• 제목/요약/키워드: Entropy index

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엔트로피지수에 의한 국내항만의 화물집중도 측정 (A Measurement of Degree of Cargo Concentration in Korean Ports Using the Entropy Index)

  • 박노경
    • 한국항만경제학회지
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    • 제20권1호
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    • pp.1-20
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    • 2004
  • The purpose of this paper is to analyze the degree of cargo concentration at Korean ports using Theil's Entropy and to compare the results with those of Gini coefficient, Hoyle(1983), and Hirshmann-Herfindahl models. The entropy indices were compared with other models after measuring the cargo concentration for the period of 1981-2000 among the 18 Korean ports. The core results of empirical analysis are as follows: first, the empirical results of entropy indices show the following trends: all the ports(concentration except 1996's slight deconcentration), ports in Western area(deconcentration in 1990s and slight concentration in 2000), ports in Southern area(deconcentration in 1980s and 1990s except concentration in 2000), and ports in Eastern area(continuous trends of concentration). However, competition power will be decreased if concentration is increased, because of the character of entropy index. The empirical results of 4 indices except Hoyle model show the comparatively same directions in terms of trends. This study found out the similar results among the following models: All the ports(entropy index & Gini coefficient & H-H model), ports in Western area(Entropy index &Hoyle model), ports in Southern area(Entropy index & Gini coefficient), and ports in Eastern area(Entropy index & H-H index).The policy planner of Korean ports should find out the determination factors of concentration and deconcentration of each ports and decide the investment priority, size and scope for balancing the development of regional ports.

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Predicting the FTSE China A50 Index Movements Using Sample Entropy

  • AKEEL, Hatem
    • The Journal of Asian Finance, Economics and Business
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    • 제9권3호
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    • pp.1-10
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    • 2022
  • This research proposes a novel trading method based on sample entropy for the FTSE China A50 Index. The approach is used to determine the points at which the index should be bought and sold for various holding durations. The findings are then compared to three other trading strategies: buying and holding the index for the entire time period, using the Relative Strength Index (RSI), and using the Moving Average Convergence Divergence (MACD) as buying/selling signaling tools. The unique entropy trading method, which used 90-day holding periods and was called StEn(90), produced the highest cumulative return: 25.66 percent. Regular buy and hold, RSI, and MACD were all outperformed by this strategy. In fact, when applied to the same time periods, RSI and MACD had negative returns for the FTSE China A50 Index. Regular purchase and hold yielded a 6% positive return, whereas RSI yielded a 28.56 percent negative return and MACD yielded a 33.33 percent negative return.

Power Investigation of the Entropy-Based Test of Fit for Inverse Gaussian Distribution by the Information Discrimination Index

  • Choi, Byungjin
    • Communications for Statistical Applications and Methods
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    • 제19권6호
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    • pp.837-847
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    • 2012
  • Inverse Gaussian distribution is widely used in applications to analyze and model right-skewed data. To assess the appropriateness of the distribution prior to data analysis, Mudholkar and Tian (2002) proposed an entropy-based test of fit. The test is based on the entropy power fraction(EPF) index suggested by Gokhale (1983). The simulation results report that the power of the entropy-based test is superior compared to other goodness-of-fit tests; however, this observation is based on the small-scale simulation results on the standard exponential, Weibull W(1; 2) and lognormal LN(0:5; 1) distributions. A large-scale simulation should be performed against various alternative distributions to evaluate the power of the entropy-based test; however, the use of a theoretical method is more effective to investigate the powers. In this paper, utilizing the information discrimination(ID) index defined by Ehsan et al. (1995) as a mathematical tool, we scrutinize the power of the entropy-based test. The selected alternative distributions are the gamma, Weibull and lognormal distributions, which are widely used in data analysis as an alternative to inverse Gaussian distribution. The study results are provided and an illustrative example is analyzed.

A hybrid evaluation of information entropy meta-heuristic model and unascertained measurement theory for tennis motion tracking

  • Zhong, Yongfeng;Liang, Xiaojun
    • Advances in nano research
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    • 제12권3호
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    • pp.263-279
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    • 2022
  • In this research, the physical education training quality was investigated using the entropy model to compute variance associated with a random value (a strong tool). The entropy and undefined estimation principles are used to extract the greatest entropy of information dependent on the index system. In the study of tennis motion tracking from a dynamic viewpoint, such stages are utilized to improve the perception of the players' achievement (Lv et al. 2020). Six female tennis players served on the right side (50 cm from the T point). The initial flat serve from T point was the movement under consideration, and the entropy was utilized to weigh all indications. As a result, a multi-index measurement vector is stabilized, followed by the confidence level to determine the structural plane establishment range. As a result, the use of the unascertained measuring technique of information entropy showed an excellent approach to assessing athlete performance more accurately than traditional ways, enabling coaches and athletes to enhance their movements successfully.

A NOTE ON THE MAXIMUM ENTROPY WEIGHTING FUNCTION PROBLEM

  • Hong, Dug-Hun;Kim, Kyung-Tae
    • Journal of applied mathematics & informatics
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    • 제23권1_2호
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    • pp.547-552
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    • 2007
  • In this note, we extends some of the results of Liu [Fuzzy Sets and systems 157 (2006) 869-878]. This extension consists of a simple proof involving weighted functions and their preference index. We also give an elementary simple proof of the maximum entropy weighting function problem with a given preference index value without using any advanced theory like variational principles or without using Lagrangian multiplier methods.

Shannon의 정보이론과 문헌정보 (Shannon's Information Theory and Document Indexing)

  • 정영미
    • 한국문헌정보학회지
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    • 제6권
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    • pp.87-103
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    • 1979
  • Information storage and retrieval is a part of general communication process. In the Shannon's information theory, information contained in a message is a measure of -uncertainty about information source and the amount of information is measured by entropy. Indexing is a process of reducing entropy of information source since document collection is divided into many smaller groups according to the subjects documents deal with. Significant concepts contained in every document are mapped into the set of all sets of index terms. Thus index itself is formed by paired sets of index terms and documents. Without indexing the entropy of document collection consisting of N documents is $log_2\;N$, whereas the average entropy of smaller groups $(W_1,\;W_2,...W_m)$ is as small $(as\;(\sum\limits^m_{i=1}\;H(W_i))/m$. Retrieval efficiency is a measure of information system's performance, which is largely affected by goodness of index. If all and only documents evaluated relevant to user's query can be retrieved, the information system is said $100\%$ efficient. Document file W may be potentially classified into two sets of relevant documents and non-relevant documents to a specific query. After retrieval, the document file W' is reclassified into four sets of relevant-retrieved, relevant-not retrieved, non-relevant-retrieved and non-relevant-not retrieved. It is shown in the paper that the difference in two entropies of document file Wand document file W' is a proper measure of retrieval efficiency.

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On Information Theoretic Index for Measuring the Stochastic Dependence Among Sets of Variates

  • Kim, Hea-Jung
    • 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.

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Curvature Entropy as A Shape-Generation Index

  • Ujiie, Yoshiki;Matsuoka, Yoshiyuki
    • 한국디자인학회:학술대회논문집
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    • 한국디자인학회 2001년도 Bulletin of The 5th Asian Design Conference International Symposium on Design Science
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    • pp.26.2-26
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    • 2001
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Formation of Employment Subcenters and Regional Industry Restructuring: Focusing Wholesale and Retail Sector in Incheon

  • YOO, Byong-Kook;KIM, Soon-Hong
    • 유통과학연구
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    • 제18권2호
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    • pp.59-67
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    • 2020
  • Purpose: This study examines the relationship between formation of employment subcenters and regional industrial structures in Incheon. Research design, data, and methodology: We used the five-year panel data from 2012 to 2016 in 146 basic municipal units of Incheon to analyze panel regression models. Gross employment density and employment to population ratio were used as indicators of employment subcenters formation. The entropy index and Hachman index were used for analyzing the diversity and heterogeneity of industrial structures. Result: The analyses of two panel regression models showed that for the formation of employment subcenters, both the Entropy and Hachman index were significantly negative in most models. But tertiary industry was shown to have a significant positive relationship in all models. In the wholesale and retail sector, it was found that the average number of employees in the employment subcenters is significantly higher than that in the non-employment subcenters. Conclusions: The specialization of the industrial structure rather than the diversification contributes to the formation of the employment subcenters in Incheon. In particular, it can be considered that the wholesale and retail sector plays a very important role in forming the employment subcenters in many areas of Incheon.

Water body extraction in SAR image using water body texture index

  • Ye, Chul-Soo
    • 대한원격탐사학회지
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    • 제31권4호
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    • pp.337-346
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    • 2015
  • Water body extraction based on backscatter information is an essential process to analyze floodaffected areas from Synthetic Aperture Radar (SAR) image. Water body in SAR image tends to have low backscatter values due to homogeneous surface of water, while non-water body has higher backscatter values than water body. Non-water body, however, may also have low backscatter values in high resolution SAR image such as Kompsat-5 image, depending on surface characteristic of the ground. The objective of this paper is to present a method to increase backscatter contrast between water body and non-water body and also to remove efficiently misclassified pixels beyond true water body area. We create an entropy image using a Gray Level Co-occurrence Matrix (GLCM) and classify the entropy image into water body and non-water body pixels by thresholding of the entropy image. In order to reduce the effect of threshold value, we also propose Water Body Texture Index (WBTI), which measures simultaneously the occurrence of repeated water body pixel pair and the uniformity of water body in the binary entropy image. The proposed method produced high overall accuracy of 99.00% and Kappa coefficient of 90.38% in water body extraction using Kompsat-5 image. The accuracy analysis indicates that the proposed WBTI method is less affected by the choice of threshold value and successfully maintains high overall accuracy and Kappa coefficient in wide threshold range.