• Title/Summary/Keyword: Objective Prediction

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THE EFFECTS OF UNCERTAIN TOPOGRAPHIC DATA ON SPATIAL PREDICTION OF LANDSLIDE HAZARD

  • Park, No-Wook;Kyriakidis, Phaedon C.
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.259-261
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    • 2008
  • GIS-based spatial data integration tasks have used exhaustive thematic maps generated from sparsely sampled data or satellite-based exhaustive data. Due to a simplification of reality and error in mapping procedures, such spatial data are usually imperfect and of different accuracy. The objective of this study is to carry out a sensitivity analysis in connection with input topographic data for landslide hazard mapping. Two different types of elevation estimates, elevation spot heights and a DEM from ASTER stereo images are considered. The geostatistical framework of kriging is applied for generating more reliable elevation estimates from both sparse elevation spot heights and exhaustive ASTER-based elevation values. The effects of different accuracy arising from different terrain-related maps on the prediction performance of landslide hazard are illustrated from a case study of Boeun, Korea.

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Optimization of spring back in U-die bending process of sheet metal using ANN and ICA

  • Azqandi, Mojtaba Sheikhi;Nooredin, Navid;Ghoddosian, Ali
    • Structural Engineering and Mechanics
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    • v.65 no.4
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    • pp.447-452
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    • 2018
  • The controlling and prediction of spring back is one of the most important factors in sheet metal forming processes which require high dimensional precision. The relationship between effective parameters and spring back phenomenon is highly nonlinear and complicated. Moreover, the objective function is implicit with regard to the design variables. In this paper, first the influence of some effective factors on spring back in U-die bending process was studied through some experiments and then regarding the robustness of artificial neural network (ANN) approach in predicting objectives in mentioned kind of problems, ANN was used to estimate a prediction model of spring back. Eventually, the spring back angle was optimized using the Imperialist Competitive Algorithm (ICA). The results showed that the employment of ANN provides us with less complicated and time-consuming analytical calculations as well as good results with reasonable accuracy.

Reliability Improvement of In-Place Concreter Strength Prediction by Ultrasonic Pulse Velocity Method (초음파 속도법에 의한 현장 콘크리트 강도추정의 신뢰성 향상)

  • 원종필;박성기
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.43 no.4
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    • pp.97-105
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    • 2001
  • The ultrasonic pulse velocity test has a strong potential to be developed into a very useful and relatively inexpensive in-place test for assuring the quality of concrete placed in structure. The main problem in realizing this potential is that the relationship between compressive strength ad ultrasonic pulse velocity is uncertain and concrete is an inherently variable material. The objective of this study is to improve the reliability of in-place concrete strength predictions by ultrasonic pulse velocity method. Experimental cement content, s/a rate, and curing condition of concrete. Accuracy of the prediction expressed in empirical formula are examined by multiple regression analysis and linear regression analysis and practical equation for estimation the concrete strength are proposed. Multiple regression model uses water-cement ratio cement content s/a rate, and pulse velocity as dependent variables and the compressive strength as an independent variable. Also linear regression model is used to only pulse velocity as dependent variables. Comparing the results of the analysis the proposed equation expressed highest reliability than other previous proposed equations.

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Orientation Prediction of Lamella Structure of High Carbon steel in Wire Drawing (신선가공시 고탄소강 선재 층상구조의 정렬 예측)

  • Kim Hyun Soo;Bae Chul Min;Lee Chung Yeol;Kim Byung Min
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.10 s.175
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    • pp.49-55
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    • 2005
  • The objective of this study was presented with a prediction on the alignment of cementite in pearlite lamella structure of high carbon steel by means of finite-element method(FEM) simulation. Pearlite strcuture was characterized by its nano-sized microstructure feature of alternation ferrite and cementite. FEM simulations were performed based on a suitable FE model describing the boundary conditions and the material behavior. With the alignment of lamella structure in high carbon pearlite steel wire, material plastic behavior was taken into account on plastic deformation and alignment of cementite. The effects of many important parameters(reduction in area, semi-die angle, initial angle of cementite ) on wire drawing process were predicted by DEFORM-2D. As the results, the possibility of wire fracture could be considerably reduced and the productivity of final product could be more increased than before.

Cloud Forecast using Numerical Weather Prediction (수치 예보를 이용한 구름 예보)

  • Kim, Young-Chul
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.15 no.3
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    • pp.57-62
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    • 2007
  • In this paper, we attempted to produce the cloud forecast that use the numerical weather prediction(NWP) MM5 for objective cloud forecast. We presented two methods for cloud forecast. One of them used total cloud mixing ratio registered to sum(synthesis) of cloud-water and cloud-ice grain mixing ratio those are variables related to cloud among NWP result data and the other method that used relative humidity. An experiment was carried out period from 23th to 24th July 2004. According to the sequence of comparing the derived cloud forecast data with the observed value, it was indicated that both of those have a practical use possibility as cloud forecast method. Specially in this Case study, cloud forecast method that use total cloud mixing ratio indicated good forecast availability to forecast of the low level clouds as well as middle and high level clouds.

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The Numerical Study on Prediction of Diesel Fuel Spray Evolution in a Different Types of Nozzle Geometry (노즐 형상에 따른 디젤 연료 분무의 발달 예측에 관한 수치 해석적 연구)

  • Min, Se Hun;Suh, Hyun Kyu
    • Journal of ILASS-Korea
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    • v.22 no.4
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    • pp.169-174
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    • 2017
  • The objective of this study was to verify the experimental and numerical results of spray evolution injected from different types of the nozzle-hole geometries. Spray visualization was taken by high speed camera under the different conditions. For the simulations of spray tip penetration, turbulence, evaporation and break-up model were applied K-zeta-f, Dukowicz and Wave model, respectively. Also, the prediction accuracy of spray tip penetration was increased by varying the spray cone angle. At the same time, the results of this work were compared in terms of spray tip penetration, and SMD characteristics. The numerical results of spray evolution process and spray tip penetration showed good agreement with experimental one.

Combustion Instability Prediction Using 1D Thermoacoustic Model in a Gas Turbine Combustor (가스터빈 연소기에서 1D 열음향 모델을 이용한 연소불안정 예측)

  • Kim, Jin Ah;Kim, Daesik
    • Journal of ILASS-Korea
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    • v.20 no.4
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    • pp.241-246
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    • 2015
  • The objective of the current study is to develop an 1D thermoacoustic model for predicting basic characteristics of combustion instability and to investigate effects of key parameters on the instabilities such as effects of flame geometry and acoustic boundary conditions. Another focus of the paper is placed on limit cycle prediction. In order to improve the model accuracy, the 1D model was modified considering the actual flame location and flame length (i.e. distribution of time delay). As a result, it is found that the reflection coefficients have a great effect on the growth rate of the instabilities. In addition, instability characteristics are shown to be strongly dependent upon the fuel compositions.

A convenient approach for penalty parameter selection in robust lasso regression

  • Kim, Jongyoung;Lee, Seokho
    • Communications for Statistical Applications and Methods
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    • v.24 no.6
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    • pp.651-662
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    • 2017
  • We propose an alternative procedure to select penalty parameter in $L_1$ penalized robust regression. This procedure is based on marginalization of prior distribution over the penalty parameter. Thus, resulting objective function does not include the penalty parameter due to marginalizing it out. In addition, its estimating algorithm automatically chooses a penalty parameter using the previous estimate of regression coefficients. The proposed approach bypasses cross validation as well as saves computing time. Variable-wise penalization also performs best in prediction and variable selection perspectives. Numerical studies using simulation data demonstrate the performance of our proposals. The proposed methods are applied to Boston housing data. Through simulation study and real data application we demonstrate that our proposals are competitive to or much better than cross-validation in prediction, variable selection, and computing time perspectives.

Prediction of Effluent Concentration for Contaminated Stream Purification using UFBR (상향류식 고정생물막조를 이용한 오염소하천 정화에 있어서 유출수 농도 예측)

  • Park, Young-Seek;Moon, Jung-Hynu;Ahn, Kab-Hwan
    • Journal of Wetlands Research
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    • v.4 no.1
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    • pp.87-95
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    • 2002
  • The objective of this study is to treat contaminated stream by using a UFBR(upflow fixed biofilm reactor) packed with waste-concrete media. This system was tested from June 1999 to January 2000. Over $20.0^{\circ}C$, $COD_{cr}$ removal efficiency did not affected with organic loading rate while, $COD_{cr}$ removal efficiency decreased about 7% with decrease of temperature from $27.0^{\circ}C$ to $8.7^{\circ}C$. Under $16^{\circ}C$, TKN removal efficiency was affected with TKN loading rate. The proposed model apply to mass balance equation of fixed biofilm reactor for predicting effluent was well satisfied with measured value($R^2=0.94$).

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Optimum Design of Axial-Flow Fans Including Noise Parameters (소음파라메터를 고려한 축류송풍기의 최적설계)

  • Son, B.J.;Lee, S.H.;Yoon, S.J.
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.7 no.1
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    • pp.1-12
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    • 1995
  • In order to seek various relationships among many design parameters employed in the design of the axial-flow fans the program which generates acoustic spectrum has been developed and its validity verified. Outputs of the program, with other outputs from a formerly developed performance prediction program, have been used to form a multi-objective function, for which an optimal design process was carried out. The present analysis shows that overall noise level and efficiency has contrasting trends, and the chord length turns out to be the most critical design variable. In the chosen design case of requirements $Q=2000m^2/min$, ${\Delta}P_s=67mmAq$, D=1.4m, the chord length of 0.2059m minimizes the overall noise level, while chord length of 0.1254m maximizes the efficiency. The resulting chord length in the balanced optimization is 0.1809m.

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