• Title/Summary/Keyword: 연속모형

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Rough Set Analysis for Stock Market Timing (러프집합분석을 이용한 매매시점 결정)

  • Huh, Jin-Nyung;Kim, Kyoung-Jae;Han, In-Goo
    • Journal of Intelligence and Information Systems
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    • v.16 no.3
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    • pp.77-97
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    • 2010
  • Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

Managerial Implication of Trails in the Teabaeksan National Park Derived from the Analysis of Visitors Behaviors Using Automatic Visitor Counter Data (탐방객 자동 계수기 데이터를 활용한 태백산국립공원 탐방로 탐방 행태 분석 및 관리 방안 제언)

  • Sung, Chan Yong;Cho, Woo;Kim, Jong-Sub
    • Korean Journal of Environment and Ecology
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    • v.34 no.5
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    • pp.446-453
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    • 2020
  • This study built a model to predict the daily number of visitors to 18 trails in the Taebaeksan National Park using the auto-counter system data to analyze the factors affecting the daily number of visitors to each trail and classified the trails by visitors' behaviors. Results of the multiple regression models with the daily number of visitors of the 18 trails indicated that the events, such as the National Foundation Day celebration of Snow Festival, affected the number of visitors of all of the 18 trails and were the most critical factor that determined the daily number of visitors to the Taebaeksan National Park. The long-holidays of three days or longer and other national holidays also affected the daily number of visitors to the trails. Precipitation had a negative impact on the number of visitors of trails where the intention of most visitors was for sightseeing or camping instead of hiking, whereas had no significant impacts on the number of visitors of trails where many visitors intended for hiking. It indicated that visitors who intended for hiking went ahead hiking even if the weather was poor. The effects of temperature had a positive effect on the number of visitors who intended for hiking but a negative effect on the number of visitor to the trails near Danggol Plaza where the Snow Festival was held in each winter, suggesting that the impact of the Snow Festival was the deterministic factor for trail management. Results of K-mean clustering showed that the 18 trails of the Taekbaeksan National Park could be classified into three types: those affected by the Snow Festival (type 1), those that have sightseeing points and so were visited mostly by non-hikers (type 2), and those visited mostly by hikers (type 3). Since visitor behaviors and illegal actions differ according to the trail type, this study's results can be used to prepare a trail management plan based on the trail characteristics.

Predicting hospital bankruptcy in Korea (병원도산 예측에 관한 연구)

  • Lee, Moo-Sik;Seo, Young-Joon
    • Journal of Preventive Medicine and Public Health
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    • v.31 no.3 s.62
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    • pp.490-502
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    • 1998
  • This study purports to find the predictor of hospital bankruptcy in Korea and to examine the predictive power of the discriminant function model of hospital bankruptcy. Data on 17 financial and 4 non-financial indicators of 31 bankrupt and 31 profitable hospitals of 1, 2, and 3 years before bankruptcy were obtained from the hospital performance databank of Korea Institute of Health Services Management. Significant variables were identified through mean comparison of each indicator between bankrupt and profitable hospitals, and the discriminant function model of hospital bankruptcy was developed. The major findings are as follows 1. As for profitability indicators, net worth to total assets, operating profit to total capital, operating profit ratio to gross revenues, normal profit to total assets, normal profit to gross revenues, net profit to total assets were significantly different in mean comparison test in 1, 2, and 3 years before hospital bankruptcy. With regard to liquidity indicators, current ratio and quick ratio were significant in 1 year before bankruptcy. For activity indicators, patients receivable turnover was significant in 2 and 3 years before bankruptcy and added value per adjusted inpatient days was significant in 3 years before bankruptcy. 2. The discriminant function in 1, 2, and 3 years before bankruptcy were; $Z=-0.0166{\times}quick$ ratio-$0.1356{\times}normal$ profit to total assets-$1.545{\times}total$ assets turnrounds in 1 year before bankruptcy, $Z=-0.0119{\times}quick$ ratio-$0.1433{\times}operating$ profit to total assets-$0.0227{\times}value$ added to total assets in 2 years before bankruptcy, and $Z=-0.3533{\times}net$ profit to total assets-$0.1336{\times}patients$ receivables turn-rounds-$0.04301{\times}added$ value per adjusted $patient+0.00119{\times}average$ daily inpatient census in 3 years before bankruptcy. 3. The discriminant function's discriminant power in 1, 2, and 3 years before bankruptcy was 77.42, 79.03, 82.25% respectively.

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Innovative Technology of Landfill Stabilization Combining Leachate Recirculation with Shortcut Biological Nitrogen Removal Technology (침출수 재순환과 생물학적 단축질소제거공정을 병합한 매립지 조기안정화 기술 연구)

  • Shin, Eon-Bin;Chung, Jin-Wook;Bae, Woo-Keun;Kim, Seung-Jin;Baek, Seung-Cheon
    • Journal of Korean Society of Environmental Engineers
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    • v.29 no.9
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    • pp.1035-1043
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    • 2007
  • A leachate containing an elevated concentration of organic and inorganic compounds has the potential to contaminate adjacent soils and groundwater as well as downgradient areas of the watershed. Moreover high-strength ammonium concentrations in leachate can be toxic to aquatic ecological systems as well as consuming dissolved oxygen, due to ammonium oxidation, and thereby causing eutrophication of the watershed. In response to these concerns landfill stabilization and leachate treatment are required to reduce contaminant loading sand minimize effects on the environment. Compared with other treatment technologies, leachate recirculation technology is most effective for the pre-treatment of leachate and the acceleration of waste stabilization processes in a landfill. However, leachate recirculation that accelerates the decomposition of readily degradable organic matter might also be generating high-strength ammonium in the leachate. Since most landfill leachate having high concentrations of nitrogen also contain insufficient quantities of the organic carbon required for complete denitrification, we combined a shortcut biological nitrogen removal (SBNR) technology in order to solve the problem associated with the inability to denitrify the oxidized ammonium due to the lack of carbon sources. The accumulation of nitrite was successfully achieved at a 0.8 ratio of $NO_2^{-}-N/NO_x-N$ in an on-site reactor of the sequencing batch reactor (SBR) type that had operated for six hours in an aeration phase. The $NO_x$-N ratio in leachate produced following SBR treatment was reduced in the landfill and the denitrification mechanism is implied sulfur-based autotrophic denitrification and/or heterotrophic denitrification. The combined leachate recirculation with SBNR proved an effective technology for landfill stabilization and nitrogen removal in leachate.

Studies on the utilization of sandy barren lands and sandy farm lands of low productivity -1. Studies on growing rice-plant in sandy barren lands (식량증산을 위한 유휴사지(遊休砂地) 및 사질계(砂質系) 농지(農地) 활용(活用)에 관한 기초적(基礎的) 연구(硏究) -1. 수도(水稻)의 사지재배(砂地栽培)에 관한 연구(硏究))

  • Kim, Yong Chul;Choe, Gyu Ho
    • Korean Journal of Soil Science and Fertilizer
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    • v.9 no.1
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    • pp.33-38
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    • 1976
  • As a basic studies for increasing food production utilizing sandy barren lands and sandy farmlands of low productivity which distributed widely in Korea, an experiment of growing rice-plant on sandy barren land was undertaken as follows. 1. Variety, IR-667 was adopted and the growing method was a nutrient-irrigation culture which aimed to minimize percolation loss in sand with an automatic contineous supplying nutrient solution for supplmenting the sand characteristics. 2. The growth type price-plant after heading was a typical higher yield plant, that is, numerous, small, narrow, and thickend leaves, straight attitute, dense fasciculated etc. though the rooting of plant after planting was delayed because of using paddy-field grown seedling. 3. The adaptability of rice-plants on sandy land seemed to be different by varieties and IR-667 was more adaptable than ordinary Japonica varieties. 4. Even at the period of heading and maturing, the root system of rice-plant grown on sand showed vigorous growth having more activated apical portions. while, even the lower leaves showed flourished state. 5. The suppling of calcium and magnecium in addition to nitrogen, phosphorus and potassium on sand made notable increase of stem number per plant, grain number per stem and yields.

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