prediction on concrete properties. A new database platform (Compos) has been developed, by which the stepwise multiple linear regression (SMLR) and BP artificial neural networks (BP ANNs) programs have been applied respectively to identify correlations between the concrete properties (strength, workability, and durability) and the dosage and/or quality of raw materials'. The results showed obvious nonlinear relations so that forecasting by using nonlinear method has clearly higher accuracy than using linear method. The forecasting accuracy rises along with the increasing of age and the prediction on cubic compressive strength have the best results, because the minimum average relative error (MARE) for 60-day cubic compressive strength was less than 8%. The precision for forecasting of concrete workability takes the second place in which the MARE is less than 15%. Forecasting on concrete durability has the lowest accuracy as its MARE has even reached 30%. These conclusions have been certified in a ready-mixed concrete plant that the synthesized MARE of 7-day/28-day strength and initial slump is less than 8%. The parameters of BP ANNs and its conformation have been discussed as well in this study.