• Title/Summary/Keyword: Gaussian Mixture Distribution (GMD)

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Construction of experimental data to calculate the arrival time of the rescue ship (구조선의 도착시간 산출을 위한 실험 데이터 구축)

  • Jeong, Jae-Yong;Jung, Cho-Young
    • Journal of Advanced Marine Engineering and Technology
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    • v.41 no.1
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    • pp.111-117
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    • 2017
  • The arrival time of rescue ships is very important in the event of distress. This paper presents the development of experimental data to calculate the arrival time of rescue ships. The ship's traffic probability distribution was used. Mokpo Port was selected as the area of study, and AIS data for a 1 year period were used. For the ship's traffic probability distribution, a gateline was established. The lateral range distribution was calculated and fitted to the normal distribution and two Gaussian mixture distributions (GMD2), and each parameter was extracted. After the locations of ${\mu}$, ${\mu}{\pm}1{\sigma}$ of the normal distribution and ${\mu}_1$ of the two Gaussian mixture distribution(GMD2) were set as waypoints, the location and probability were determined. A scenario was established in relation to each type of parameter. Thus, the arrival time can be calculated.

Estimation of Probability Distribution Functions for Water Temperature Data in Korean Coasts (한반도 연안 수온자료의 확률분포함수 추정)

  • Jeong, Shin Taek;Cho, Hongyeon;Ko, Dong Hui;Oh, Nam Sun;Son, Kyeong-Pyo
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.25 no.1
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    • pp.11-19
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    • 2013
  • As the temperature data show a distribution pattern with a number of peaks, assumption of normal distribution will result in a serious bias in the analysis. In this study, the Gaussian Mixture Distribution (GMD), a type of bimodal distribution, is presumed as a frequency distribution for the water temperature, in order to estimate the optimal parameter and to carry out the relation analysis between the optimal parameter and the basic statistical information such as mean and variance on the data. By the way, an estimation formulae to compute the frequency distribution of the data is developed by computing the parameters of GMD (i.e. ${\alpha}_1$, ${\mu}_1$, ${\sigma}_1$, ${\alpha}_2$, ${\mu}_2$, ${\sigma}_2$) by means of the major characteristic values, such as mean, standard deviation and skewness of the data. The formulae shows an excellent coincidence with the result from the observation data, in the RMS limit accuracy of 5%.