• Journal of applied mathematics & informatics
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• 제23권1_2호
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• pp.153-165
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• 2007

This paper deals with the empirical Bayes two-action problem of testing $H_0\;:\;{\theta}{\leq}{\theta}_0$: versus $H_1\;:\;{\theta}>{\theta}_0$ using a linear error loss for some discrete nonexponential families having probability function either $$f_1(x{\mid}{\theta})=(x{\alpha}+1-{\theta}){\theta}^x\prod\limits_{j=0}^x\;(j{\alpha}+1)$$ or $$f_2(x{\mid}{\theta})=[{\theta}\prod\limits_{j=0}^{x-1}(j{\alpha}+1-{\theta})]/[\prod\limits_{j=0}^x\;(j{\alpha}+1)]$$. Two empirical Bayes tests ${\delta}_n^*\;and\;{\delta}_n^{**}$ are constructed. We have shown that both ${\delta}_n^*\;and\;{\delta}_n^{**}$ are asymptotically optimal, and their regrets converge to zero at an exponential decay rate O(exp(-cn)) for some c>0, where n is the number of historical data available when the present decision problem is considered.

• Journal of electromagnetic engineering and science
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• 제18권2호
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• pp.136-140
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• 2018

We propose an improved semi-empirical scattering model for X-band radar backscattering from rough sea surfaces. This new model has a wider validity range of wind speeds than does the existing semi-empirical sea spectrum (SESS) model. First, we retrieved the small-roughness parameters from the sea surfaces, which were numerically generated using the Pierson-Moskowitz spectrum and measurement datasets for various wind speeds. Then, we computed the backscattering coefficients of the small-roughness surfaces for various wind speeds using the integral equation method model. Finally, the large-roughness characteristics were taken into account by integrating the small-roughness backscattering coefficients multiplying them with the surface slope probability density function for all possible surface slopes. The new model includes a wind speed range below 3.46 m/s, which was not covered by the existing SESS model. The accuracy of the new model was verified with two measurement datasets for various wind speeds from 0.5 m/s to 14 m/s.

• 대한원격탐사학회지
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• 제17권2호
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• pp.141-153
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• 2001

A semi-empirical polarimetric backscattering model for bare soil surfaces is presented. Based on measurements by using polarimetric scatterometers and the JPL AirSAR, as well as the theoretical models, the backscattering coefficints $\sigma$$^0_w$, $\sigma$$^0_{hh}$ and $\sigma$$^0_{vh}$, and the parameters of the copolarized phase-difference probability density function, namely the degree of correlation $\alpha$ and the copolarized-phase-difference $\zeta$, are modeled empirically in terms of the volumetric soil moisture content m$_v$ and the surface roughness parameters $k_s$ and $k_l$, where k=2$\pi$f/c, s is the rms height and l is the correlation length.

• Earthquakes and Structures
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• 제3권1호
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• pp.1-15
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• 2012

An empirical predictive relationship correlating bracketed duration to earthquake magnitude, site-to-source distance, and local site conditions (i.e. rock vs. stiff soil) for stable continental regions of North America is presented herein. The correlation was developed from data from 620 horizontal motions for central and eastern North America (CENA), consisting of 28 recorded motions and 592 scaled motions. The bracketed duration data was comprised of nonzero and zero durations. The non-linear mixed-effects regression technique was used to fit a predictive model to the nonzero duration data. To account for the zero duration data, logistic regression was conducted to model the probability of zero duration occurrences. Then, the probability models were applied as weighting functions to the NLME regression results. Comparing the bracketed durations for CENA motions with those from active shallow crustal regions (e.g. western North America: WNA), the motions in CENA have longer bracketed durations than those in the WNA. Especially for larger magnitudes at far distances, the bracketed durations in CENA tend to be significantly longer than those in WNA.

• 품질경영학회지
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• 제41권1호
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• pp.149-162
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• 2013

Purpose: The purpose of this study was to design of a probabilistic model for optimum manpower planning in R&D department by Montecarlo simulation. Methods: We investigate the process and the requirement of manpower planning and scheduling in R&D department. The empirical distributions of necessary time and manpower for R&D projects are developed. From the empirical distributions, we can estimate a probability distribution of optimum manpower in R&D department. A simulation method of estimating the probability distribution of optimum manpower is considered. It is a useful tool for obtaining the sum, the variance and other statistics of the distributions. Results: The real industry cases are given and the properties of the model are investigated by Montecarlo Simulation. we apply the model to the research laboratory of the global company, and investigate and compensate the weak points of the model. Conclusion: The proposed model provides various and correct information such as average, variance, percentile, minimum, maximum and so on. A decision maker of a company can easily develop the future plan and the task of researchers may be allocated properly. we expect that the productivity can be improved by this study. The results of this study can be also applied to other areas including shipbuilding, construction, and consulting areas.

• 산업경영시스템학회지
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• 제30권3호
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• pp.103-108
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• 2007

This paper presents the conceptual framework for estimating and predicting system's susceptibility to failure as function of condition parameter value which is representing the current status of performance measure using on-line performance reliability. The performance of such system depends on one parameter with a probability distribution that degrades with time gracefully. Performance reliability represents the probability that physical performance will remain satisfactory over a finite period of time or usage cycles in the future. An empirical physical performance function is constructed to incorporate explanatory variables (operating and environmental conditions) over a time or usage dimension. This function enables one to model device performance and the associated classical reliability measures simultaneously, in the performance domain and time domain. The conditional performance reliability structure developed represents a tool to predict system performance over time or usage for next usage period. By enabling such a framework, it can bring us more efficient planning and execution in system's operation control as well as maintenance to reduce costs and/or increase profits.

• Structural Engineering and Mechanics
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• 제68권4호
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• pp.423-442
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• 2018

In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

• Wind and Structures
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• 제25권3호
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• pp.261-282
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• 2017

The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.228-232
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• 2017

Extreme hydrological events can cause serious threats to the society. Hence, the selection of probability distributions for extreme rainfall is a fundamental issue. For this reason, this study was focused on understanding possible distributional changes in annual daily maximum rainfalls (AMRs) over time in Sri Lanka using quantile regression. A simplified nine-category distributional-change scheme based on comparing empirical probability density function of two years (i.e. the first year and the last year), was used to determine the distributional changes in AMRs. Daily rainfall series of 13 station over Sri Lanka were analyzed for the period of 1960-2015. 4 distributional change categories were identified for the AMRs. 5 stations showed an upward trend in all the quantiles (i.e. 9 quantiles: from 0.05 to 0.95 with an increment of 0.01 for the AMR) which could give high probability of extreme rainfall. On the other hand, 8 stations showed a downward trend in all the quantiles which could lead to high probability of the low rainfall. Further, we identified a considerable spatial diversity in distributional changes of AMRs over Sri Lanka.

• 한국수자원학회논문집
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• 제46권6호
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• pp.643-653
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• 2013

적절한 확률분포형을 결정하고 그에 따른 확률수문량을 산정하는 것은 빈도해석에서 가장 중요한 절차이며, 이를 수행하기 위해서는 경험적 확률분포에서 얻어지는 자료와 가정한 확률분포에서 얻어지는 자료의 일치 정도를 판별하는 적합도 검정을 거쳐야 한다. 지금까지 일반적으로 적용된 적합도 검정 방법은 분포형의 전체적인 적합정도를 판별하여 최근의 기상이변으로 인한 극치 사상에 대하여는 충분히 고려하지 못하고 있다. 따라서 본 연구에서는 분포형의 극치 사상에 가중치를 주는 modified Anderson-Darling(AD) 검정 방법을 3변수 Weibull 분포형에 적용하여 검정통계량 한계값과 기각력을 살펴보았으며 이를 실제자료에 적용한 결과, modified AD 검정 방법이 다른 기존의 적합도 검정보다 더 우수한 기각력을 가지고 있음을 확인하였다. 이는 앞으로 3변수 Weibull 분포형을 이용한 극치 수문량 선정에 있어 modified AD 방법이 하나의 기준으로 작용할 수 있을 것이라 판단된다.