• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• 한국유기농업학회지
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• 제25권2호
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• pp.279-293
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• 2017

This study suggests the yield forecast models for autumn chinese cabbage and radish using crop growth and development information. For this, we construct 24 alternative yield forecast models and compare the predictive power using root mean square percentage errors. The results shows that the predictive power of model including crop growth and development informations is better than model which does not include those informations. But the forecast errors of best forecast models exceeds 5%. Thus it is important to establish reliable data and improve forecast models.

• 보건교육건강증진학회지
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• 제13권2호
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• pp.130-166
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• 1996

As compared with body height and body weight by ages and sexes, by means of the data reported under other researchers from 1967 to 1994 for 33 years, this study obtained the estimate value of body height and body weight by ages and sexes for the same period, and figured out prediction value of body height and body weight in the ages of between 6 and 14 from 1995 to 2000. These surveys and measurements took for one year from October 1st 1994 to September 30th. As shown in the 〈Table 1〉, in order to calculate the establishment, estimate value and prediction value of the chronological regression model of body height and body weight, by well-grounded 17 representative research papers, this research statistically tested propriety of liner regression model by the residual analysis in advance of being reconciled to simple liner regression model by the autonomous variable-year and the subordinate variable-body weight and measured prediction value, theoretical value from 1962 to 1994 by means of 2nd or 3rd polynomial regression model, with this redult did prediction value from 1995 to 2000. 1. Chronological Change of Body Height and Body Weight The analysis result from regression model of the chronological body height and body weight for the aged 6 - 16 in both sexes ranging from 1962 to 1994, corned from the 〈Table 2-20〉. On the one hand, the measurement value of respective researchers had a bit changes by ages with age growing, but the other hand, theoretical value, prediction value showed the regular increase by the stages and all values indicated a straight line on growth and development with age growing. That is, in case of the aged 6, males had 109.93cm in 1962 and females 108.93cm, but we found the increase that males had 1I8.0cm, females 1I3.9cm. In theoretical value, prediction value, males showed the increase from 109.88cm to 1I7.89cm and females from 109.27cm to 1I5.64cm respectively. There was the same inclination toward all ages. 2. Comparision to Measurement Value and Prediction Value of Body Height and Body Weight in 1994 As shown in the 〈Table 21〉, in case of body height, measurement value and prediction value of body height and body weight by ages and sexes almost showed the similiar inclination and poor grade, in case of body weight, prediction value in males had a bit low value by all ages, and prediction value in females had a high value in adolescence, to the contrary, a low value in adult. 3. Prediction Value of Body Height and Body Weight from 1995 to 2000 This research showed that body height and body weight remarkably increased in adolescence but slowly in adult. This study represented that Korean physique was on the increase and must be measured continually hereafter.

• Journal of Microbiology and Biotechnology
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• 제19권7호
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• pp.718-726
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• 2009

The objective of this study was to develop and validate secondary models that can predict growth parameters of L. monocytogenes Scott A as a function of concentrations (0-3%) of a commercial potassium lactate (PL) and sodium diacetate (SDA) mixture, pH (5.5-7.0), and temperature (4-37DC). A total of 120 growth curves were fitted to the Baranyi primary model that directly estimates lag time (LT) and specific growth rate (SGR). The effects of the variables on L. monocytogenes Scott A growth kinetics were modeled by response surface analysis using quadratic and cubic polynomial models of the natural logarithm transformation of both LT and SGR. Model performance was evaluated with dependent data and independent data using the prediction bias ($B_f$) and accuracy factors ($A_f$) as well as the acceptable prediction zone method [percentage of relative errors (%RE)]. Comparison of predicted versus observed values of SGR indicated that the cubic model fits better than the quadratic model, particularly at 4 and $10^{\circ}C$. The $B_f$and $A_f$for independent SGR were 1.00 and 1.08 for the cubic model and 1.08 and 1.16 for the quadratic model, respectively. For cubic and quadratic models, the %REs for the independent SGR data were 92.6 and 85.7, respectively. Both quadratic and cubic polynomial models for SGR and LT provided acceptable predictions of L. monocytogenes Scott A growth in the matrix of conditions described in the present study. Model performance can be more accurately evaluated with $B_f$and $A_f$and % RE together.

• 한국대기환경학회지
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• 제26권4호
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• pp.367-379
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• 2010

Future climate changes over the Seoul metropolitan area (SMA) were predicted by the Weather Research and Forecasting (WRF) model using future land-use data from the urban growth model (SLEUTH) and forecast fields from ECHAM5/MPI-OM1 GCM (IPCC scenario A1B). Simulations from the SLEUTH model with GIS information (slope, urban, hill-shade, etc.) derived from the water management information system (WAMIS) and the intelligent transportation systems-standard nodes link (ITS-SNL) showed that considerable increase by 17.1% in the fraction of urban areas (FUA) was found within the SMA in 2020. To identify the effects of the urban growth on the temperature and wind variations in the future, WRF simulations by considering urban growth were performed for two seasons (summer and winter) in 2020s (2018~2022) and they were compared with those in the present (2003~2007). Comparisons of model results showed that significant changes in surface temperature (2-meter) were found in an area with high urban growth. On average in model domain, positive increases of $0.31^{\circ}C$ and $0.10^{\circ}C$ were predicted during summer and winter, respectively. These were higher than contributions forced by climate changes. The changes in surface temperature, however, were very small expect for some areas. This results suggested that surface temperature in metropolitan areas like the SMA can be significantly increased only by the urban growth during several decades.

• 대한기계학회논문집A
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• 제26권11호
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• pp.2399-2408
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• 2002

A prediction procedure has been developed to evaluate the microtructures and material properties of heat affected zone (HAZ) in pressure vessel steel weld, based on temperature analysis, thermodynamics calculation and reaction kinetics model. Temperature distributions in HAE are calculated by finite element method. The microstructures in HAZ are predicted by combining the temperature analysis results with the reaction kinetics model for austenite grain growth and austenite decomposition. Substituting the microstructure prediction results into the previous experimental relations, the mechanical material properties such as hardness, yielding strength and tensile strength are calculated. The prediction procedure is modified and verified by the comparison between the present results and the previous study results for the simulated HAZ in reactor pressure vessel (RPV) circurnferential weld. Finally, the microstructures and mechanical material properties are determined by applying the final procedure to real RPV circumferential weld and the local weak zone in HAZ is evaluated based on the application results.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1530-1537
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• 2016

Recently, solar power generation shows the significant growth in the renewable energy field. Using the short-term prediction, it is possible to control the electric power demand and the power generation plan of the auxiliary device. However, a short-term prediction can be used when you know the weather forecast. If it is not possible to use the weather forecast information because of disconnection of network at the island and the mountains or for security reasons, the accuracy of prediction is not good. Therefore, in this paper, we proposed a system capable of short-term prediction of solar power generation amount by using only the weather information that has been collected by oneself. We used temperature, humidity and insolation as weather information. We have applied a moving average to each information because they had a characteristic of time series. It was composed of min, max and average of each information, differences of mutual information and gradient of it. An artificial neural network, SVM and RBF Network model was used for the prediction algorithm and they were combined by Ensemble method. The results of this suggest that using a moving average during pre-processing and ensemble prediction models will maximize prediction accuracy.

• 한국지리정보학회지
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• 제19권3호
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• pp.75-88
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• 2016

본 연구는 도시성장 시나리오와 CLUE-s 모형을 이용해 한반도의 시공간적인 미래 토지이용 변화를 예측하였다. 이를 위한 CLUE-s 모형의 입력 자료로 2008년 환경부 토지이용도와 국가수자원관리종합시스템(WAMIS)에서 1980년부터 2011년까지 5년 간격의 토지이용 통계 자료를 구축하였다. 토지이용 항목은 총 6개(수역, 시가지, 논, 밭, 산림, 초지)로 분류하였으며, 다양한 토지 변화요소(Driving Factor)와 특별토지이용 정책 자료로 환경부의 국토환경성평가 지도를 적용하였다. 시나리오 예측 결과는 각 도별로 2008년의 토지피복 통계와 비교를 통해 검증하였다. 시가지를 대상으로 한 실측값과의 오차율은 경기도(9.47%), 강원도(9.96%), 충청북도(10.63%), 충청남도(7.53%), 전라북도(9.48%), 전라남도(6.92%), 경상북도(2.50%), 경상남도(8.09%)로 나타났다. 이러한 오차의 원인은 미래 도시성장을 수학적으로 예측하기 위해 모형 내에서 조정된 성장률과 국가 정책으로 인한 실제 성장률의 차이로 인한 것으로 판단된다. 2100년의 미래 토지이용 변화 예측 결과 시가지는 2008년에 비해 28.24% 상승할 것으로 예측되었으며 논, 밭, 산림은 각각 8.27%, 6.72%, 1.66% 감소할 것으로 예측되었다.

• 한국식품과학회지
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• 제37권6호
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• pp.1012-1017
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• 2005

게맛살로부터 분리한 주요 부패세균은 내열성 포자를 형성하는 Bacillus subtilis와 Bacillus licheniformis로 동정되었다. 게맛살의 제조 공정상 가열 처리 과정에서 B. subtilis와 B. Licheniformis 등 내열성 포자를 형성하는 균을 완전히 사멸시키기는 어려우며, 살아남은 포자는 유통과정 중, 적정 온도와 시간이 경과함에 따라, 영향 세포로 발아하여 게맛살의 부패에 영향을 미친다. 이러한 부패세균의 증식에 있어서 초기균수와 온도의 영향을 조사한 결과, 초기균수에 따른 최대증식속도상수(k)와 유도기(LT), 세대시간(GT)은 유의적인 차이가 없었으며, 온도의 영향이 지배적인 것으로 나타났다. 또한 본 실험에서 유도기(LT)와 온도의 관계는 $L(hr)=2.5219e^{-0.2467{\cdot}T}$의 관계가 성립하며, square root model과 polynomial model을 이용, 온도와 초기균수에 대한 최대증식속도상수(k)를 정량화한 정량평가모델을 개발하였으며, 그 식은 다음과 같다. $$Square\;root\;model:\;{\sqrt{k}}=0.0267\;(T-3.5089)$$ $$Polynomial model:\;k=-0.2160+0.0241T-0.01999A_0$$ 온도와 초기균수에 대한 최대증식속도상수(k)의 정량평가모델로부터 특정온도와 초기 균수에서 최대증식속도상수(k)를 계산할 수 있으며, 계산된 최대증식속도상수(k)를 균의 기본 증식 모델인 Gomperz model에 적용하여 균의 성장을 예측할 수 있었다.

• 한국식품과학회지
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• 제36권2호
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• pp.349-354
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• 2004

수산식품에서 문제가 되는 식중독 균인 V. parahaemolyticus를 대상으로 온도, pH 및 초기균수에 따른 균의 성장 실험 결과를 데이터베이스화하여 이를 바탕으로 균의 성장을 정량적으로 평가할 수 있는 수학적 모델을 개발하였다. $1.0{\times}10^{2},\;1.0{\times}10^{3},\;1.0{\times}10^{4}\;CFU/mL$의 각 초기균수 조건에서 실험치와 예측치의 상관계수는 각각 0.966, 0.979, 0.965으로 나타났다. 또한, 초기균수를 고려하지 않은 모델식은 상관계수가 0.966으로 다음과 같이 나타났다. Polynomial model: $$k=1.10{\cdot}\exp(-0.5(((T-34.14)/9.09)^{2}+((pH-6.59)/4.68)^{2}))$$ 균의 증식 지표치인 최대증식속도상수 k는 온도에 지배적인 영향을 받았으며, pH 및 초기균수에 따른 유의적인 차이는 없었으므로 (P>0.05), k와 온도와의 관계식인 square root model로 나타내었다. Square root model: $${\sqrt{k}\;0.06(T-9.55)[1-\exp(0.07(T-49.98))]$$ V. parahaemolyticus의 경우, square root model에 의한 실험치와 예측치의 상관계수는 0.977로 polynomial model보다 높은 적용성을 나타내었다.