전통숙박시설 선택속성, 만족도 및 행동의도 차이분석: 경주 수오재 방문객을 중심으로

방영근,부숙진,조태영 한국호텔관광학회 2012 호텔관광연구 Vol.14 No.1

Researchers have determined selection attribute factors of traditional accommodation facilities. These were identified by studying visitors and the relationship of these factors based on traditional accommodation facilities, visitors' satisfaction and their revisiting intention. 187 questionnaires were collected from the visitors who visited the Suojae, the largest facility in Kyungjoo area which contributed to the results of the research and 180 was used for analysis. Different analyses were used to develop the results for this research. Factor analysis was conducted for identifying the selection attribute factors of traditional facilities. These confirmed the validity and reliability through the reliability analysis of items of each factor. ANOVA was used to determine the difference between visitors’ (gender, age and educational background) and, Duncan analysis for post optimality analysis. Results showed that only food influenced significantly in the gender, room facility, and convenience facility. The service and stability factors were extracted from the age, and subsidiary facilities and stability factors influenced significantly in the educational background. There were many factors which didn't influence the results of this study, as well as factors which influenced significantly to the visitors' satisfaction among the selection attribute factors. Furthermore, there should be more sophisticated further research to help conclude the test. This study would be helpful to the operators of traditional accommodation facility as well as academically because there were almost no research about it.

고택 숙박시설의 선택속성이 방문객의 만족도 및 행동의도에 미치는 영향

방영근,서태양 한국호텔관광학회 2010 호텔관광연구 Vol.12 No.4

This study was conducted to derive the selection attributes of Korean traditional house which selected as one of traditional life experience tourism that represent Korean tourism and should foster, and to find the factors which impacts visitor's satisfaction and behavioral intention. For the purpose of this study, data selected from 5 Korean traditional houses which had relatively many visitors and managed systematically, and analyzed impacts of visitor's selection attributes on satisfaction and behavioral intention by survey(n=255). As a results of factor analysis on selection attributes of Korean traditional house, it showed that 5 factors(cultural traditionality, room facility, IT service, food, accessibility) had significant impact, but 4 factors(subsidiary facilities, convenience facility, manager and public service, stability) were rejected. Also, satisfaction of Korean traditional house had significant impact on intention of revisit and recommendation. In this study, unique experience and atmosphere that would feel in the Korean traditional house which was dwelled ancestor's traditional culture had significant impact on satisfaction and behavioral intention of Korean traditional house experience tourism which recognized by visitors, and the implications would be helpful to understand visitor’s recognition.

시계열 예측을 위한 이동평균 변화율 기반 퍼지 시스템 TSK

방영근,이철희 대한전기학회 2020 전기학회논문지 Vol.69 No.3

It is very difficult for nonstationary or nonlinear time series to establish a proper prediction model. In this paper, we propose a TSK FPS that uses the rate of change of MA of data as the predictor input. The LPF property of the MA stabilizes statistical characteristics of time series and the rate of change of them removes the monotonic increasing/decreasing tendency of the data, thereby overcoming the rule bias of the data. For the fuzzy partitioning of input space, CBKM using the correlation coefficient as the similarity index is applied. As a result, more appropriate rules to the attribute of data can be obtained. In order to verify the validity of the proposed method, simulations were performed on representative cases of nonstationary and nonlinear time series, respectively. The result of the simulation shows excellent performance and effectiveness of the proposed method.

진행성위암의 내시경적 관찰

방영근,김두경,송환규,권녕걸,황영실,박노춘,량웅석 大韓消化器病學會 1981 大韓消化器病學會誌 Vol.13 No.1

2 LERP IT2TSK 차 추세 차분형 기반 퍼지 예측시스템 설계 및 전력부하 예측

방영근,이철희 대한전기학회 2020 전기학회논문지 Vol.69 No.8

This paper deals with the electric power load prediction system. The first step is, in original data, making of additional information necessary to the system design by using the linear interpolation method. Next is generating the valid input data in which the rapidly increasing trend is mitigated by the 2nd order trend difference method. Final step is designing the IT2TSK fuzzy prediction system that can properly handle the uncertainty involved in the generated data. To design IT2TSK fuzzy prediction system, IT2 fuzzy sets, K-means clustering algorithm, and least square method are used individually for expressing the footprint of uncertainty, tuning the IT2 fuzzy sets, and identifying the parameters of TSK regressive model. In simulation, the performance and effectiveness of the proposed system are verified by comparing with other system after analyzing the prediction results of two types of electric power load data.

FS-RS를 이용한 가스 식별 시스템의 설계

방영근,심재선,박하용,이철희 대한전기학회 2012 대한전기학회 학술대회 논문집 Vol.2012 No.7

HCBKA를 이용한 Interval Type-2 퍼지 논리시스템 기반 예측 시스템 설계

방영근,이철희 江原大學校 産業技術硏究所 2010 産業技術硏究 Vol.30 No.A

To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2 TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1 Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlationship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

진행성위암의 (進行性胃癌) 내시경적 (內視鏡的) 관찰

방영근,김두경,송환규,권영걸,황영실,박노춘,양웅석 ( Young Keun Bang,Doo Kyung Kim,Hwan Kyu Song,Young Girl Kweon,Young Sil Hwang,Noh Choon Park ) 대한소화기학회 1981 대한소화기학회지 Vol.13 No.1

A clinical analysis was done among 211 cases of advanced stomach cancer which had been confirmed with gastrofiberscopy for 3 years from May, 1977 to September, 1980 at the Depart- ment of Internal Medicine, Yvallace Memorial Baptist Hospital, Busan, Korea The following results were obtained; 1. Among the 211 cases of advanced stomach cancer, 145 cases(68. 72%) were male and 66 cases(31.27%) were female. The ratio of male to female was 2. 2: l. 2. The peak age incidence was in the 5 th decade with 73 cases(34. 59%) and next came the 4 th decade with 54 cases(25, 59%), the 6 th decade with 40 cases(18. 95%) and the 3 rd decade with 27 cases(12. 79%). 3. Among the 173 cases of advanced stomach cancer, 62 cases(35. 83%) were confined to the body of stomach which was the most prevalent site and next came 55 cases(31. 79%) in antrum, 30 cases(17. 34po) in both antrum and body, and 7 cases(4. 04%) in angulus. On the other hand, among the 137 cases, 71 cases(51. 82%) were confined to lesser curvature which was the most prevalent site, and next came 28 cases(20.43%) in greater curvature, 25 cases (18. 24%) in posterior wall, and 13 cases(9. 48%) in anterior wall viewing the stomach laterally. 4. As for the Borrmanns classification in 187 cases, the most frequent was type g with 83 cases and next came type IV with 40 cases, type ]I with 29 cases and type [ with 25 cases in the order. 5 As for the UGI roentgenographic study in 139 cases, stomach cancer was found in 115 cases(82. 73%), benign gastric ulcer in 9 cases(6 47%), gastritis in 6 cases(4. 31%) and norm- al findings in 6 cases(4. 31%). 6. As for the gastrofiberscopic biopsy done in 144 cases, 104 cases(72. 2%) were positive for cancer cell and 40 cases were negative for cancer cell(27. 77%).

가스 식별 시스템 설계를 위한 유전알고리즘과 퍼지시스템 적용에 관한 연구

방영근,조해파,이철희,Bang, Young-Keun,Haibo, Zhao,Lee, Chul-Heui 강원대학교 산업기술연구소 2011 産業技術硏究 Vol.31 No.2

Recently, machine olfactory systems that have been proposed as an artificial substitute of the human olfactory system are being studied by many researchers because they can scent dangerous gases and identify the type of gases in contamination areas instead of the human. In this paper, we present an effective design method for the gas identification system. The design method adopted the sequential combination between genetic algorithms and TSK fuzzy logic system. First, the proposed method allowed the designed gas identification system effectively performing the pattern analysis because it was able to avoid the curse of dimensionality caused by use of a large number of sensors. Secondly, the method led the gas identification system to good performance because it was able to deal with drift characteristics of the sensor data by using description ability of the fuzzy system for nonlinear data. In simulation, we demonstrated the effectiveness of the designed gas identification system by using the simulation results of five types of gases.

RCGKA를 이용한 최적 퍼지 예측 시스템 설계

방영근,심재선,이철희 江原大學校 産業技術硏究所 2009 産業技術硏究 Vol.29 No.B

In the case of traditional binary encoding technique, it takes long time to converge the optimal solutions and brings about complexity of the systems due to encoding and decoding procedures. However, the ROGAs (real-coded genetic algorithms) do not require these procedures, and the k-means clustering algorithm can avoid global searching space. Thus, this paper proposes a new approach by using their advantages. The proposed method constructs the multiple predictors using the optimal differences that can reveal the patterns better and properties concealed in non- stationary time series where the k-means clustering algorithm is used for data classification to each predictor, then selects the best predictor. After selecting the best predictor, the cluster centers of the predictor are tuned finely via RCGKA in secondary tuning procedure. Therefore, performance of the predictor can be more enhanced. Finally, we verifies the prediction performance of the proposed system via simulating typical time series examples.