• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.107-110
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• 1991

When the noise has both additive and signal-dependent components, locally optimum detector test statistics are obtained for detection of weak composite signals using the generalized Neyman-Pearson lemma. In order to consider the non-additive noise as well as purely-additive noise, a generalized observation model is used in this paper. The locally optimum detector test statistics are derived for several different cases according to the relative strengths of the known signal component, the random signal component, and the signal-dependent noise component. Schematic diagrams of the locally optimum detector structures are also included.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.19-43
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• 2011

Tuning the architecture of SVM (support vector machine) is to build an SVM model of better performance. Two different tuning methods of the grid search and the GA (genetic algorithm) have been addressed in the literature, each of which has its own methodological pros and cons. This paper suggests a combined method for tuning the architecture of SVM models, which employs the GAM (generalized additive models), the grid search, and the GA in sequence. The GAM is used for selecting input variables, and the grid search and the GA are employed for finding optimal parameter values of the SVM models. Applying the method to a bankruptcy prediction problem, we show that SVM model tuned by the proposed method outperforms other SVM models.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1572-1581
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• 2022

Energy conversion to renewable energy is being promoted to solve the recently serious environmental pollution problem. Solar energy is one of the promising natural renewable energy sources. Compared to other energy sources, it is receiving great attention because it has less ecological impact and is sustainable. It is important to predict power generation at a future time in order to maximize the output of solar energy and ensure the stability and variability of power. In this paper, solar power generation data and sensor data were used. Using the PCC(Pearson Correlation Coefficient) analysis method, factors with a large correlation with power generation were derived and applied to the GAM(Generalized Additive Model). And the prediction accuracy of the power generation prediction model was judged. It aims to derive efficient solar power generation in the future and improve power generation performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.11
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• pp.955-961
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• 1990

Test statistics are obtained for detection of weak signals in signal-dependent noise using rank statistics. A generalized model is used in this paper in order to consider non-additivenoise as well as purely-additive noise. Locally optimum rank detectors for the model are shown to have similarity to locally optimum detectors and to be generalizations of these for the purely-additive noise model. A similar result is obtained for multi-input cases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.4
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• pp.332-339
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• 1988

Using a generalized observation model, in which one can express the effects of non-additive noise such as signal-dependent noise and multiplicative noise in addition to purely-additive noise, the problem of weak random-signal detection is investigated. It is shown that the test statistics of locally optimum detectors for detection of weak random signals in signal-dependent noise model are interesting extensions of those in purely-additive noise model. This result is a complement to the result for weak random-signal detction in multiplicative noise model.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.61-70
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• 2020

To estimate the ventilation volume of mechanically ventilated swine farms, various regression models were applied, and errors were compared to select the regression model that can best simulate actual data. Linear regression, linear spline, polynomial regression (degrees 2 and 3), logistic curve, generalized additive model (GAM), and gompertz curve were compared. Overfitting models were excluded even when the error rate was small. The evaluation criteria were root mean square error (RMSE) and mean absolute percentage error (MAPE). The evaluation results indicated that degree 3 exhibited the lowest error rate; however, an overestimation contradiction was observed in a certain section. The logistic curve was the most stable and superior to all the models. In the estimation of ventilation volume by all of the models, the estimated ventilation volume of the logistic curve was the smallest except for the model with a large error rate and the overestimated model.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.11-18
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• 2012

Increasing concern about biodiversity has lead to a rise in demand on the spatial assessment of biological resources such as biodiversity assessment, protected area selection, habitat management and restoration in Korea. The purpose of this study is to create species richness map through data collection and modeling techniques for wildlife habitat assessment. The GAM (Generalized Additive Model) is easy to interpret and shows better relationship between environmental variables and a response variable than an existing overlap analysis and GLM (Generalized Linear Model). The study area delineated by a large watershed contains Jirisan national park, Mt. Baekun and Sumjin river with three kinds of protected areas (a national park, a landscape ecology protected area and an otter protected area). We collected the presence-absence data for wildlife (mammals and birds) using a stratified random sampling based on a land cover in the study area and implemented natural and socio-environmental data affecting wildlife habitats. After doing a habitat use analysis and specifying significant factors for each species, we built habitat suitability models using a presence-absence model and created habitat suitability maps for each species. Biodiversity maps were generated by taxa and all species using habitat suitability maps. Significant factors affecting each species habitat were different according to their habitat selection. Although some species like a water deer or a great tit were distributed at the low elevation, most potential habitats for mammals and birds were found at the edge of a national park boundary or near a forest around the medium elevation of a mountain range. This study will be used for a basis on biodiversity assessment and proected area selection carried out by Ministry of Environment.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1215-1227
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• 2009

Underwriting refers to the process that the insurance company measures the potential risk of the future clients and decide whether insuring them with current premium. Although the traditional underwriting system used in Korean automobile insurance market is easy to understand, it is not based on a reliable statistical procedure. In this paper, we propose to apply the generalized additive model into construction of underwriting system, which is based on statistical analysis. We use automobile insurance data in Korea and apply our approach to the data. The results from the empirical analysis would be useful even for determining the significance of each variable in calculating automobile insurance premium.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.265-274
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• 2000

Relationship between the daily mortality and total suspended particulate(TSP) for the period of 1996-1997 was examined in Seoul, Korea. Generalized additive model was adapted for the analysis to allow the seasonality and long-term time effect in the air pollution and the nonlinear relationships with weather variables such as air temperature and relative humidity. An increase of 100 Ji9/m') TSP corresponds to 0.8-5.2 percent increase of the daily mortality Unidirectional (prospective and retrospective) case-crossover design results in large bias of the estimates. Bidirectional method gives relatively unbiased estimates but the standard errors are larger Case-crossover design should be used with caution in the situation where the data have seasonal trends like air pollution study.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.509-518
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• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.