• 제목/요약/키워드: Validation Set

검색결과 679건 처리시간 0.024초

순차적으로 선택된 특성과 유전 프로그래밍을 이용한 결정나무 (A Decision Tree Induction using Genetic Programming with Sequentially Selected Features)

  • 김효중;박종선
    • 경영과학
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    • 제23권1호
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    • pp.63-74
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    • 2006
  • Decision tree induction algorithm is one of the most widely used methods in classification problems. However, they could be trapped into a local minimum and have no reasonable means to escape from it if tree algorithm uses top-down search algorithm. Further, if irrelevant or redundant features are included in the data set, tree algorithms produces trees that are less accurate than those from the data set with only relevant features. We propose a hybrid algorithm to generate decision tree that uses genetic programming with sequentially selected features. Correlation-based Feature Selection (CFS) method is adopted to find relevant features which are fed to genetic programming sequentially to find optimal trees at each iteration. The new proposed algorithm produce simpler and more understandable decision trees as compared with other decision trees and it is also effective in producing similar or better trees with relatively smaller set of features in the view of cross-validation accuracy.

Airline In-flight Meal Demand Forecasting with Neural Networks and Time Series Models

  • Lee, Young-Chan
    • 한국정보시스템학회:학술대회논문집
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    • 한국정보시스템학회 2000년도 추계학술대회
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    • pp.36-44
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    • 2000
  • The purpose of this study is to introduce a more efficient forecasting technique, which could help result the reduction of cost in removing the waste of airline in-flight meals. We will use a neural network approach known to many researchers as the “Outstanding Forecasting Technique”. We employed a multi-layer perceptron neural network using a backpropagation algorithm. We also suggested using other related information to improve the forecasting performances of neural networks. We divided the data into three sets, which are training data set, cross validation data set, and test data set. Time lag variables are still employed in our model according to the general view of time series forecasting. We measured the accuracy of our model by “Mean Square Error”(MSE). The suggested model proved most excellent in serving economy class in-flight meals. Forecasting the exact amount of meals needed for each airline could reduce the waste of meals and therefore, lead to the reduction of cost. Better yet, it could enhance the cost competition of each airline, keep the schedules on time, and lead to better service.

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심전도 자동 진단을 위한 기저선 동요 평가 및 제거에 관한 연구 (A study of estimation and removal of baseline drift for the automated diagnosis of electrocardiogram)

  • 권혁제;이명호
    • 전자공학회논문지B
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    • 제33B권7호
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    • pp.99-106
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    • 1996
  • Estimation and removal procedures for baseline drift have been developed using linear, cubic spline, and bilineared transformed high pass filter. Linear and cubic spline interpolation with the PQ and TP segmens, which are considered to be isoelectric, as fiducial points ahve been estimated respectively. For a quantitative validation of the estimation procedure, 4 ECGs with arfificial baseline drift were constructed and analyzed by mean square error calculations and amplitude histograms. Also real ECGs were analyzed in a test set of the CSE data set 3 and set 4. Baseline drift detecton rule were designed and new method for the decision of fiducial point were constructed to avoid distorting as the case of premature ventricular or atrial contraction. From these comparison, proposed cubic spline method with PQ and TP segment (CS_PQ & TP) emerged as the most efficient method.

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Teenagers Consumption Within the Moderating Role of Saudis Habit Through Fuzzy Set Approach

  • Maher Toukabri
    • International Journal of Computer Science & Network Security
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    • 제24권3호
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    • pp.173-181
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    • 2024
  • The healthy products dedicated for young people are qualified as a solution to protect the future generation, especially that most commercial deals do not consider the consumer's health and environment. Therefore, it is crucial to define the antecedent of healthy purchases and to examine their impact on teenagers. This research aims to explore the antecedents and the consequences of the consumption of Saudis teenagers. Therefore, we develop a research model in the conceptual framework and the hypotheses to test. The empirical analysis required two samples from Saudis youth consumers. The first sample was utilized in the exploratory study with SPSS software. Then, the second was employed to the confirmatory part with the Amos software, as well as the validation of the hypotheses, and model with Fuzzy Set approach. The findings of this study have significant insights into the Saudi consumption and implications for both practitioners and researchers. Then, we have particularly strenuous on intention purchase antecedents of organic foods, and their consume habit moderation.

신용평가모형에서 두 분포함수의 동일성 검정을 위한 비모수적인 검정방법 (Nonparametric homogeneity tests of two distributions for credit rating model validation)

  • 홍종선;김지훈
    • Journal of the Korean Data and Information Science Society
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    • 제20권2호
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    • pp.261-272
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    • 2009
  • 신용평가모형에서 두 집단의 판별력 검정방법 중의 하나로 두 분포함수의 동일성 검정을 위한 비모수적인 Kolmogorov-Smirnov (K-S) 검정방법이 대표적으로 적용되고 있다. 본 연구에서는 신용평가모형에서 두 분포함수의 동일성 검정을 위하여 K-S 검정 방법 외에 Cramer-Von Mises, Anderson-Darling, Watson 검정방법들을 소개하고 Joseph (2005)의 기준에 대응하는 판단기준을 제안한다. 또한 신용평가 자료와 유사한 상황 하에서의 모의실험을 통해서 불량률, 표본크기 그리고 제II종 오류율을 고려한 대안적인 판단기준을 제시하고 그 적용방법에 대해서 살펴본다.

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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
    • 한국작물학회지
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    • 제51권spc1호
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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.

국제 통신 표준 언어를 이용한 통신 프로토콜 설계 및 검증 방법론 연구 (A Study on the Design and Validation Methodology of Communication Protocols Using International Communication Standard Languages)

  • 노철우
    • 컴퓨터교육학회논문지
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    • 제5권4호
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    • pp.31-42
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    • 2002
  • 본 논문에서는 통신 프로토콜 개발 시 사용되는 PDU, SDU, SAP, 서비스 프리미티브를 어떻게 정의하고 사용하는지에 대한 명확한 설계 개념과 검증 방법을 ITU에서 통신 규격 및 설계 언어로 권고하고 있는 SDL과 국제 통신 표준 언어인 ASN.1, MSC, TTCN을 사용하여 정립한다. 통신 프로토콜의 예로 잘 알려진 Inres 프로토콜을 확장하여 SDL로 설계하며, SDL의 설계 규격에 비트 스트링 전송을 위한 ASN.1 메시지의 삽입, 규격에 대한 설계 검증을 위한 MSC의 생성, 검증으로부터 TTCN을 이용한 시험 케이스의 생성 및 적합성 시험 등 프로토콜 개발 순기 전반에 걸친 개발 방법론을 정립한다.

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A Comparative Study on Arrhenius-Type Constitutive Models with Regression Methods

  • Lee, Kyunghoon;Murugesan, Mohanraj;Lee, Seung-Min;Kang, Beom-Soo
    • 소성∙가공
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    • 제26권1호
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    • pp.18-27
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    • 2017
  • A comparative study was performed on strain-compensated Arrhenius-type constitutive models established with two regression methods: polynomial regression and regression Kriging. For measurements at high temperatures, experimental data of 70Cr3Mo steel were adopted from previous research. An Arrhenius-type constitutive model necessitates strain compensation for material constants to account for strain effect. To associate the material constants with strain, we first evaluated them at a set of discrete strains, then capitalized on surrogate modeling to represent the material constants as a function of strain. As a result, disparate flow stress models were formed via the two different regression methods. The constructed constitutive models were examined systematically against measured flow stresses by validation methods. The predicted material constants were found to be quite accurate compared to the actual material constants. However, notable mismatches between measured and predicted flow stresses were revealed by the proposed validation techniques, which carry out validation with not the entire, but a single tensile test case.

Studies on 5 Protein Fractions Prediction of Forage Legume Mixture by NIRS

  • Lee, Hyo-Won;Jang, Sungkwon;Lee, Hyo-Jin;Park, Hyung-Soo
    • 한국초지조사료학회지
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    • 제34권3호
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    • pp.214-218
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    • 2014
  • This study was conducted to assess the feasibility of near-infrared reflectance spectroscopy (NIRS) as a rapid and reliable method for the estimation of crude protein (CP) fractions in forage legume mixtures (sudangrass and pea mixture, and kidney bean and potato mixture). A total of 178 samples were collected and their spectral reflectance obtained in the range of 400~2,500 nm. Of these, 50 samples were selected for calibration and validation, and 35 samples were used for calibration of the data set, and the modified partial least square regression (MPLSR) analysis was performed. The correlation coefficient ($r^2$) and the standard error of cross-validation (SECV) of the calibration models in the CP fractions, A, B1, B2, B3, and C, were 0.94 (1.05), 0.92 (0.74), 0.96 (0.95), 0.91 (0.42), and 0.83 (0.38), respectively. Fifteen samples were used for equation validation, and the $r^2$ and the standard error of prediction (SEP) were 0.87 (1.45), 0.91 (0.49), 0.94 (1.13), 0.36 (0.96), and 0.74 (0.67), respectively. This study showed that NIRS could be an effective tool for the rapid and precise estimation of CP fractions in forage legume mixtures.

Validation of a non-linear hinge model for tensile behavior of UHPFRC using a Finite Element Model

  • Mezquida-Alcaraz, Eduardo J.;Navarro-Gregori, Juan;Lopez, Juan Angel;Serna-Ros, Pedro
    • Computers and Concrete
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    • 제23권1호
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    • pp.11-23
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    • 2019
  • Nowadays, the characterization of Ultra-High Performance Fiber-Reinforced Concrete (UHPFRC) tensile behavior still remains a challenge for researchers. For this purpose, a simplified closed-form non-linear hinge model based on the Third Point Bending Test (ThirdPBT) was developed by the authors. This model has been used as the basis of a simplified inverse analysis methodology to derive the tensile material properties from load-deflection response obtained from ThirdPBT experimental tests. In this paper, a non-linear finite element model (FEM) is presented with the objective of validate the closed-form non-linear hinge model. The state determination of the closed-form model is straightforward, which facilitates further inverse analysis methodologies to derive the tensile properties of UHPFRC. The accuracy of the closed-form non-linear hinge model is validated by a robust non-linear FEM analysis and a set of 15 Third-Point Bending tests with variable depths and a constant slenderness ratio of 4.5. The numerical validation shows excellent results in terms of load-deflection response, bending curvatures and average longitudinal strains when resorting to the discrete crack approach.