• Title/Summary/Keyword: Standard least square method

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Development of Rating Curves Using a Maximum Likelihood Model (최우도 모형을 이용한 수위-유량곡선식 개발)

  • Kim, Gyeong-Hoon;Park, Jun-Il;Shin, Chan-Ki
    • Journal of environmental and Sanitary engineering
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    • v.23 no.4
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    • pp.83-93
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    • 2008
  • The non-linear least squares model(NLSM) has long been the standard technique used by hydrologists for constructing rating curves. The reasons for its adaptation are vague, and its appropriateness as a method of describing discharge measurement uncertainty has not been well investigated. It is shown in this paper that the classical method of NLSM can model only a very limited class of variance heterogeneity. Furthermore, this lack of flexibility often leads to unaccounted heteroscedasticity, resulting in dubious values for the rating curve parameters and estimated discharge. By introducing a heteroscedastic maximum likelihood model(HMLM), the variance heterogeneity is treated more generally. The maximum likelihood model stabilises the variance better than the NLSM approach, and thus is a more robust and appropriate way to fit a rating curve to a set of discharge measurements.

Characteristics of Input-Output Spaces of Fuzzy Inference Systems by Means of Membership Functions and Performance Analyses (소속 함수에 의한 퍼지 추론 시스템의 입출력 공간 특성 및 성능 분석)

  • Park, Keon-Jun;Lee, Dong-Yoon
    • The Journal of the Korea Contents Association
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    • v.11 no.4
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    • pp.74-82
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    • 2011
  • To do fuzzy modelling of a nonlinear process needs to analyze the characteristics of input-output of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods. For this, fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the fuzzy rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the clusters are used for identification of fuzzy model and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. In the consequence part of the fuzzy rules fuzzy reasoning is conducted by two types of inferences such as simplified and linear inference. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. And lastly, using gas furnace process which is widely used in nonlinear process we evaluate the performance and the system characteristics.

The analysis of optical influence on the grading tolerances and proportions for the round brilliant cut polished diamonds (Round brilliant cut으로 연마한 diamond의 등급별 허용 오차와 proportions에 관한 광학적 영향력 분석)

  • Kim, Eun-Ju
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.23 no.4
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    • pp.173-179
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    • 2013
  • Even though a rough diamond shape is irregular and rugged, it is easy to be processed to make gem, shaped facets (table, crown, pavilion and girdle) were precisely treated because they influence on the evaluation of diamond grading. Those specifications suitable for the standard round brilliant cut diamond polishing were investigated and in 95 % statistical confidence interval, standard deviation, mean and acceptable tolerance were examined. According to these variables (size, angle, depth, and thickness) distribution, the frequency analysis of ratings and proportions were compared with each other. The correlation between each variables and the evidence of influence represented in proportion were determined by the regression analysis applying LSM (Least Square Method). In this research, it was recognized that table sizes of the diamond jewels and pavilion depth (in %) influence the rating decision and in particular, the depth of pavilion acting as the main factor of proportions, also plays an important role in optical phenomena.

Meshless formulation for shear-locking free bending elements

  • Kanok-Nukulchai, W.;Barry, W.J.;Saran-Yasoontorn, K.
    • Structural Engineering and Mechanics
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    • v.11 no.2
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    • pp.123-132
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    • 2001
  • An improved version of the Element-free Galerkin method (EFGM) is presented here for addressing the problem of transverse shear locking in shear-deformable beams with a high length over thickness ratio. Based upon Timoshenko's theory of thick beams, it has been recognized that shear locking will be completely eliminated if the rotation field is constructed to match the field of slope, given by the first derivative of displacement. This criterion is applied directly to the most commonly implemented version of EFGM. However in the numerical process to integrate strain energy, the second derivative of the standard Moving Least Square (MLS) shape functions must be evaluated, thus requiring at least a $C^1$ continuity of MLS shape functions instead of $C^0$ continuity in the conventional EFGM. Yet this hindrance is overcome effortlessly by only using at least a $C^1$ weight function. One-dimensional quartic spline weight function with $C^2$ continuity is therefore adopted for this purpose. Various numerical results in this work indicate that the modified version of the EFGM does not exhibit transverse shear locking, reduces stress oscillations, produces fast convergence, and provides a surprisingly high degree of accuracy even with coarse domain discretizations.

Determination of Total Volatile Bases of Tobacco Using Near Infrared Spectroscopy (근외적 분광분석법을 이용한 담배 중 전휘발성염기 분석)

  • Kim Yong-Ok;Jang Gi-Chul;Lee Chul-Hee;Chung Han-Joo
    • Journal of the Korean Society of Tobacco Science
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    • v.27 no.2
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    • pp.207-211
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    • 2005
  • This study was carried out to develop calibration equation of total volatile bases of tobacco leaf using near infrared spectroscopy(NIRS). Burley, imported flue-cured and oriental leaf tobacco samples were collected in 2005 crop year. Calibration equation was developed by modified partial least square method. The standard error of calibration and $R^2$ between traditional analytical method and NIRS analytical method were $0.038\%$, 0.983 for burley and $0.027\%$, 0.986 for imported flue-cured and oriental leaf, respectively. The standard error of performance and $R^2$ between traditional analytical method and NIRS analytical method were $0.048\%$, 0.940 for burley and $0.024\%$, 0.986 for imported flue-cured and oriental leaf, respectively. From these results, the NIRS analytical method seems to be applicable in analyzing total volatile bases of tobacco.

Determination of Precise Regional Geoid Heights on and around Mount Jiri, South Korea

  • Lee, Suk-Bae
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.1
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    • pp.9-15
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    • 2018
  • Precise regional geoid heights on and around Mount Jiri were calculated and were compared to the KNGeoid14 (Korean National Geoid 2014) model. In this study, gravimetric geoid heights were calculated by using RCR (Remove-Compute-Restore) technique and then hybrid geoid heights were calculated by using the LSC (Least Square Collocation) method in the same area. In addition, gravity observation and GNSS(Global Navigation Satellite System) surveying performed in this study were utilized to determine gravimetric geoid heights and to compute hybrid geoid heights, respectively. The results of the study show that the post-fit error (mean and standard deviation) of hybrid geoid heights was evaluated as $0.057{\pm}0.020m$, while the mean and standard deviation of the differences were -0.078 and 0.085 m, respectively for KNGeoid14. Therefore, hybrid geoid heights in this study show more considerable progress than KNGeoid14.

The Combined Method of Structure Selection and Parameter Identification of Equations of Motion to Analyze the Model Tests of a Submerged Body (몰수체 모형 시험 해석을 위한 운동방정식의 구조 선택 및 계수 식별 결합법)

  • C.K. Kim
    • Journal of the Society of Naval Architects of Korea
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    • v.35 no.2
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    • pp.20-28
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    • 1998
  • To accurately predict the motion of a submergible, the nonlinear structure of dynamic model should be selected and corresponding parameters should be estimated using model test. Providing the model structure, only the values of parameters are unknown and the estimation can thus be formulated as a standard least square problem. Unfortunately, the nonlinear model structure of submersibles is rarely known a prior and method of model structure determination from measurement data of model test should be developed and included as a vital part of the estimation procedure. In this study, the well-known linear least square algorithm for the analysis of model tests and a way to measure the goodness are reviewed, and the identification algorithm based on an orthogonal decomposition method of Gram-Schmidt is extended to combine structure selection and maneuvering coefficients estimation in a very simple and efficient manner. Finally, the efficiency of this algorithm is verified by using simulation and applying to the analysis of model test of a submerged body. As a result, it was verified that this combined method might be very erective in selecting the structure of dynamic model estimating the maneuvering coefficients from measurement fiat of model test.

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Multiple Microphone Technique for a Direct Measurement of In-duct Acoustical Parameters (다수의 마이크를 이용한 관내 음향 변수의 직접 측정법)

  • Jang, Seung-Ho;Ih, Jeong-Guon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2000.06a
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    • pp.1661-1666
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    • 2000
  • Nowadays, the two microphone method is accepted as the standard as specified in ASTM E1050-90 for measuring in-duct acoustic properties. However, research results on using the least square method with multiple measurement points and broadband excitation have been reported for enhancing the frequency response of the two microphone method. In this paper, the effects of varying the relative measurement positions on errors in the estimation of the acoustic quantities is studied for the multiple microphone method. Both of the theoretical and experimental results show that, among every possible sensor positioning configurations, the equidistant positioning of sensors yields the smallest error within the effective measurement frequency range. In addition, it is noted that the measurement accuracy can be increased and the effective frequency range can be widened by increasing the number of equidistant sensors. Measurement examples are shown and the results support the findings.

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The Identification of Multi-Fuzzy Model by means of HCM and Genetic Algorithms (클러스터링 기법과 유전자 알고리즘에 의한 다중 퍼지 모델으 동정)

  • Park, Byoun-Jun;Lee, Su-Gu;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.3007-3009
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    • 2000
  • In this paper, we design a Multi-Fuzzy model by means of clustering method and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model. HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

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Nondestructive Prediction of Fatty Acid Composition in Sesame Seeds by Near Infrared Reflectance Spectroscopy

  • Kim, Kwan-Su;Park, Si-Hyung;Choung, Myoung-Gun;Kim, Sun-Lim
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.51 no.spc1
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    • pp.304-309
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    • 2006
  • Near infrared reflectance spectroscopy (NIRS) was used to develop a rapid and nondestructive method for the determination of fatty acid composition in sesame (Sesamum indicum L.) seed oil. A total of ninety-three samples of intact seeds were scanned in the reflectance mode of a scanning monochromator, and reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations were developed using modified partial least square regression with internal cross validation (n=63). The equations obtained had low standard errors of cross-validation and moderate $R^2$ (coefficient of determination in calibration). Prediction of an external validation set (n=30) showed significant correlation between reference values and NIRS estimated values based on the SEP (standard error of prediction), $r^2$ (coefficient of determination in prediction) and the ratio of standard deviation (SD) of reference data to SEP. The models developed in this study had relatively higher values (more than 2.0) of SD/SEP(C) for oleic and linoleic acid, having good correlation between reference and NIRS estimate. The results indicated that NIRS, a nondestructive screening method could be used to rapidly determine fatty acid composition in sesame seeds in the breeding programs for high quality sesame oil.