• 대한교통학회지
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• 제7권2호
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• pp.45-52
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• 1989

The network equilibrium theory is to estimate the travel choices on a transportation network when the resulting travel times and costs are one basis for the choices. Increasing use of this principle on travel assignment problem lead to develop the combined choice models including not only travel options such as mode and route, but location options like trip distribution problems. This paper, first, reviews earlier developments of variable demand network equilibrium models, combined modeles of trip distribution and assignment, and entropy constrained combined models. Then various model structures of combining travel choice models based on network equilibrium theory and entropy constraints are discussed.

• Communications for Statistical Applications and Methods
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• 제16권4호
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• pp.659-667
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• 2009

Recently Song and Cheon (2006) and Cheon and Lim (2009) developed the generalized maximum entropy(GME) estimator to solve ill-posed problems for the regression coefficients in the simple panel model. The models discussed consider the individual and a spatial autoregressive disturbance effects. However, in many application in economics the data may contain nested groupings. This paper considers a two-way error component model with nested groupings for the ill-posed data and proposes the GME estimator of the unknown parameters. The performance of this estimator is compared with the existing methods on the simulated dataset. The results indicate that the GME method performs the best in estimating the unknown parameters in terms of its quality when the data are ill-posed.

• 한국어학
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• 제79권
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• pp.63-89
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• 2018

This study explores contrastive relation among voiced bilabial fricative [${\ss}$], voiceless bilabial stop [p] and glide [w] in Middle Korean consonant system based on Probabilistic Model. Preceding researches about voiced bilabial fricative [${\ss}$] proposed two influential arguments. One is voiced bilabial fricative [${\ss}$] was an independent phoneme, the other is it was not an independent phoneme but an allophone of voiceless bilabial stop [p] in Middle Korean. This study applies Probabilistic Phonological Relationship Model (PPRM) for solving the problem of dichotomy about contrastive and allophonic relations. The analysis result of the contrastive entropy by PPRM suggests that voiced bilabial fricative [${\ss}$] was just an allophone of voiceless bilabial stop [p] or glide [w] in Middle Korean. Comparing the entropies between [p] and other consonants with the entropies between [${\ss}$] and other consonants, a continuum defined in terms of entropy reveals that [${\ss}$] in Middle Korean was more allophonic than phonemic.

• 전자공학회논문지CI
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• 제41권2호
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• pp.87-94
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• 2004

특징 집합 선택은 학습 알고리즘의 전처리 과정으로 사용되기도 한다. 수집된 자료가 문제와 관련이 없다거나 중복된 정보를 갖고 있는 경우, 이를 학습 모델생성 이전에 제거함으로써 학습의 성능을 향상시킬 수 있다. 또한 탐색 공간을 감소시킬 수 있으며 저장 공간도 줄일 수 있다. 본 논문에서는 특징 집합의 추출과 추출된 특징 집합의 성능 평가를 위하여 엔트로피를 기반으로 한 휴리스틱 함수를 사용하는 새로운 특징 선택 알고리즘을 제안하였다. 탐색 방법으로는 ACS 알고리즘을 이용하였다. 그 결과 학습에 사용될 특징의 차원을 감소시킴으로써 학습 모델의 크기와 불필요한 계산 시간을 감소시킬 수 있었다.

• 전기전자학회논문지
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• 제26권4호
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• pp.531-536
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• 2022

배터리를 효율적으로 관리하기 위해서는 배터리의 건강 상태와 잔여 수명을 정확하게 추정하고 관리하는 것이 중요하다. 배터리는 같은 종류여도 설비용량 및 전압 등의 특성이 다르며 학습용 모델을 위한 배터리와 모델을 통한 예측을 위한 배터리가 서로 다를 경우에는 정확도 측정에 한계가 있다. 본 논문에서는 전압의 분포와 방전 시간을 이용한 엔트로피 지수를 일반화하고 4개의 배터리를 각각 1개씩 교차적으로 훈련 집합과 테스트 집합으로 정의하여 기계학습의 선형회귀 분석을 통하여 배터리의 건강 상태를 예측하는 방법을 제안하였다. 제안된 방법은 평균 절대값 퍼센트 오차를 이용하여 95% 이상의 높은 정확도를 나타내었다.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.190-194
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• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• Journal of the Korean Statistical Society
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• 제26권1호
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• pp.131-146
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• 1997

In this paper the problem of measuring the stochastic dependence among sets fo random variates is considered, and attention is specifically directed to forming a single well-defined measure of the dependence among sets of normal variates. A new information theoretic measure of the dependence called dependence index (DI) is introduced and its several properties are studied. The development of DI is based on the generalization and normalization of the mutual information introduced by Kullback(1968). For data analysis, minimum cross entropy estimator of DI is suggested, and its asymptotic distribution is obtained for testing the existence of the dependence. Monte Carlo simulations demonstrate the performance of the estimator, and show that is is useful not only for evaluation of the dependence, but also for independent model testing.

• 자원ㆍ환경경제연구
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• 제9권2호
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• pp.285-309
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• 2000

One of the main issues in natural resource economics is estimating the amount of stock and the biological growth functions of renewable natural resources. Since the stock level is not directly observed the usual econometric approaches cannot be employed for this purpose. The maximum entropy approach has been suggested as a useful alternative to estimate the dynamic model of natural resource use. This study estimates the stock and the growth function of Korean anchovy using the data for yield and yield efforts. The results show that the current level of anchovy yield exceeds its maximum sustainable yield, which implies that the stock will decrease substantially over time.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.193-207
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• 2001

When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

• Journal of Multimedia Information System
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• 제5권4호
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• pp.273-276
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• 2018

In video compression standards, the entropy coding is essential to the high performance compression because redundancy of data symbols is removed. Binary arithmetic coding is one of high performance entropy coding methods. However, the dependency between consecutive binary symbols prevents improving the throughput. For the throughput enhancement, a new probability model is proposed for encoding multi-symbols at one time. In the proposed method, multi-symbol encoder is implemented with only adders and shifters, and the multiplication table for interval subdivision of binary arithmetic coding is removed. Compared to the compression ratio of CABAC of H.264/AVC, the performance degradation on average is only 1.4% which is negligible.