• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.7
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• pp.822-830
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• 2012

Clutters are all unwanted radar returns to affect on detection of targets. Radar clutter is characterized by amplitude distributions, spectrum, etc. Clutter is modelled with considering these kinds of characteristics. In this paper, a Weibull distribution function approximated by uniform distribution function is suggested. Weibull distribution function is used to model the various clutters. This paper shows that the data generated by the approximated solution of Weibull distribution function satisfy the Weibull probability density function. This paper shows that the data generation time of approximated Weibull distribution function solution is reduced by 20 % compared with the generation time of original Weibull probability density function.

• School Mathematics
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• v.13 no.3
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• pp.423-446
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• 2011

In school mathematics, concepts of definite integral and integration by substitution have mathematical connection with introduction of probability density function, expectation of continuous random variable, and standardization of normal distribution. However, we have difficulty in finding mathematical connection between integration and continuous probability distribution in the curriculum manual, 13 kinds of 'Basic Calculus and Statistics' and 10 kinds of 'Integration and Statistics' authorized textbooks, and activity books applied to the revised curriculum. Therefore, the purpose of this study is to provide a teaching method connected with mathematical concepts of integral in regard to three concepts in continuous probability distribution chapter-introduction of probability density function, expectation of continuous random variable, and standardization of normal distribution. To find mathematical connection between these three concepts and integral, we analyze a survey of student, the revised curriculum manual, authorized textbooks, and activity books as well as 13 domestic and 22 international statistics (or probability) books. Developed teaching method was applied to actual classes after discussion with a professional group. Through these steps, we propose the result by making suggestions to revise curriculum or change the contents of textbook.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1276-1282
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• 2013

This paper proposes a stochastic modeling of plug-in electric vehicles (PEVs) distribution in power systems, and analyzes the corresponding clustering characteristic. It is essential for power utilities to estimate the PEV charging demand as the penetration level of PEV is expected to increase rapidly in the near future. Although the distribution of PEVs in power systems is the primary factor for estimating the PEV charging demand, the data currently available are statistics related to fuel-driven vehicles and to existing electric demands in power systems. In this paper, we calculate the number of households using electricity at individual ending buses of a power system based on the electric demands. Then, we estimate the number of PEVs per household using the probability density function of PEVs derived from the given statistics about fuel-driven vehicles. Finally, we present the clustering characteristic of the PEV distribution via case studies employing the test systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.33-36
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• 2008

We introduce some properties for fuzzy binomial distributions with fuzzy valued probability. First we define fuzzy type I error and type II error for fuzzy relative frequency and agreement index. And we show that an fuzzy power function and fuzzy binomial frequency function for binomial proportion test.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.11 no.3
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• pp.165-172
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• 1999

A probability density function of reliability function is derived in this paper, by which the stability of armor units on the rubble-mound breakwater can be studied on the probabilistic approach. To obtain the distribution, each random variable of the reliability function is assumed to follow Gaussian distribution. The distribution function of reliability function is in agreement with the histogram simulated by the Monte-Carlo method. In addition, the failure probability of armor units on the rubble-mound breakwater evaluated by the derived probability density function is shown to have the same order of magnitude as those calculated by FMA and AFDA of moment method. In particular, it is important to note that random variables of the reliability function may be considered to be statistically independent in the reliability analysis of armor units on the rubble-mound breakwater. Therefore, the present approach may be straightforwardly applicable to all of the cases that any random variables in the reliability function are controlled by other distribution functions as well as normal distribution.

• Journal of the Society of Naval Architects of Korea
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• v.52 no.1
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• pp.88-95
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• 2015

For the frequency-domain spectral fatigue analysis, the probability density function of stress range needs to be estimated based on the stress spectrum only, which is a frequency domain representation of the response. The probability distribution of the stress range of the narrow-band spectrum is known to follow the Rayleigh distribution, however the PDF of wide-band spectrum is difficult to define with clarity due to the complicated fluctuation pattern of spectrum. In this paper, efforts have been made to figure out the links between the probability density function of stress range to the structural response of wide-band Gaussian random process. An artificial neural network scheme, known as one of the most powerful system identification methods, was used to identify the multivariate functional relationship between the idealized wide-band spectrums and resulting probability density functions. To achieve this, the spectrums were idealized as a superposition of two triangles with arbitrary location, height and width, targeting to comprise wide-band spectrum, and the probability density functions were represented by the linear combination of equally spaced Gaussian basis functions. To train the network under supervision, varieties of different wide-band spectrums were assumed and the converged probability density function of the stress range was derived using the rainflow counting method and all these data sets were fed into the three layer perceptron model. This nonlinear least square problem was solved using Levenberg-Marquardt algorithm with regularization term included. It was proven that the network trained using the given data set could reproduce the probability density function of arbitrary wide-band spectrum of two triangles with great success.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.443-455
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• 1999

A simulation-based approach to estimating the probability of an arbitrary region under a multivariate normal distribution is developed. In specific, the probability is expressed as the ratio of the unrestricted and the restricted multivariate normal density functions, where the restriction is given by the region whose probability is of interest. The density function of the restricted distribution is then estimated by using a sample generated from the Gibbs sampling algorithm.

• Bulletin of the Korean Mathematical Society
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• v.55 no.5
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• pp.1563-1575
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• 2018

In this paper, our central focus is upon gamma and beta q-distributions from a probabilistic viewpoint. The gamma and the beta q-distributions are characterized by investing the nature of the joint q-probability density function through the q-independence property and the q-Laplace transform.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.869-875
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• 1996

This paper investigates a method for dtermining a threshold value based on the probability distribution function for color image segmentation. Principal components of normalized color is nalyzed and found that there are effective color transforms for outdoor scents. We esplain the functional relationship of the treshold and the probability of a regiona detection, asuming bivarate Gaussian probability density function. Experimental results show that the probability of detection is proportional to the segmented area.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.4
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• pp.58-66
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• 1998

Irrigation Reservoir Water Supply Index(IRWSI), which can be applied to the effective supply and management of the irrigation water resources, was developed. IRWSI was formulated as resealed nonexceedance probabilities of two hydrologic components : reservoir storage ratio and precipitation. To generate nonexceedance probability of hydrologic component, it was important to define the optimal one among the various probability distribution function in the state of nature. To define an optimal probability distribution, in this study, four types of probability distribution function were tested by the K-S fitting, and for the calculation of IRWSI, reservoir storage ratio(%) and precipitation used Normal distribution & Gamma distribution, respectively. In this study, the weight coefficients of a and b for each hydrologic component, which is precipitation and reservoir storage ratio, was decided as 0.8 and 0.2, respectively. While some studies changed weight coefficients according to the size of basin area, this study used same values without considering that. From the analysis of drought characteristics, it was found that the IRWSI was sensitive to the size of irrigation area rather than the size of basin area, and the south-eastern region of Korea had been suffered from severe drought damage.