• Title/Summary/Keyword: probability experiment

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A study on the ordering of PIM family similarity measures without marginal probability (주변 확률을 고려하지 않는 확률적 흥미도 측도 계열 유사성 측도의 서열화)

  • Park, Hee Chang
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.2
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    • pp.367-376
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    • 2015
  • Today, big data has become a hot keyword in that big data may be defined as collection of data sets so huge and complex that it becomes difficult to process by traditional methods. Clustering method is to identify the information in a big database by assigning a set of objects into the clusters so that the objects in the same cluster are more similar to each other clusters. The similarity measures being used in the cluster analysis may be classified into various types depending on the nature of the data. In this paper, we computed upper and lower limits for probability interestingness measure based similarity measures without marginal probability such as Yule I and II, Michael, Digby, Baulieu, and Dispersion measure. And we compared these measures by real data and simulated experiment. By Warrens (2008), Coefficients with the same quantities in the numerator and denominator, that are bounded, and are close to each other in the ordering, are likely to be more similar. Thus, results on bounds provide means of classifying various measures. Also, knowing which coefficients are similar provides insight into the stability of a given algorithm.

Evaluation of Network Reliability Using Most Probable States

  • Oh, Dae-Ho;Park, Dong-Ho;Lee, Seung-Min
    • Proceedings of the Korean Reliability Society Conference
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    • 2001.06a
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    • pp.463-469
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    • 2001
  • An algorithm is presenter for generating the most probable states in decreasing order of probability of each unit. The proposed new algorithm in this note is compared with the existing methods regarding memory requirement and execution time. Our method is simpler and, judging from the computing experiment, it requires less memory size than the previously known methods and takes comparable execution time to previous methods for an acceptable level of criterion.

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Analysis of binary data by empirical logit transformation and the type of Freeman-Tukey inverse sine transformation (경험로지트변환과 Freeman-Tukey형 역정현 변환에 의한 계수치 자료의 해석)

  • 김홍준;채규용;이상용
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.20 no.42
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    • pp.1-8
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    • 1997
  • In case of analysis of discrete data, it shows by way of example orthogonal array experiment for o, 1 data. This paper introduced expirical logit transformation and the type of Freeman-Tukey inverse sine transformation. As the result of analysis of variance, empirical logit transformation turned out a mistake in application but it is possible for graphical analysis by normal probability paper.

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Multiresponse Surfaces Optimization Based on Evidential Reasoning Theory

  • He, Zhen;Zhang, Yuxuan
    • International Journal of Quality Innovation
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    • v.5 no.1
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    • pp.43-51
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    • 2004
  • During process design or process optimization, it is quite common for experimenters to find optimum operating conditions for several responses simultaneously. The traditional multiresponse surfaces optimization methods do not consider the uncertain relationship among these responses sufficiently. For this reason, the authors propose an optimization method based on evidential reasoning theory by Dempster and Shafer. By maximizing the basic probability assignment function, which indicates the degree of belief that certain operating condition is the solution of this multiresponse surfaces optimization problem, the desirable operating condition can be found.

SELECTION PROCEDURES TO SELECT POPULATIONS BETTER THAN A CONTROL

  • Kumar, Narinder;Khamnel, H.J.
    • Journal of the Korean Statistical Society
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    • v.32 no.2
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    • pp.151-162
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    • 2003
  • In this paper, we propose two selection procedures for selecting populations better than a control population. The bestness is defined in terms of location parameter. One of the procedures is based on two-sample linear rank statistics whereas the other one is based on a comparatively simple statistic, and is useful when testing time is expensive so that an early termination of an experiment is desirable. The proposed selection procedures are seen to be strongly monotone. Performance of the proposed procedures is assessed through simulation study.

A study on the text-dependent speaker recognition system Using a robust matching process (강인한 정합과정을 이용한 텍스트 종속 화자인식에 관한 연구)

  • Lee, Han-Ku;Lee, Kee-Seong
    • Proceedings of the KIEE Conference
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    • 2002.11c
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    • pp.605-608
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    • 2002
  • A text-dependent speaker recognition system using a robust matching process is studied. The feature histogram of LPC cepstral coefficients for matching is used. The matching process uses mixture network with penalty scores. Using probability and shape comparison of two feature histograms, similarity values are obtained. The experiment results will be shown to show the effectiveness of the proposed algorithm.

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Hyperparameter Selection for APC-ECOC

  • Seok, Kyung-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1219-1231
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    • 2008
  • The main object of this paper is to develop a leave-one-out(LOO) bound of all pairwise comparison error correcting output codes (APC-ECOC). To avoid using classifiers whose corresponding target values are 0 in APC-ECOC and requiring pilot estimates we developed a bound based on mean misclassification probability(MMP). It can be used to tune kernel hyperparameters. Our empirical experiment using kernel mean squared estimate(KMSE) as the binary classifier indicates that the bound leads to good estimates of kernel hyperparameters.

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Analysis of Results and Techniques about Precipitation Enhancement by Aircraft Seeding in Korea (항공기를 이용한 인공증우(설) 기술과 결과분석)

  • Cha, Joo Wan;Jung, Wooseon;Chae, Sanghee;Ko, A-Reum;Ro, Yonghun;Chang, Ki-Ho;Seo, Seongkyu;Ha, Jong-Chul;Park, Dongoh;Hwang, Hyun Jun;Kim, Min Hoo;Kim, Kyung Eak;Ku, Jung Mo
    • Atmosphere
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    • v.29 no.4
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    • pp.481-499
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    • 2019
  • National Institute of Meteorological Sciences has conducted a total 54 cloud seeding experiments with a silver iodide and calcium chloride using aircrafts from 2008 to 2018. The goal of the experiments is to improve the techniques of precipitation enhancement in Korea. The cloud seeding experiments using the silver iodide and calcium chloride were 36 and 18 times, respectively. During the cloud seeding experiments of the silver iodide and calcium chloride, the average values of total cloud amount for two kinds of seeding materials were 9.6 for and 8.1, respectively. The cloud type with the highest occurrence was Nimbostratus (Ns)-Stratus (St) (58%) in the silver iodide cloud seeding experiment. It was Altostratus (As)-Stratocumulus (Sc) (44%) in the calcium chloride cloud seeding experiment. Compared to probability of obtaining cloud seeding effect of the experiments using a leased aircraft, the probability using an atmospheric research aircraft increased from 43% to 63% in the silver iodide cloud seeding experiment and from 29% to 75% in the calcium chloride cloud seeding experiment. However, the increasing tendency was only shown during the one year experiment (2018). To get the meaningful statistical tendency of the cloud seeding effects, it is needed to implement many experiments in several years. Further we have to more clearly understand the characteristics of clouds developing in Korea and implement the cloud seeding experiments under a variety of weather conditions in order to develop the optimized precipitation enhancement technology in Korea.

A Study on the Construction and Analysis of Fractional Designs by Using Arrays for Factorial Experiments (배열을 이용한 효과적인 일부실시법의 설계 및 분석방법에 관한 연구)

  • Kim, Sang-Ik
    • Journal of Korean Society for Quality Management
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    • v.40 no.1
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    • pp.15-24
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    • 2012
  • For the construction of fractional factorial designs, the various arrays can be widely used. In this paper we review the statistical properties of fractional designs constructed by two arrays such as orthogonal array and partially balanced array, and develop a quick and easy method for analyzing unreplicated saturated designs. The proposed method can be characterized that we control the error rate by experiment-wise way and exploit the multivariate Student $t$-distribution. Especially the proposed method can be used efficiently together with some exploratory analysis methods, such as half normal probability plot method.

An Intelligent Fire Detection Algorithm for Fire Detector

  • Hong, Sung-Ho;Choi, Moon-Su
    • International Journal of Safety
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    • v.11 no.1
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    • pp.6-10
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    • 2012
  • This paper presents a study on the analysis for reducing the number of false alarms in fire detection system. In order to intelligent algorithm fuzzy logic is adopted in developing fire detection system to reduce false alarm. The intelligent fire detection algorithm compared and analyzed the fire and non-fire signatures measured in circuits simulating flame fire and smoldering fire. The algorithm has input variables obtained by fire experiment with K-type thermocouple and optical smoke sensor. Also triangular membership function is used for inference rules. And the antecedent part of inference rules consists of temperature and smoke density, and the consequent part consists of fire probability. A fire-experiment is conducted with paper, plastic, and n-heptane to simulate actual fire situation. The results show that the intelligent fire detection algorithm suggested in this study can more effectively discriminate signatures between fire and similar fire.