• Title/Summary/Keyword: weighted average

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The Effects of DEM Resolution on Hydrological Simulation in BASINS-HSPF Modeling

  • Jeon, Ji-Hong;Yoon, Chun-Gyung
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2002.10a
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    • pp.453-456
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    • 2002
  • In this study, the effect of DEM resolution (15m, 30m, 50m, 70m, 100m, 200m, 300m) on the hydrological simulation was examined using BASINS (Better Assessment Science Integrating point and Nonpoint Source) for Heukcheon watershed (303.3km2) data from 1998 to 1999. Generally, as the cell size of DEM increased, topographical changes were observed as the original range of elevation decreased. The processing time of watershed delineation and river network needed more time and effort on smaller cell size of DEM. The larger DEM demonstrated had some errors in the junction of river network which might effects on the simulation of water quantity and quality. The area weighted average watershed slope became lower but the length weighted average channel slope became higher as the DEM size increased. DEM resolution affected substantially on the topographical parameter but less on the hydrological simulation. Considering processing time and accuracy on hydrological simulation DEM mesh size of 100m is recommended for this watershed.

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A threshold-asymmetric realized volatility for high frequency financial time series (비대칭형 분계점 실현변동성의 제안 및 응용)

  • Kim, J.Y.;Hwang, S.Y.
    • The Korean Journal of Applied Statistics
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    • v.31 no.2
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    • pp.205-216
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    • 2018
  • This paper is concerned with volatility computations for high frequency time series. A threshold-asymmetric realized volatility (T-RV) is suggested to capture a leverage effect. The T-RV is compared with various conventional volatility computations including standard realized volatility, GARCH-type volatilities, historical volatility and exponentially weighted moving average volatility. High frequency KOSPI data are analyzed for illustration.

Evaluation of Surrogate Models for Shape Optimization of Compressor Blades

  • Samad, Abdus;Kim, Kwang-Yong
    • 유체기계공업학회:학술대회논문집
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    • 2006.08a
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    • pp.367-370
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    • 2006
  • Performances of multiple surrogate models are evaluated in a turbomachinery blade shape optimization. The basic models, i.e., Response Surface Approximation, Kriging and Radial Basis Neural Network models as well as weighted average models are tested for shape optimization. Global data based errors for each surrogates are used to calculate the weights. These weights are multiplied with the respective surrogates to get the final weighted average models. The design points are selected using three level fractional factorial D-optimal designs. The present approach can help address the multi-objective design on a rational basis with quantifiable cost-benefit analysis.

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SPC 기법에 의한 밀링공구의 파손분석 및 검색

  • 서석환;전치혁;최용종
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1992.10a
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    • pp.47-51
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    • 1992
  • Automatic detection of tool breakage during NC machining is a key issue not only for improving productivity but to implement the unattended manufacturing system. In this paper, we develop a vibration sensor-based tool breakage detection system for NC milling processes. The system obtains the time-domain vibration signal from the sensor attached on the spindle bracket of our CNC machine and declares tool failures through the on-line monitoring schemes. For on-line detection, our approach is to use the PSC(statistical process control) methods being increasingly used for on-line process control. The main thrust of this paper is to propose and compare the performance of SPC methods including : a) X-bar control scheme, b) S control scheme, c)EWMA (exponentially weighted moving average) scheme, and d) AEWMA (adaptive exponentially weighted moving average) scheme. The performance of the control schemes are compared in terms of the type 1 and 2 error calculated from the experiment data.

Face Recognition Using PCA and Fuzzy Weighted Average Method (PCA와 퍼지 가중치 평균 기법을 이용한 얼굴 인식)

  • Woo, Young-Woon;Kim, Hyung-Soo;Park, Jae-Min;Cho, Jae-Hyun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2011.01a
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    • pp.315-316
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    • 2011
  • 일반적으로 영상에서 얼굴 영상을 검출하고 인식하는 알고리즘은 패턴 인식 연구에 있어서 인간과 컴퓨터의 상호작용의 연구라는 면에서 아주 중요한 문제로 연구되어 왔다. 본 논문에서는 고유얼굴을 이용하여 유클리디언 거리법과 퍼지기법의 인식률을 비교해보고자 한다. PCA(Principal Component Analysis) 방식은 우수한 인식 결과를 보장하는 얼굴인식 기법중의 하나이며, 얼굴 영상을 이용하여 공분산 행렬을 계산하고, 공분산 행렬을 통해 생성된 저차원의 벡터, 즉 고유얼굴(Eigenface)을 이용하여 가중치를 계산하고, 이 가중치를 기준으로 인식을 수행하는 기법이다. 이를 기반으로 하여, 본 논문에서는 전처리 과정, 고유얼굴 과정, 유클리디언 거리법 및 퍼지 소속도 함수 설계 과정, 신경망 학습과정, 인식과정으로 구성된 5단계의 얼굴 인식 알고리즘을 제안한다.

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[ $\overline{X}$ ] Chart with Geometrically Adjusted Control Limits under Continually Improving Processes (지속적으로 향상되는 공정에서 기하 조정 관리한계를 사용한 $\overline{X}$ 관리도)

  • Ryu, Mi-Jung;Park, Chang-Soon
    • Journal of Korean Society for Quality Management
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    • v.34 no.4
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    • pp.125-132
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    • 2006
  • An adjusted control limit of the $\overline{X}$ chart is proposed for monitoring the continually improving processes. The continual improvement of the process implies the decrease of the process variance, which is represented by a logistic curve. The process standard deviation is estimated by the exponentially weighted moving average of the sample standard deviations from the past to the current times. The control limits are adjusted by the estimated standard deviation at every sampling time. The performance of the adjusted control limit is compared with that of the standard control limits for various cases of the decreasing speed and size of the variance. The results show that the $\overline{X}$ chart with the adjusted control limits provides better performances for monitoring the small and moderate shifts in continually improving processes.

Channel Estimation Based on the Weighted Moving Average in T-DMB Receivers (T-DMB 수신기에서 가중이동평균을 기반으로 한 채널추정)

  • Park, Sung-Ik;Lee, Jae-Yong;Lim, Hyoung-Soo;Kim, Hyoung-Nam;Kim, Heung-Mook;Lee, Jong-Soo
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2006.11a
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    • pp.153-156
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    • 2006
  • 본 논문에서는 T-DMB 수신기의 채널추정 성능향상을 위한 잡음감소 기법을 제안한다. 일반적으로 T-DMB 수신기에서의 채널추정은 파일럿 신호 추출과 채널계수 추정에 의해 수행된다. 채널추정의 성능은 수신 SNR (Signal to Noise Ratio)과 연관되어 추정된 채널계수에 남아있는 잡음성분에 의해 결정되기 때문에, 잔존하는 잡음성분을 감소시키는 것은 매우 중요하다. 이러한 잡음성분을 감소시키기 위해, M-point 가중이동평균(weighted moving average)을 기반으로 한 잡음제거 기법을 제안한다. 전산 실험에 의하면, 제안된 방법은 등화 후 SER (Symbol Error Rate) 측면에서 기존의 방법에 비해 2-3 dB의 성능 향상을 보인다.

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Optimization of Vane Diffuser in a Mixed-Flow Pump for High Efficiency Design

  • Kim, Jin-Hyuk;Kim, Kwang-Yong
    • International Journal of Fluid Machinery and Systems
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    • v.4 no.1
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    • pp.172-178
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    • 2011
  • This paper presents an optimization procedure for high-efficiency design of a mixed-flow pump. Optimization techniques based on a weighted-average surrogate model are used to optimize a vane diffuser of a mixed-flow pump. Validation of the numerical results is performed through experimental data for head, power and efficiency. Three-level full factorial design is used to generate nine design points within the design space. Three-dimensional Reynoldsaveraged Navier-Stokes equations with the shear stress transport turbulence model are discretized by using finite volume approximation and solved on hexahedral grids to evaluate the efficiency as the objective function. In order to reduce pressure loss in the vane diffuser, two variables defining the straight vane length ratio and the diffusion area ratio are selected as design variables in the present optimization. As the results of the design optimization, the efficiency at the design flow coefficient is improved by 7.05% and the off-design efficiencies are also improved in comparison with the reference design.

A study on the improvement of fuzzy ARTMAP for pattern recognition problems (Fuzzy ARTMAP 신경회로망의 패턴 인식율 개선에 관한 연구)

  • 이재설;전종로;이충웅
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.9
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    • pp.117-123
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    • 1996
  • In this paper, we present a new learning method for the fuzzy ARTMAP which is effective for the noisy input patterns. Conventional fuzzy ARTMAP employs only fuzzy AND operation between input vector and weight vector in learning both top-down and bottom-up weight vectors. This fuzzy AND operation causes excessive update of the weight vector in the noisy input environment. As a result, the number of spurious categories are increased and the recognition ratio is reduced. To solve these problems, we propose a new method in updating the weight vectors: the top-down weight vectors of the fuzzy ART system are updated using weighted average of the input vector and the weight vector itself, and the bottom-up weight vectors are updated using fuzzy AND operation between the updated top-down weitht vector and bottom-up weight vector itself. The weighted average prevents the excessive update of the weight vectors and the fuzzy AND operation renders the learning fast and stble. Simulation results show that the proposed method reduces the generation of spurious categories and increases the recognition ratio in the noisy input environment.

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Multisensor Data Combination Using Fuzzy Weighted Average (퍼지 가중 평균을 이용한 다중 센서 데이타 융합)

  • Kim, Wan-Joo;Ko, Joong-Hyup;Chung, Myung-Jin
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.383-386
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    • 1993
  • In this paper, we propose a sensory data combination method by a fuzzy number approach for multisensor data fusion. Generally, the weighting of one sensory data with respect to another is derived from measures of the relative reliabilities of the two sensory modules. But the relative weight of two sensory data can be approximately determined through human experiences or insufficient experimental data without difficulty. We represent these relative weight using appropriate fuzzy numbers as well as sensory data itself. Using the relative weight, which is subjective valuation, and a fuzzy-numbered sensor data, the fuzzy weighted average method is used for a representative sensory data. The manipulation and calculation of fuzzy numbers can be carried out using the Zadeh's extension principle which can be approximately implemented by the $\alpha$-cut representation of fuzzy numbers and interval analysis.

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