• Title/Summary/Keyword: weighted function

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Evaluation of Probability Precipitation using Climatic Indices in Korea (기상인자를 이용한 우리나라의 확률강수량 평가)

  • Oh, Tae-Suk;Moon, Young-Il
    • Journal of Korea Water Resources Association
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    • v.42 no.9
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    • pp.681-690
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    • 2009
  • In this research, design precipitation was calculated by reflecting the climatic indices and its uncertainty assessment was evaluated. Climatic indices used the sea surface temperature and moisture index which observed globally. The correlation coefficients were calculated between the annual maximum precipitation and the climatic indices. and then climatic indices which have the larger correlation coefficient were selected. Therefore, the regression relationship was established by a locally weighted polynomial regression. Next, climatic indices were generated by montecarlo simulation using kernel function. Finally, the design rainfall was calculated by the locally weighted polynomial regression using generated climatic indices. At the result, the comparison of design rainfall between the reflection of the climatic indices and the frequency analysis did not indicate a significant difference. Also, this result can be used as basic data for calculation of probability precipitation to reflect climate change.

Feature Selection and Classification of Protein CDS Using n-Block substring weighted Linear Model (N-Block substring 가중 선형모형을 이용한 단백질 CDS의 특징 추출 및 분류)

  • Choi, Seong-Yong;Kim, Jin-Su;Han, Seung-Jin;Choi, Jun-Hyeog;Rim, Kee-Wook;Lee, Jung-Hyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.5
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    • pp.730-736
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    • 2009
  • It is more important to analysis of huge gemonics data in Bioinformatics. Here we present a novel datamining approach to predict structure and function using protein's primnary structure only. We propose not also to develope n-Block substring search algorithm in reducing enormous search space effectively in relation to feature selection, but to formulate weighted linear algorithm in a prediction of structure and function of a protein using primary structure. And we show efficient in protein domain characterization and classification by calculation weight value in determining domain association in each selected substring, and also reveal that more efficient results are acquired through claculated model score result in an inference about degree of association with each CDS(coding sequence) in domain.

DEVELOPMENT OF A NUMERICAL SIMULATION METHOD FOR THE ANALYSIS OF SLOSHING PROBLEMS BASED ON CCUP SCHEME (슬로싱 해석을 위한 CCUP 기반 시뮬레이션 기술 개발)

  • Park, J.C.;Hwang, S.C.;Jeong, S.M.
    • Journal of computational fluids engineering
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    • v.16 no.2
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    • pp.1-10
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    • 2011
  • A new computational program, which is based on the CIP/CCUP(Constraint Interpolation Profile/CIP Combined Unified Procedure) method, has been developed to numerically analyse sloshing phenomena dealt as multiphase-flow problems. For the convection terms of Navier-Stokes equations, the RCIP(Rational function CIP) method was adopted and the THINC-WLIC(Tangent of Hyperbola for Interface Capturing-Weighted Line Interface Calculation) method was used to capture the air/water interface. To validate the present numerical method, two-dimensional dam-breaking and sloshing problems in a rectangular tank were solved by the developed method in a stationary Cartesian grid system. In the case of sloshing problems, simulations by using a improved MPS(Moving Particle Simulation) method, which is named as PNU-MPS(Pusan National University-MPS), were also carried out. The computational results are compared with those of experiments and most of the comparisons are reasonably good.

Comparative Analysis of Learning Methods of Fuzzy Clustering-based Neural Network Pattern Classifier (퍼지 클러스터링기반 신경회로망 패턴 분류기의 학습 방법 비교 분석)

  • Kim, Eun-Hu;Oh, Sung-Kwun;Kim, Hyun-Ki
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.9
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    • pp.1541-1550
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    • 2016
  • In this paper, we introduce a novel learning methodology of fuzzy clustering-based neural network pattern classifier. Fuzzy clustering-based neural network pattern classifier depicts the patterns of given classes using fuzzy rules and categorizes the patterns on unseen data through fuzzy rules. Least squares estimator(LSE) or weighted least squares estimator(WLSE) is typically used in order to estimate the coefficients of polynomial function, but this study proposes a novel coefficient estimate method which includes advantages of the existing methods. The premise part of fuzzy rule depicts input space as "If" clause of fuzzy rule through fuzzy c-means(FCM) clustering, while the consequent part of fuzzy rule denotes output space through polynomial function such as linear, quadratic and their coefficients are estimated by the proposed local least squares estimator(LLSE)-based learning. In order to evaluate the performance of the proposed pattern classifier, the variety of machine learning data sets are exploited in experiments and through the comparative analysis of performance, it provides that the proposed LLSE-based learning method is preferable when compared with the other learning methods conventionally used in previous literature.

Weighted zero-inflated Poisson mixed model with an application to Medicaid utilization data

  • Lee, Sang Mee;Karrison, Theodore;Nocon, Robert S.;Huang, Elbert
    • Communications for Statistical Applications and Methods
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    • v.25 no.2
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    • pp.173-184
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    • 2018
  • In medical or public health research, it is common to encounter clustered or longitudinal count data that exhibit excess zeros. For example, health care utilization data often have a multi-modal distribution with excess zeroes as well as a multilevel structure where patients are nested within physicians and hospitals. To analyze this type of data, zero-inflated count models with mixed effects have been developed where a count response variable is assumed to be distributed as a mixture of a Poisson or negative binomial and a distribution with a point mass of zeros that include random effects. However, no study has considered a situation where data are also censored due to the finite nature of the observation period or follow-up. In this paper, we present a weighted version of zero-inflated Poisson model with random effects accounting for variable individual follow-up times. We suggested two different types of weight function. The performance of the proposed model is evaluated and compared to a standard zero-inflated mixed model through simulation studies. This approach is then applied to Medicaid data analysis.

Design of Robust Load Frequency Controller using Mixed Sensitivity based $H_{\infty}$ norm (혼합강도 $H_{\infty}$ 제어기법을 이용한 강인한 부하주파수 제어기 설계)

  • 정형환;김상효;이정필;한길만
    • Journal of Advanced Marine Engineering and Technology
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    • v.24 no.3
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    • pp.88-98
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    • 2000
  • In this paper, a robust controller using $H_{\infty}$ control theory has been designed for the load frequency control of interconnected 2-area power system. The main advantage of the proposed $H_{\infty}$ controller is that uncertainties of power system can be included at the stage of controller design. Representation of uncertainties is modeled by multiplicative uncertainly. In the mixed sensitivity problems, disturbance attenuation and uncertainty of the system is treated simultaneously. The robust stability and the performance of model uncertainties are represented by frequency weighted transfer function. The design of load frequency controller for each area was based on state-space approach. The comparative computer simulation results for the proposed controller and the conventional techniques such as the optimal control and the PID one were analyzed at the additions of various disturbances. Their deviation magnitude of frequency and tie line power flow at each area were mainly evaluated. Also the testing results of robustness for the cases that the perturbations of the all parameters of power system were amounted to about 20% were introduced. It was approved that the resultant performances of the proposed $H_{\infty}$ controller with mixed sensitivity were more robust and stable than the one of conventional controllers.

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Speaker Verification Performance Improvement Using Weighted Residual Cepstrum (가중된 예측 오차 파라미터를 사용한 화자 확인 성능 개선)

  • 위진우;강철호
    • The Journal of the Acoustical Society of Korea
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    • v.20 no.5
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    • pp.48-53
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    • 2001
  • In speaker verification based on LPC analysis the prediction residues are ignored and LPCC(LPC cepstrum) are only used to compose feature vectors. In this study, LPCC and RCEP (residual cepstrum) extracted from residues are used as feature parameters in the various environmental speaker verification. We propose the weighting function which can enlarge inter-speaker variation by weighting pitch, speaker inherent vector, included in residual cepstrum. Simulation results show that the average speaker verification rate is improved in the rate of 6% with RCEP and LPCC at the same time and is improved in the rate of 2.45% with the proposed weighted RCEP and LPCC at the same time compared with no weighting.

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Overlap and Add Sinusoidal Synthesis Method of Speech Signal using Amplitude-weighted Phase Error Function (정현파 크기로 가중치 된 위상 오류 함수를 사용한 음성의 중첩합산 정현파 합성 방법)

  • Park, Jong-Bae;Kim, Gyu-Jin;Hyeok, Jeong-Gyu;Kim, Jong-Hark;Lee, In-Sung
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.12C
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    • pp.1149-1155
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    • 2007
  • In this paper, we propose a new overlap and add speech synthesis method which demonstrates improved continuity performance. The proposed method uses a weighted phase error function and minimizes the wave discontinuity of the synthesis signal, rather than the phase discontinuity, to estimate the mid-point phase. Experimental results show that the proposed method improves the continuity between the synthesized signals relative to the existing method.

Multiple Attribute Group Decision Making Problems Based on Fuzzy Number Intuitionistic Fuzzy Information

  • Park, Jin-Han;Kwun, Young-Chel;Park, Jong-Seo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.2
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    • pp.265-272
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    • 2009
  • Fuzzy number intuitionistic fuzzy sets (FNIFSs), each of which is characterized by a membership function and a non-membership function whose values are trigonometric fuzzy number rather than exact numbers, are a very useful means to describe the decision information in the process of decision making. Wang [10] developed some arithmetic aggregation operators, such as the fuzzy number intuitionistic fuzzy weighted averaging (FIFWA) operator, the fuzzy number intuitionistic fuzzy ordered weighted averaging (FIFOWA) operator and the fuzzy number intuitionistic fuzzy hybrid aggregation (FIFHA) operator. In this paper, based on the FIFHA operator and the FIFWA operator, we investigate the group decision making problems in which all the information provided by the decision-makers is presented as fuzzy number intuitionistic fuzzy decision matrices where each of the elements is characterized by fuzzy number intuitionistic fuzzy numbers, and the information about attribute weights is partially known. An example is used to illustrate the applicability of the proposed approach.

A Simple Human Visual Weighted Hadamard Transform Image Coding (단순한 시각적 하중에 의한 아다마르 영상부호화)

  • Hwang, Jae-Jeong;Lee, Moon-Ho
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.4
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    • pp.98-105
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    • 1989
  • Various models incorporating Human Visual System (HVS) with the Hadamard transform (HT) represented by Walsh functions are considered. Using the exact frequency components of HT basis functions, the optimum modulation transfer function (MTF) which has a higher peak frequency than DCT schemes is obtimum modulation transfer function (MTF) which has a higher peak frequency than DCT schemes is obtained analytically and visually. The main criterion, for error measurement, is errors at the block boundaries which is an important factor in transform coding. The scheme which has no inverse HVS is proposed. It causes some degradation of image data but it is insignigicant. Crossing area of 4 blocks is equalized by the HVS weighting coefficients. The HVS weighted coding results in perceptually higher quality images compared with the unweighted scheme.

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