• Title/Summary/Keyword: Predicting Patterns

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A Study on the Time Series Analysis of the Actual Unit Cost based on the Bid Prices (시계열을 이용한 실적단가 예측방안에 관한 연구)

  • Park, Won-Young;Seo, Jong-Won;Kang, Sang-Hyeok;Choi, Bong-Joon
    • Korean Journal of Construction Engineering and Management
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    • v.10 no.4
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    • pp.50-57
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    • 2009
  • The Korea Standard of Estimate which has been used as the only basis of Cost estimate of public construction projects is failed to reflect the fluctuation of current construction cost. Therefore, the government decided to gradually introduce historical construction cost into cost estimate of public construction projects from 2004 and to reduce the use of Korean Standard of Estimate. This paper presents a series of process and the methodology for computing Actual Cost and analyzing the fluctuation patterns based on not only previous contract prices which made a successful bid but also all of the other bid prices. Also, this paper mainly handles a device for extracting strategic bid price such as low price bid for assuring reliable data and for predicting the construction cost which is built by Wavelet Analysis of Time series Analysis data and Neural Network. It is anticipated that the effective use of the proposed process for estimating actual unit cost would make the cost estimation more current and reasonable.

The Model Predicting Unqualified Dental Practitioners Experience Pattern (치과 무면허 불법시술 경험 패턴 연구 : 2006 국민 구강건강 실태조사 자료)

  • Kim, E.Y.;Lim, K.O.;Ham, S.W.;Park, R.W.
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.10
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    • pp.3839-3845
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    • 2010
  • In this study, the patterns of people who get dental services from unqualified dental practitioners were identified by using "2006 National Dental Health Investigation". There were 4,543 people in total and the group was divided into two groups - those who had experience of receiving dental services from unqualified practitioners and of those who had not. The most pattern model was CHAID. It was patterned that 39% of those who are more than 68 years would experience such unqualified dental service, and it was found that 3% of those who are less than 33 years experienced such a service. It was found that 45% of those who are 55 or 68 years and woman would experience such unqualified dental service, and 32% of those who are 55 or 68 years and man experienced such a service. With the increase in health awareness, the burden of medical bills is also rising. However, cases of unqualified dental treatments that could cause extremely dangerous symptoms are also rising recently. Therefore it is most important to anticipate those groups who are most exposed to unqualified dental services, and educate them with appropriate information and publicise about the danger.

A Study on the Construction of Database, Online Management System, and Analysis Instrument for Biological Diversity Data (생물다양성 자료의 데이터베이스화와 온라인 관리시스템 및 분석도구 구축에 관한 연구)

  • Bec Kee-Yul;Jung Jong-Chul;Park Seon-Joo;Lee Jong-Wook
    • Journal of Environmental Science International
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    • v.14 no.12
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    • pp.1119-1127
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    • 2005
  • The management of data on biological diversity is presently complex and confusing. This study was initiated to construct a database so that such data could be stored in a data management, and analysis instrument to correct the problems inherent in the current incoherent storage methods. MySQL was used in DBMS(DataBase Management System), and the program was basically produced using Java technology Also, the program was developed so people could adapt to the requirements that are changing every minute. We hope this was accomplished by modifying easily and quickly the advanced programming technology and patterns. To this end, an effective and flexible database schema was devised to store and analyze diversity databases. Even users with no knowledge of databases should be able to access this management instrument and easily manage the database through the World Wide Web. On a basis of databases stored in this manner, it could become routinely used for various databases using this analysis instrument supplied on the World Wide Web. Supplying the derived results by using a simple table and making results visible using simple charts, researchers could easily adapt these methods to various data analyses. As the diversity data was stored in a database, not in a general file, this study makes the precise, error-free and high -quality storage in a consistent manner. The methods proposed here should also minimize the errors that might appear in each data search, data movement, or data conversion by supplying management instrumentation on the Web. Also, this study was to deduce the various results to the level we required and execute the comparative analysis without the lengthy time necessary to supply the analytical instrument with similar results as provided by various other methods of analysis. The results of this research may be summerized as follows: 1)This study suggests methods of storage by giving consistency to diversity data. 2)This study prepared a suggested foundation for comparative analysis of various data. 3)It may suggest further research, which could lead to more and better standardization of diversity data and to better methods for predicting changes in species diversity.

An Electric Load Forecasting Scheme for University Campus Buildings Using Artificial Neural Network and Support Vector Regression (인공 신경망과 지지 벡터 회귀분석을 이용한 대학 캠퍼스 건물의 전력 사용량 예측 기법)

  • Moon, Jihoon;Jun, Sanghoon;Park, Jinwoong;Choi, Young-Hwan;Hwang, Eenjun
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.10
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    • pp.293-302
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    • 2016
  • Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

Analysis of the Spatial Distribution of Total Phosphorus in Wetland Soils Using Geostatistics (지구통계학을 이용한 습지 토양 중 총인의 공간분포 분석)

  • Kim, Jongsung;Lee, Jungwoo
    • Journal of Korean Society of Environmental Engineers
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    • v.38 no.10
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    • pp.551-557
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    • 2016
  • Fusing satellite images and site-specific observations have potential to improve a predictive quality of environmental properties. However, the effect of the utilization of satellite images to predict soil properties in a wetland is still poorly understood. For the reason, block kriging and regression kriging were applied to a natural wetland, Water Conservation Area-2A in Florida, to compare the accuracy improvement of continuous models predicting total phosphorus in soils. Field observations were used to develop the soil total phosphorus prediction models. Additionally, the spectral data and derived indices from Landsat ETM+, which has 30 m spatial resolution, were used as independent variables for the regression kriging model. The block kriging model showed $R^2$ of 0.59 and the regression kriging model showed $R^2$ of 0.49. Although the block kriging performed better than the regession kriging, both models showed similar spatial patterns. Moreover, regression kriging utilizing a Landsat ETM+ image facilitated to capture unique and complex landscape features of the study area.

Analysing the Relationship Between Tree-Ring Growth of Quercus acutissima and Climatic Variables by Dendroclimatological Method (연륜기후학적 방법에 의한 상수리나무의 연륜생장과 기후인자와의 관계분석)

  • Moon, Na Hyun;Sung, Joo Han;Lim, Jong Hwan;Park, Ko Eun;Shin, Man Yong
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.17 no.2
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    • pp.93-101
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    • 2015
  • This study was conducted to analyze the relationship between tree-ring growth of Quercus acutissima and climatic variables by dendroclimatological method. Annual tree-ring growth data of Quercus acutissima collected by the $5^{th}$ National Forest Inventory (NFI5) were organized to analyze the spatial distribution of the species growth pattern. To explain the relationship between tree-ring growth of Quercus acutissima and climatic variables, monthly temperature and precipitation data from 1950 to 2010 were compared with tree-ring growth data for each county. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, four clusters were identified. In addition, index chronology of Quercus acutissima for each cluster was produced through cross-dating and standardization procedures. The adequacy of index chronologies was tested using basic statistics such as mean sensitivity, auto correlation, signal to noise ratio, and expressed population signal of annual tree-ring growth. Response function analysis was conducted to reveal the relationship between tree-ring growth and climatic variables for each cluster. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of Quercus acutissima and for predicting changes in tree growth patterns caused by climate change.

Outlook on Blooming Dates of Spring Flowers in the Korean Peninsula under the RCP8.5 Projected Climate (신 기후변화시나리오 조건에서 한반도 봄꽃 개화일 전망)

  • Kim, Jin-Hee;Cheon, Jung-Hwa;Yun, Jin I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.15 no.1
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    • pp.50-58
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    • 2013
  • This study was carried out to evaluate the geospatial characteristics of blooming date migration in three major spring flowers across North and South Korea as influenced by climate change. A thermal time-based phenology model driven by daily maximum and minimum temperature was adjusted for the key parameters (i.e., reference temperature, chilling requirement, heating requirement) used for predicting blooming of forsythia, azaleas, and Japanese cherry. The model was run by the RCP 8.5 projected temperature outlook over the Korean Peninsula and produced the mean booming dates for the three climatological normal years in the future (2011-2040, 2041-2070, and 2071-2100) at a 12.5 km grid spacing. Comparison against the observed blooming date patterns in the baseline climate (1971-2000) showed that there will be a substantial acceleration in blooming dates of the three species, resulting in cherry booming in February and flowers of azaleas and forsythia found at the top of mountain Baikdu by the 2071-2100 period. Flowering dates of the three species in the near future (2011-2040) may be accelerated by 3-5 days at minimum and 10-11 days at maximum compared with that in the baseline period (1971-2000). Those values corresponding to the middle future (2041-2070) can be from a minimum of 9-11 days to a maximum of 23-24 days. Blooming date of Japanese cherry can be accelerated by 26 days on average for the far future (2071-2100). The acceleration seems more prominent at islands and coastal plain areas than over inland mountainous areas.

Analysis of drought propagation using hydrometeorological data: from meteorological drought to agricultural drought (수문기상 정보를 이용한 가뭄 전이 분석: 기상학적 가뭄에서 농업적 가뭄)

  • Yu, Myungsu;Cho, Younghyun;Kim, Tae-Woong;Chae, Hyo-Sok
    • Journal of Korea Water Resources Association
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    • v.51 no.3
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    • pp.195-205
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    • 2018
  • Drought is a complex phenomenon caused by various factors which can be classified into natural and anthropogenic causes. In Korea, the natural drought typically occurs when the high pressure of the Pacific Ocean develops rapidly or becomes stronger than usual in summer, resulting in a short-lived monsoon season. Drought also can be classified into meteorological, agricultural, hydrological, and socioeconomic drought depending on the development process and consequences. Each type of droughts can influence the other drought types directly or indirectly. Drought propagation refers a phenomenon that changes from meteorological drought to agricultural or hydrological drought. In this study, the occurrence and patterns of drought propagation are evaluated. The relationship between meteorological and agricultural droughts was assessed using hydrometeorological data. We classified the types of drought into five categories to evaluate the occurrence and characteristics of drought propagation. As results, we found drought propagation did not occur or delayed until three months, depending on the type of drought. The further generalized relationship of drought propagation is expected to be used for predicting agricultural drought from the preceding meteorological drought.

Numerical Analysis on Cutting Power of Disc Cutter with Joint Distribution Patterns (절리분포 양상에 따른 디스크커터의 절삭력에 관한 수치해석적 연구)

  • Lee, Seung-Joong;Choi, Sung-O.
    • Tunnel and Underground Space
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    • v.21 no.3
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    • pp.151-163
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    • 2011
  • The LCM test is one of the most powerful and reliable methods for designing the disc cutter and for predicting the TBM (Tunnel Boring Machine) performance. It has an advantage to predict the actual load on disc cutter from the laboratory test on the real-size large rock samples, however, it also has a disadvantage to transport and/or prepare the large rock samples and to need an extra cost for experiment. Moreover it is not easy to execute the test for jointed rock mass, and sometimes the design model estimated from the test can not be applied to the real design of disc cutter. In order to break this critical point, lots of numerical studies have been performed. PFC2D can simulate crack propagation and rock fragmentation effectively, because it is useful in particle flow analysis. Consequently, in this study, the PFC2D has been adopted for numerical analysis on cutting power of disc cutter according to the different angle of joint, the different direction of joint, and the different space of joint with jointed rock mass models. From the numerical analyses, it was concluded that the bigger cutting power of disc cutter was needed for reverse cutting direction to joint rather than for forward direction, and the cutting power of disc cutter was increased with decreasing the dip angle of joint and decreasing the space of joints in reverse cutting direction. The more precise numerical model for disc cutter can be developed from comparison between the numerical results and LCM test results, and the resonable guideline is expected for prediction of TBM performance and disc cutter.

Development of Homogeneous Road Section Determination and Outlier Filter Algorithm (국도의 동질구간 선정과 이상치 제거 방법에 관한 연구)

  • Do, Myung-Sik;Kim, Sung-Hyun;Bae, Hyun-Sook;Kim, Jong-Sik
    • Journal of Korean Society of Transportation
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    • v.22 no.7 s.78
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    • pp.7-16
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    • 2004
  • The homogeneous road section is defined as one consisted of similar traffic characteristics focused on demand and supply. The criteria, in the aspect of demand, are the diverging rate and the ratio of green time to cycle time at signalized intersection, and distance between the signalized intersections. The criteria, in that or supply, are the traffic patterns such as traffic volume and its speed. In this study, the effective method to generate valuable data, pointing out the problems of removal method of obscure data, is proposed using data collected from Gonjiam IC to Jangji IC on the national highway No.3. Travel times are collected with licence matching method and traffic volume and speed are collected from detectors. Futhermore, the method of selecting homogeneous road section is proposed considering demand and supply aspect simultaneously. This method using outlier filtering algorithm can be applied to generate the travel time forecasting model and to revise the obscured of missing data transmitting from detectors. The point and link data collected at the same time on the rational highway can be used as a basis predicting the travel time and revising the obscured data in the future.