• 대한음성학회지:말소리
• /
• 제45호
• /
• pp.117-126
• /
• 2003

Decision tree-based state tying has been proposed in recent years as the most popular approach for clustering the states of context-dependent hidden Markov model-based speech recognition. The aims of state tying is to reduce the number of free parameters and predict state probability distributions of unseen models. But, when doing state tying, the size of a decision tree is very important for word independent recognition. In this paper, we try to construct optimized decision tree based on the average of feature vectors in state pool and the number of seen modes. We observed that the proposed optimal decision tree is effective in predicting the state probability distribution of unseen models.

• 경영과학
• /
• 제27권1호
• /
• pp.33-43
• /
• 2010

This paper presents a method for the estimation and analysis of the economic value of weather forecasts for CRM decision-making problems in the leisure industry. Value is calculated in terms of the customer's satisfaction returned from the user's decision under the specific payoff structure, which is itself represented by a customer's satisfaction ratio model. The decision is assessed by a modified cost-loss model to consider the customer's satisfaction instead of the loss or cost. Site-specific probability and deterministic forecasts, each of which is provided in Korea and China, are applied to generate and analyze the optimal decisions. The application results demonstrate that probability forecasts have greater value than deterministic forecasts, provided that the users can locate the optimal decision threshold. This paper also presents the optimal decision strategy for specific customers with a variety of satisfaction patterns.

• 한국전자파학회논문지
• /
• 제20권6호
• /
• pp.544-550
• /
• 2009

미사일 경고 레이다의 위협 판단 성능을 분석하기 위해서는 과대응률/미대응률 측면에서 얼마나 효과적으로 위협을 판단하는지를 분석해야 한다. 이러한 효과도 분석을 위해 Monte-Carlo 기법을 이용하여 시뮬레이션을 수행해 왔으나 시뮬레이션 수행 시간이 많이 걸리는 단점이 있었다. 본 논문에서는 단점을 보완하기 위해 확률 모델을 이용한 효과도 분석 기법을 제안하였다. 확률 모델을 설정하는 방법과 실제 시뮬레이션을 통해 전차에 장착한 레이다의 효과도를 분석한 결과를 보인다. 또한, Monte-Carlo 기법과 제안하는 확률 모델 이용 기법에 대한 시뮬레이션 수행 시간의 비교 결과를 제시하고자 한다.

• 농촌계획
• /
• 제25권3호
• /
• pp.29-36
• /
• 2019

The purpose of this study was to analyze affecting factors to consider and make decision on the urban-to-rural migrants using survey data. In the consideration model of urban-to-rural migrants, it was found that the more interest in "urban-to-rural migrants concern" was, the higher probability to consider about urban-to-rural migrants. The lower the age and income level, the higher probability to consider about the urban-to-rural migrants. In the decision making model of urban-to-rural migrants, the more interest in "urban-to-rural migrants concern" was, the higher probability to decision making of urban-to-rural migrants. The higher of stable pension income and the lower of the expected living cost, the higher probability of decision on urban-to-rural migrants. The results of this analysis show that it is necessary to continuous education to increase "interests and information about rural areas", and A number of safeguards are needed to ensure stable income after urban-to-rural migrants to increase the population of the urban-to-rural migrants.

• Nuclear Engineering and Technology
• /
• 제54권8호
• /
• pp.2941-2959
• /
• 2022

The fire brigade non-suppression probability model is a major factor that should be considered in evaluating fire-induced risk through fire probabilistic risk assessment (PRA), and also uncertainty is a critical consideration in support of risk-informed performance-based (RIPB) fire protection decision-making. This study developed an optimal integrated probabilistic fire brigade non-suppression model considering uncertainty of parameters based on the Bayesian Markov Chain Monte Carlo (MCMC) approach on electrical fire which is one of the most risk significant contributors. The result shows that the log-normal probability model with a location parameter (µ) of 2.063 and a scale parameter (σ) of 1.879 is best fitting to the actual fire experience data. It gives optimal model adequacy performance with Bayesian information criterion (BIC) of -1601.766, residual sum of squares (RSS) of 2.51E-04, and mean squared error (MSE) of 2.08E-06. This optimal log-normal model shows the better performance of the model adequacy than the exponential probability model suggested in the current fire PRA methodology, with a decrease of 17.3% in BIC, 85.3% in RSS, and 85.3% in MSE. The outcomes of this study are expected to contribute to the improvement and securement of fire PRA realism in the support of decision-making for RIPB fire protection programs.

• 산업경영시스템학회지
• /
• 제4권4호
• /
• pp.63-69
• /
• 1981

As enterprises are getting bigger and bigger and more competecious, an engineering economy for the maximization of profit based on basic theory must be considered. This thesis present dynamic computer model for the decision which controls complicated and various man- machine system optimally. This model occur in general stage can be adaptable to every kind of enterprises. So, any one who has no expert knowledge is able to get the optimal solution. And decision tree used in this paper can be applied in every kinds of academic circles as well as whole the industrial world. This paper studied optimal management of engineering project based upon basic theory of engineering economy. It introduces and functionizes the variables which generalize every possible elements, set up a model in order to find out the variable which maximize the calculated value among many other variables. And the selected values ate used as decision- marking variables for the optimal management of engineering projects. It found out some problem of this model. They are : 1. In some kinds of man-machine system it refers to Probability, but other case, it depends on only experimental probability. 2. Unless decision making process (decision tree) goes on, this model can not be applied. So these cases, this paper says, can be solved by adapting finite decision tree which is analyzed by using the same technic as those in product introduction problem. And this paper set up the computer model in order to control every procedure quickly and optimally, using Fortran IV.

• 한국지반신소재학회논문집
• /
• 제16권4호
• /
• pp.129-137
• /
• 2017

본 연구에서는 Decision Tree model을 기반으로 개발된 산사태 예측프로그램 SHAPP ver 1.0을 이용하여 전라남도 무안군 ${\bigcirc}{\bigcirc}$지역의 호남선 철도 주변에 대한 산사태 발생예측을 실시하였다. 이를 위하여 먼저 대상지역의 총 8개소에서 토층시료를 채취하고, 이에 대한 토질시험을 실시하였다. 대상지역에 대한 토질시험결과를 토대로 투수계수와 간극비에 대한 주제도를 작성하고 수치지형도를 이용하여 지형의 경사분석을 실시하였다. 이를 이용하여 산사태 발생예측을 실시한 결과 총 15,552개의 해석셀 가운데 435개의 셀에서 산사태가 발생될 것으로 예측되었다. 이때 해석셀의 크기는 $10m{\times}10m$이므로 산사태 발생예상 면적은 $43,500m^2$으로 나타났다.

• Communications for Statistical Applications and Methods
• /
• 제7권2호
• /
• pp.605-616
• /
• 2000

Three primary interests frequently raised by mortgage companies are introduced and the corresponding statistical approaches for the default probability in mortgage companies are examined. Statistical models considered in this paper are time series, logistic regression, decision tree, neural network, and discrete time models. Usage of the models is illustrated using an artificially modified data set and the corresponding models are evaluated in appropriate manners.

• 대한전기학회논문지
• /
• 제33권10호
• /
• pp.381-386
• /
• 1984

This paper deals with the microcomputer realization of EMG pattern recognition system which provides identification of motion commands from the EMG signals for the on-line control of a prosthetic arm. A probabilistic model of pattern is formulated in the feature space of integral absolute value(IAV) to describe the relation between a motion command and the location of corresponding pattern. This model enables the derivation of sample density function of a command in the feature space of IAV. Classification is caried out through the multiclass sequential decision process, where the decision rule and the stopping rule of the process are designed by using the simple mathematical formulas defined as the likelihood probability and the decision measure, respectively. Some floating point algorithms such as addition, multiplication, division, square root and exponential function are developed for calculating the probability density functions and the decision measure. Only six primitive motions and one no motion are incorporated in this paper.

• Journal of Information Processing Systems
• /
• 제10권4호
• /
• pp.602-617
• /
• 2014

The performance of a cognitive radio network (CRN) solely depends on how precisely the secondary users can sense the presence or absence of primary users. The incorporation of a spatial false alarm makes deriving the probability of a correct decision a cumbersome task. Previous literature performed this task for the case of a received signal under a Normal probability density function case. In this paper we enhance the previous work, including the impact of carrier frequency, the gain of antennas on both sides, and antenna heights so as to observe the robustness against noise and interference and to make the correct decision of detection. Three small scale fading channels: Rayleigh, Normal, and Weibull were considered to get the real scenario of a CRN in an urban area. The incorporation of a maximal-ratio combining and selection combing with a variation of the number of received antennas have also been studied in order to achieve the correct decision of spectral sensing, so as to serve the cognitive users. Finally, we applied the above concept to a traffic model of the CRN, which we based on a two-dimensional state transition chain.