• Title/Summary/Keyword: generalized maximum entropy

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Comparison of Species Distribution Models According to Location Data (위치자료의 종류에 따른 생물종 분포모형 비교 연구)

  • Seo, Chang-Wan;Park, Yu-Ri;Choi, Yun-Soo
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.4
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    • pp.59-64
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    • 2008
  • We need to use the strength of each Species Distribution Model(SDM) because presence location data were only collected due to time and economic limitations in Korea. This study investigated and compared GAM(Generalized Additive Model) which is one of presence-absence models with Maxent(Maximum Entropy Model) which is one of presence only models according to location data(presence/absence data). The target species was Fisher(Martes pennanti) which is an endangered species in California, USA. We implemented environmental data such as topography, climate and vegetation, and applied models to sub-regions and study area. The results of this study were as follows. Firstly, GAM which used real presence and absence data was better than GAM which used pseudo-absence data and Maxent which used presence-only data. Secondly, Maxent was better than GAM when presence-only data were used. Lastly, each model which applied to different regions didn't predict other area well due to the difference of habitat environment and over-predicted outside of study area. We need to select an optimal model to predict a suitable habitat according to the type and distribution of location data.

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Bandwidth Management of WiMAX Systems and Performance Modeling

  • Li, Yue;He, Jian-Hua;Xing, Weixi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.2 no.2
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    • pp.63-81
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    • 2008
  • WiMAX has been introduced as a competitive alternative for metropolitan broadband wireless access technologies. It is connection oriented and it can provide very high data rates, large service coverage, and flexible quality of services (QoS). Due to the large number of connections and flexible QoS supported by WiMAX, the uplink access in WiMAX networks is very challenging since the medium access control (MAC) protocol must efficiently manage the bandwidth and related channel allocations. In this paper, we propose and investigate a cost-effective WiMAX bandwidth management scheme, named the WiMAX partial sharing scheme (WPSS), in order to provide good QoS while achieving better bandwidth utilization and network throughput. The proposed bandwidth management scheme is compared with a simple but inefficient scheme, named the WiMAX complete sharing scheme (WCPS). A maximum entropy (ME) based analytical model (MEAM) is proposed for the performance evaluation of the two bandwidth management schemes. The reason for using MEAM for the performance evaluation is that MEAM can efficiently model a large-scale system in which the number of stations or connections is generally very high, while the traditional simulation and analytical (e.g., Markov models) approaches cannot perform well due to the high computation complexity. We model the bandwidth management scheme as a queuing network model (QNM) that consists of interacting multiclass queues for different service classes. Closed form expressions for the state and blocking probability distributions are derived for those schemes. Simulation results verify the MEAM numerical results and show that WPSS can significantly improve the network’s performance compared to WCPS.

A Study on Decision Tree for Multiple Binary Responses

  • Lee, Seong-Keon
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.971-980
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    • 2003
  • The tree method can be extended to multivariate responses, such as repeated measure and longitudinal data, by modifying the split function so as to accommodate multiple responses. Recently, some decision trees for multiple responses have been constructed by Segal (1992) and Zhang (1998). Segal suggested a tree can analyze continuous longitudinal response using Mahalanobis distance for within node homogeneity measures and Zhang suggested a tree can analyze multiple binary responses using generalized entropy criterion which is proportional to maximum likelihood of joint distribution of multiple binary responses. In this paper, we will modify CART procedure and suggest a new tree-based method that can analyze multiple binary responses using similarity measures.

Optimal Management of Mackerel in Korea: A Maximum Entropy Approach (최대 엔트로피 기법을 이용한 한국 연근해 고등어 최적 관리에 관한 연구)

  • Park, Yunsun;Kwon, Oh-Sang
    • Environmental and Resource Economics Review
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    • v.28 no.2
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    • pp.277-306
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    • 2019
  • Mackerel is one of the most widely consumed aquatic products in Korea. Concerns about the depletion of stocks have also arisen as the catch has decreased. The primary purpose of this study is to estimate the mackerel stock and derive the optimal level of catch in Korea. We apply a generalized maximum entropy econometric method to estimate the mackerel growth function, which does not require the steady state assumption. We incorporate a bootstrapping approach to derive the significance levels of parameter estimates. We found that the average ratio of catch to the estimated total stock was less than 30% before the 1990s but exceeded 40% in the 1990s. After 2000, it dropped back to about 36%. This finding indicates that mackerel may have been over-fished in the 1990s, but the government regulations introduced in the 2000s alleviated over-fishing problems. Nevertheless, our dynamic optimization analysis suggests that the total allowable catch may need to be carefully controlled to achieve socially optimal management of resources.

Spatial Planning of Climate Adaptation Zone to Promote Climate Change Adaptation for Endangered Species (생물다양성 보전을 위한 기후적응지역 설정 연구 -삵의 서식지를 중심으로-)

  • Lee, Dongkun;Baek, Gyounghye;Park, Chan;Kim, Hogul
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.14 no.6
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    • pp.111-117
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    • 2011
  • This study attempts to facilitate climate change adaptation in conservation area by spatial planning of climate adaptation zone for endangered species. Spatial area is South Korea and select leopard cat (Prionailurus bengalensis) as a target species of this study. In order to specify the climate adaptation zone, firstly, Maximum entropy method (Maxent) was used to identify suitable habitat, and then core habitat was selected for leopard cat. Secondly, land use resistance index was evaluated and least cost distance was analyzed for target species. In this step we choose dispersal capacity of leopard cat to reflect species ecological characteristic. Finally, climate adaptation zone is described and adaptation measures are suggested. The presented approach could be generalized for application into conservation planning and restoration process. Furthermore, spatial planning of climate adaptation zone could increase heterogeneity of habitat and improve adaptive capacity of species and habitat itself.

Effect and uncertainty analysis according to input components and their applicable probability distributions of the Modified Surface Water Supply Index (Modified Surface Water Supply Index의 입력인자와 적용 확률분포에 따른 영향과 불확실성 분석)

  • Jang, Suk Hwan;Lee, Jae-Kyoung;Oh, Ji Hwan;Jo, Joon Won
    • Journal of Korea Water Resources Association
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    • v.50 no.7
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    • pp.475-488
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    • 2017
  • To simulate accurate drought, a drought index is needed to reflect the hydrometeorological phenomenon. Several studies have been conducted in Korea using the Modified Surface Water Supply Index (MSWSI) to simulate hydrological drought. This study analyzed the limitations of MSWSI and quantified the uncertainties of MSWSI. The influence of hydrometeorological components selected as the MSWSI components was analyzed. Although the previous MSWSI dealt with only one observation for each input component such as streamflow, ground water level, precipitation, and dam inflow, this study included dam storage level and dam release as suitable characteristics of the sub-basins, and used the areal-average precipitation obtained from several observations. From the MSWSI simulations of 2001 and 2006 drought events, MSWSI of this study successfully simulated drought because MSWSI of this study followed the trend of observing the hydrometeorological data and then the accuracy of the drought simulation results was affected by the selection of the input component on the MSWSI. The influence of the selection of the probability distributions to input components on the MSWSI was analyzed, including various criteria: the Gumbel and Generalized Extreme Value (GEV) distributions for precipitation data; normal and Gumbel distributions for streamflow data; 2-parameter log-normal and Gumbel distributions for dam inflow, storage level, and release discharge data; and 3-parameter log-normal distribution for groundwater. Then, the maximum 36 MSWSIs were calculated for each sub-basin, and the ranges of MSWSI differed significantly according to the selection of probability distributions. Therefore, it was confirmed that the MSWSI results may differ depending on the probability distribution. The uncertainty occurred due to the selection of MSWSI input components and the probability distributions were quantified using the maximum entropy. The uncertainty thus increased as the number of input components increased and the uncertainty of MSWSI also increased with the application of probability distributions of input components during the flood season.

Application of Texture Feature Analysis Algorithm used the Statistical Characteristics in the Computed Tomography (CT): A base on the Hepatocellular Carcinoma (HCC) (전산화단층촬영 영상에서 통계적 특징을 이용한 질감특징분석 알고리즘의 적용: 간세포암 중심으로)

  • Yoo, Jueun;Jun, Taesung;Kwon, Jina;Jeong, Juyoung;Im, Inchul;Lee, Jaeseung;Park, Hyonghu;Kwak, Byungjoon;Yu, Yunsik
    • Journal of the Korean Society of Radiology
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    • v.7 no.1
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    • pp.9-15
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    • 2013
  • In this study, texture feature analysis (TFA) algorithm to automatic recognition of liver disease suggests by utilizing computed tomography (CT), by applying the algorithm computer-aided diagnosis (CAD) of hepatocellular carcinoma (HCC) design. Proposed the performance of each algorithm was to comparison and evaluation. In the HCC image, set up region of analysis (ROA, window size was $40{\times}40$ pixels) and by calculating the figures for TFA algorithm of the six parameters (average gray level, average contrast, measure of smoothness, skewness, measure of uniformity, entropy) HCC recognition rate were calculated. As a result, TFA was found to be significant as a measure of HCC recognition rate. Measure of uniformity was the most recognition. Average contrast, measure of smoothness, and skewness were relatively high, and average gray level, entropy showed a relatively low recognition rate of the parameters. In this regard, showed high recognition algorithms (a maximum of 97.14%, a minimum of 82.86%) use the determining HCC imaging lesions and assist early diagnosis of clinic. If this use to therapy, the diagnostic efficiency of clinical early diagnosis better than before. Later, after add the effective and quantitative analysis, criteria research for generalized of disease recognition is needed to be considered.

Development and application of GLS OD matrix estimation with genetic algorithm for Seoul inner-ringroad (유전알고리즘을 이용한 OD 추정모형의 개발과 적용에 관한 연구 (서울시 내부순환도로를 대상으로))

  • 임용택;김현명;백승걸
    • Journal of Korean Society of Transportation
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    • v.18 no.4
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    • pp.117-126
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    • 2000
  • Conventional methods for collecting origin-destination trips have been mainly relied on the surveys of home or roadside interview. However, the methods tend to be costly, labor intensive and time disruptive to the trip makers, thus the methods are not considered suitable for Planning applications such as routing guidance, arterial management and information Provision, as the parts of deployments in Intelligent Transport Systems Motivated by the problems, more economic ways to estimate origin-destination trip tables have been studied since the late 1970s. Some of them, which have been estimating O-D table from link traffic counts are generally Entropy maximizing, Maximum likelihood, Generalized least squares(GLS), and Bayesian inference estimation etc. In the Paper, with user equilibrium constraint we formulate GLS problem for estimating O-D trips and develop a solution a1gorithm by using Genetic Algorithm, which has been known as a g1oba1 searching technique. For the purpose of evaluating the method, we apply it to Seoul inner ringroad and compare it with gradient method proposed by Spiess(1990). From the resu1ts we fond that the method developed in the Paper is superior to other.

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Selection of Optimal Models for Predicting the Distribution of Invasive Alien Plants Species (IAPS) in Forest Genetic Resource Reserves (산림생태계 보호구역에서 외래식물 분포 예측을 위한 최적 모형의 선발)

  • Lim, Chi-hong;Jung, Song-hie;Jung, Su-young;Kim, Nam-shin;Cho, Yong-chan
    • Korean Journal of Environment and Ecology
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    • v.34 no.6
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    • pp.589-600
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    • 2020
  • Effective conservation and management of protected areas require monitoring the settlement of invasive alien species and reducing their dispersion capacity. We simulated the potential distribution of invasive alien plant species (IAPS) using three representative species distribution models (Bioclim, GLM, and MaxEnt) based on the IAPS distribution in the forest genetic resource reserve (2,274ha) in Uljin-gun, Korea. We then selected the realistic and suitable species distribution model that reflects the local region and ecological management characteristics based on the simulation results. The simulation predicted the tendency of the IAPS distributed along the linear landscape elements, such as roads, and including some forest harvested area. The statistical comparison of the prediction and accuracy of each model tested in this study showed that the GLM and MaxEnt models generally had high performance and accuracy compared to the Bioclim model. The Bioclim model calculated the largest potential distribution area, followed by GLM and MaxEnt in that order. The Phenomenological review of the simulation results showed that the sample size more significantly affected the GLM and Bioclim models, while the MaxEnt model was the most consistent regardless of the sample size. The optimal model overall for predicting the distribution of IAPS among the three models was the MaxEnt model. The model selection approach based on detailed flora distribution data presented in this study is expected to be useful for efficiently managing the conservation areas and identifying the realistic and precise species distribution model reflecting local characteristics.