• 제목/요약/키워드: back prediction

검색결과 449건 처리시간 0.028초

Modeling properties of self-compacting concrete: support vector machines approach

  • Siddique, Rafat;Aggarwal, Paratibha;Aggarwal, Yogesh;Gupta, S.M.
    • Computers and Concrete
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    • 제5권5호
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    • pp.461-473
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    • 2008
  • The paper explores the potential of Support Vector Machines (SVM) approach in predicting 28-day compressive strength and slump flow of self-compacting concrete. Total of 80 data collected from the exiting literature were used in present work. To compare the performance of the technique, prediction was also done using a back propagation neural network model. For this data-set, RBF kernel worked well in comparison to polynomial kernel based support vector machines and provide a root mean square error of 4.688 (MPa) (correlation coefficient=0.942) for 28-day compressive strength prediction and a root mean square error of 7.825 cm (correlation coefficient=0.931) for slump flow. Results obtained for RMSE and correlation coefficient suggested a comparable performance by Support Vector Machine approach to neural network approach for both 28-day compressive strength and slump flow prediction.

고속선 궤도틀림진전예측에 관한 연구 (A Study on High Speed Railway Track Deterioration Prediction)

  • 심윤섭;김기동;이성욱;우병구;이기우
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2010년도 춘계학술대회 논문집
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    • pp.261-267
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    • 2010
  • Present maintenance of a high speed railway is after the fack maintenance that executes a task when measured value goes over threshold value except some planned maintenance. It is difficult from efficient management of maintenance human resource and equipment commitment because it is difficult to predict quantity of maintenance targets. Corrective maintenance is pushed back on the repair priority of other target to need repair and it is exceeded repair cost potentially. For safety and dependable track management because track deterioration prediction is linked directly with track's life and safety of train service, it is very important that track management be based on preventive maintenance. In this study, we propose statistics model of track quality to use track inspection data and forecast model for track deterioration prediction.

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The application of neural network system to the prediction of pollutant concentration in the road tunnel

  • Lee, Duck-June;Yoo, Yong-Ho;Kim, Jin
    • 한국지구물리탐사학회:학술대회논문집
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    • 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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    • pp.252-254
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    • 2003
  • In this study, it was purposed to develop the new method for the prediction of pollutant concentration in road tunnels. The new method was the use of artificial neural network with the back-propagation algorithm which can model the non-linear system of tunnel environment. This network system was separated into two parts as the visibility and the CO concentration. For this study, data was collected from two highway road tunnels on Yeongdong Expressway. The tunnels have two lanes with one-way direction and adopt the longitudinal ventilation system. The actually measured data from the tunnels was used to develop the neural network system for the prediction of pollutant concentration. The output results from the newly developed neural network system were analysed and compared with the calculated values by PIARC method. Results showed that the prediction accuracy by the neural network system was approximately five times better than the one by PIARC method. ill addition, the system predicted much more accurately at the situation where the drivers have to be stayed for a while in tunnels caused by the low velocity of vehicles.

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대도시 도로교통 소음 예측 연구 (Study on the prediction of urban road traffic)

  • 여운호
    • 소음진동
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    • 제6권2호
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    • pp.253-259
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    • 1996
  • Neighboring buildings which are sufficiently close to both sides of an urban street reflect sound back to the road and sound energy is increased by thses reflectors. Therefore, this study is forcussed on the prediction modeling for road traffic noise under reflective conditions. A part of a block in urban road is regared as a box. The sound energy density in the box is employed to establish prediction formulas in terms of independent variables. The variables. The validity of the proposed prediction method has been experimentally confirmed by applying it to actually measured road traffic noise data. On the whole, the agreement between measured and predicted noise levels appeared to be satisfactory.

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유한요소법에 기초한 박판에서의 압하력 및 압연동력 정밀 예측 On-Line모델 (II) 장력의 영향 (FE-based On-Line Model for the Prediction of Roll Force and Roll Power in Finishing Mill (II) Effect of Tension)

  • 곽우진;김영환;박해두;이중형;황상무
    • 한국소성가공학회:학술대회논문집
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    • 한국소성가공학회 2001년도 추계학술대회 논문집
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    • pp.121-124
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    • 2001
  • On-line prediction model which calculate roll force, roll power and forward slip of continuous hot strip rolling was built based on the results of plane strait rigid-viscoplastic finite element process model. Using the integrated FE process model, a series of finite element simulation was conducted over the process variables, and the influence of various process conditions on non-dimensional parameters was inspected. The prediction accuracy of the proposed on-line model under front and back tension is examined through comparison with predictions from a finite element process model over the various process conditions. In addition, we examined the validity of the on-line prediction model through comparison with roll force of experiment in hot rolling.

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훈련데이터 집합을 사용하지 않는 소프트웨어 품질예측 모델 (A Software Quality Prediction Model Without Training Data Set)

  • 홍의석
    • 정보처리학회논문지D
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    • 제10D권4호
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    • pp.689-696
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    • 2003
  • 설계 개체의 결함경향성을 판별하는 위험도 예측 모델은 분석이나 설계 같은 소프트웨어 개발 초기 단계에서 시스템의 문제 부분들을 찾아 내는데 사용된다. 복잡도 메트릭에 기반한 많은 위험도 예측 모델들이 제안되었지만 그들 대부분은 모델 훈련을 위한 훈련데이터 집합을 필요로 하는 모델들이었다. 하지만 대부분의 개발집단은 훈련데이터 집합을 보유하고 있지 않기 때문에 이들 모델들은 대부분의 개발집단에서 사용될 수 없다는 커다란 문제점이 있었다. 이러한 문제점을 해결하기 위해 본 논문에서는 Kohonen SOM 신경망을 이용하여 훈련데이터 집합을 사용하지 않는 새로운 예측 모델 KSM을 제안한다. 여러 내부 특성들과 모델 사용의 용이성 그리고 모의실험을 통한 예측 정확도 비교를 통해 KSM을 잘 알려진 예측 모델인 역전파 신경망 모델(BPM)과 비교하였으며 그 결과 KSM의 성능이 BPM에 근접하다는 것을 보였다.

전화조사에서 재통화 규칙준수와 응답자 임의선택의 영향 - R&R 울산 사례의 통계적 재분석 - (Effects of Call-back Rules and Random Selection of Respondents: Statistical Re-analysis of R&R’s Ulsan Survey Data.)

  • 허명회;임여주;노규형
    • 응용통계연구
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    • 제16권2호
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    • pp.247-259
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    • 2003
  • 우리나라 조사업계에서는 전화조사의 방법론으로 성과 나이, 지역에 표본 수를 사전 지정하는 방식의 할당표집 (quota sampling)을 주로 쓰고 있다. 이러한 할당표집은 조사비용과 기간의 단축이라는 이점을 갖지만 이론적 타당성이 결여되어 있어 학문적으로는 받아들이기 어렵다. 때문에, 학계에서는 그 동안 수차례 임의표집(random sampling)에 근거한 전화조사를 조사업계에 요구해 왔다. 이에 응하여, (주)리서치 앤 리서치가 2002년 울산시장 선거예측 조사에 임의표집에 의한 전화조사를 실시하였다 본 사례연구는 이 자료를 심층적으로 재분석하여 임의표집에서의 재통화 및 응답자 임의선정 절차가 자료 질 및 최종 예측치에 주는 영향에 대하여 살펴볼 것이다.

강우-유출 예측모형 개발을 위한 자기조직화 이론의 적용 (Application of Self-Organizing Map Theory for the Development of Rainfall-Runoff Prediction Model)

  • 박성천;진영훈;김용구
    • 대한토목학회논문집
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    • 제26권4B호
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    • pp.389-398
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    • 2006
  • 본 연구에서는 강우의 시 공간적 분포의 불규칙한 변동성을 고려한 강우-유출예측모형을 위해 인공신경망(Artificial Neural Networks: ANNs)의 기법의 일종인 자기조직화(Self Organizing Map: SOM) 이론과 역전파 학습 알고리즘(Back Propagation Algorithm: BPA을 복합적으로 이용하였다. 기존의 인공신경망 연구에서 야기된 저 갈수기의 유출량에 대한 과대평가, 홍수기의 유출량에 대한 과소평가, 예측값이 연속적으로 선행 유출량을 나타내는 Persistence 현상을 해결하기 위하여 패턴분류 성능을 지닌 SOM 이론을 예측모형의 전처리 과정으로 이용하였다. 먼저, 본 연구에서 제안한 방법은 SOM에 의해 강우-유출 관계를 분류하고, SOM에 의한 분류에 따라 각각의 모형을 구성한다. 개별적으로 구축된 모형은 유출량의 예측을 위해 각각의 양상에 따라 분류된 자료를 이용한다. 결과적으로 본 연구에서 제안한 방법은 과거의 인공신경망의 일반적인 적용에 의한 결과보다 더 나은 예측능력을 보여주었으며, 더불어 유출량의 과소 및 과대추정과 Persistence 현상과 같은 문제점이 나타나지 않았다.

역해석기법을 통한 NATM 터널의 안정성 평가 (Stability Estimation of NATM Tunnel due to Excavation using Back Analysis)

  • 이재호;김영수;김광일;박진규;박시현;최칠용
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2008년도 춘계 학술발표회 초청강연 및 논문집
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    • pp.494-504
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    • 2008
  • Successful design, construction and maintenance of NATM tunnel demands prediction, control, stability estimation and monitoring of surface settlement, gradient and ground displacement with high accuracy. Back analysis using measured data and forward analysis have been and are indispensable tools to achieve this goal. Sakurai provided the hazard warning levels for assessing the stability of tunnels using the relation of critical strain and apparent Young's modulus. This paper performed the estimation of tunnel stability on construction. Firstly, the apparent Young's modulus concept and back analysis method is introduced for the assessment of tunnel safety during excavation a brief framework. Secondly, this paper deals with case study using "Apparent Young's modulus" and "Back analysis" for the purpose of estimating the stability of NATM tunnel in Korea. Finally, a general method that can be estimated the tunnel stability discussed by a flow chart.

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근전도를 이용한 Sorensen 검사시 성인남녀 등 근육의 근피로도 분석 (Spectral Electromyographic Fatigue Analysis of Back Muscles in Healthy Adult Men and Women During Sorensen Test)

  • 이미선;김태영
    • 한국전문물리치료학회지
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    • 제5권3호
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    • pp.63-71
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    • 1998
  • Trunk holding test (Sorensen test) appear to have more value than strength test in prediction the occurrence of low back pain. Electromyographic activity of trunk extensor muscles during these test may provide clues to the etiology of neuromuscular-based low back pain. This study investigated the difference in back muscle endurance between healthy adult men and women using surface electromyographic (EMG) power spectral analysis. Thirty hea1thy subjects (15 men and 15 women) performed an unsupported trunk holding test for 60 seconds. Recording surface electrodes were placed over the erector spinae medially and laterally at vertebral levels of $L_1$ and $L_5$. Slope of total frequency was evaluated using the MP100WSW Fast Fourier Transform spectrum analysis program. The slopes of all indices of back muscle fatigue, except right $L_5$, were significantly steeper in men than in women (p<0.05). Our results indicated that the trunk holding test using EMG power spectral analysis of erector spinae muscles is useful for the evaluation of fatigue rate of these muscles. Our results also showed a higher muscle endurance in healthy adult women than in men.

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