• 제목/요약/키워드: model trees

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상태 전이 모델 기반 결함 트리 분석 (Fault Tree Analysis based on State-Transition Model)

  • 정인상
    • 한국콘텐츠학회논문지
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    • 제11권10호
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    • pp.49-58
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    • 2011
  • 결함 트리 분석(Fault Tree Analysis)은 결함 트리를 구축하여 시스템의 안전성 분석을 수행한다. 그러나 결함 트리를 구성하는 작업은 대상 시스템의 도메인에 대한 지식과 경험을 필요로 하며 많은 시간과 노력을 소요한다. 이 논문에서는 시스템 설계 산출물인 상태 전이 모델을 기반으로 결함 트리를 체계적으로 구성하는 방법을 제안한다. 이를 위해 시스템 상태 전이 모델의 안정성 확보에 필요한 조건들을 식별하고 결함 트리를 구성할 수 있는 템플리트를 개발한다. 이 논문에서는 제안된 방법을 철도 건널목 제어 시스템에 적용한 결과도 기술한다.

데이터마이닝기법상에서 적합된 예측모형의 평가 -4개분류예측모형의 오분류율 및 훈련시간 비교평가 중심으로 (Evaluations of predicted models fitted for data mining - comparisons of classification accuracy and training time for 4 algorithms)

  • 이상복
    • Journal of the Korean Data and Information Science Society
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    • 제12권2호
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    • pp.113-124
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    • 2001
  • 의사결정나무모형 가운데 하나인 CHAID, 로지스틱 회귀모형, 이들을 이용한 각각의 베깅모형 등 4가지 예측분류모형에 대한 오분류율과 훈련시간을 표본크기별로 계산하고, 이들 모형에 대한 모의실험 비교를 통하여 주어진 알고리즘들의 효율성을 평가하였다. 베깅 의사결정나무모형은 오분류율은 낮았으나 상대적으로 훈련시간이 가장 길었다.

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Stand Structure of the Natural Broadleaved-Korean Pine Forests in Northeast China

  • Li, Fengri;Ma, Zhihai
    • 한국산림과학회지
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    • 제94권5호통권162호
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    • pp.321-329
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    • 2005
  • Based on the data representing four typical Korean pine forest types, the age structure, DBH distribution, species composition, and forking rule were systemically analyzed for old-growth Korean pine forest in Liangshui Nature Reserve, northeast China. The age structure of Korean pine trees was strongly uneven-aged with one dominated peak following normal distribution, and age of trees varied from 100 to 180 years within a stand. The DBH and height differences in same age class (20 years) varied from 28 cm~64 cm and 5 to 20 m, respectively. Many conifer and hard wood species, such as spruce, fir, costata birch, basswood, oak, and elm, were mixed with dominated trees of Korean pine. The canopy of the old-growth Korean pine forest can be divided into two layers, and differences of mean age and height between Layer I and Layer II were ranged 80~150 years and 7~13 m, respectively. The Weibull function was used to model the diameter distribution and performed well to describe size-class distribution either with a single peak in over-story canopy and inverse J-shape in under-story canopy for old-growth Korean pine stands. The forking height of Korean pine trees ranged from 16m to 24 m (mean 19.4 m) and tree age about 120 to 160 years old. The results will provide a scientific basis to protect and recover the ecosystem of natural old-growth Korean pine and also provide the model in management of Korean pine plantation.

Wind loading on trees integrated with a building envelope

  • Aly, Aly Mousaad;Fossati, Fabio;Muggiasca, Sara;Argentini, Tommaso;Bitsuamlak, Girma;Franchi, Alberto;Longarini, Nicola;Crespi, Pietro;Chowdhury, Arindam Gan
    • Wind and Structures
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    • 제17권1호
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    • pp.69-85
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    • 2013
  • With the sustainability movement, vegetated building envelopes are gaining more popularity. This requires special wind effect investigations, both from sustainability and resiliency perspectives. The current paper focuses on wind load estimation on small- and full-scale trees used as part of green roofs and balconies. Small-scale wind load assessment was carried out using a wind tunnel testing in a global-effect study to understand the interference effects from surrounding structures. Full-scale trees were investigated at a large open-jet facility in a local-effect study to account for the wind-tree interaction. The effect of Reynolds number combined with shape change on the overall loads measured at the base of the trees (near the roots) has been investigated by testing at different model-scales and wind speeds. In addition, high-speed tests were conducted to examine the security of the trees in soil and to assess the effectiveness of a proposed structural mitigation system. Results of the current research show that at relatively high wind speeds the load coefficients tend to be reduced, limiting the wind loads on trees. No resonance or vortex shedding was visually observed.

UAV 영상과 SfM 기술을 이용한 가로수의 탄소저장량 추정 (Estimation Carbon Storage of Urban Street trees Using UAV Imagery and SfM Technique)

  • 김다슬;이동근;허한결
    • 한국환경복원기술학회지
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    • 제22권6호
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    • pp.1-14
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    • 2019
  • Carbon storage is one of the regulating ecosystem services provided by urban street trees. It is important that evaluating the economic value of ecosystem services accurately. The carbon storage of street trees was calculated by measuring the morphological parameter on the field. As the method is labor-intensive and time-consuming for the macro-scale research, remote sensing has been more widely used. The airborne Light Detection And Ranging (LiDAR) is used in obtaining the point clouds data of a densely planted area and extracting individual trees for the carbon storage estimation. However, the LiDAR has limitations such as high cost and complicated operations. In addition, trees change over time they need to be frequently. Therefore, Structure from Motion (SfM) photogrammetry with unmanned Aerial Vehicle (UAV) is a more suitable method for obtaining point clouds data. In this paper, a UAV loaded with a digital camera was employed to take oblique aerial images for generating point cloud of street trees. We extracted the diameter of breast height (DBH) from generated point cloud data to calculate the carbon storage. We compared DBH calculated from UAV data and measured data from the field in the selected area. The calculated DBH was used to estimate the carbon storage of street trees in the study area using a regression model. The results demonstrate the feasibility and effectiveness of applying UAV imagery and SfM technique to the carbon storage estimation of street trees. The technique can contribute to efficiently building inventories of the carbon storage of street trees in urban areas.

원자력발전소의 화재사건 확률론적안전성평가 모델 구축에 관한 연구 (A Study on the Constructions of Fire Events Probabilistic Safety Assessment Model for Nuclear Power Plants)

  • 강대일;김길유
    • 한국안전학회지
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    • 제31권5호
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    • pp.187-194
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    • 2016
  • A single fire event within a fire area can cause multiple initiating events considered in internal events probabilistic safety assessment (PSA). For an example, a fire event in turbine building fire area can cause a loss of the main feed-water and loss of off-site power initiating events. This fire initiating event could result in special plant responses beyond the scope of the internal events PSA model. One approach to address a fire initiating event is to develop a specific fire event tree. However, the development of a specific fire event tree is difficult since the number of fire event trees may be several hundreds or more. Thus, internal fire events PSA model has been generally constructed by modifications of the pre-developed internal events PSA model. New accident sequence logics not covered in the internal events PSA model are separately developed to incorporate them into the fire PSA model. Recently, many fire PSA models have fire induced initiating event fault trees not shown in an internal event PSA model. Up to now, there has been no analytical comparative study on the constructions of fire events PSA model using internal events PSA model with and without fault trees of initiating events. In this study, the changing process of internal events PSA model to fire events PSA model is analytically presented and discussed.

Molecular Biology of Secondary Growth

  • Han, Kyung-Hwan
    • Journal of Plant Biotechnology
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    • 제3권2호
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    • pp.45-57
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    • 2001
  • Trees have the ability to undergo secondary growth and produce a woody body. This tree-specific growth is affected by the secondary vascular system and the developmental continuum of secondary phloem and xylem. Secondary growth is one of the most important biological processes on earth. Considering its economic and environmental significance, our knowledge of tree growth and development is surprisingly limited. Trees have received little attention as model species in plant science, as most Plant biology questions can be best addressed by using herbaceous model species, such as Arabidopsis. Furthermore, tree biology is difficult to study mainly due to the inherent problems of tree species, including large size, long generation time, large genome size, and recalcitrance to biotechnological manipulations. Despite all of this, one must rely on trees as models to study tree-specific questions, such as secondary growth, which cannot be studied effectively in non-woody model species. Recent advances in genomics technology provide a unique opportunity to overcome these inherent tree-related problems. Several groups, including our own, have been successful in studying the biology of wood formation with a variety of hardwood and softwood species. In this article, 1 first review the current understanding of tree growth and then discuss the recent attempts to fully explore and realize the potential of molecular biology as a tool for enhanced understanding of secondary growth.

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Prediction of Larix kaempferi Stand Growth in Gangwon, Korea, Using Machine Learning Algorithms

  • Hyo-Bin Ji;Jin-Woo Park;Jung-Kee Choi
    • Journal of Forest and Environmental Science
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    • 제39권4호
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    • pp.195-202
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    • 2023
  • In this study, we sought to compare and evaluate the accuracy and predictive performance of machine learning algorithms for estimating the growth of individual Larix kaempferi trees in Gangwon Province, Korea. We employed linear regression, random forest, XGBoost, and LightGBM algorithms to predict tree growth using monitoring data organized based on different thinning intensities. Furthermore, we compared and evaluated the goodness-of-fit of these models using metrics such as the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). The results revealed that XGBoost provided the highest goodness-of-fit, with an R2 value of 0.62 across all thinning intensities, while also yielding the lowest values for MAE and RMSE, thereby indicating the best model fit. When predicting the growth volume of individual trees after 3 years using the XGBoost model, the agreement was exceptionally high, reaching approximately 97% for all stand sites in accordance with the different thinning intensities. Notably, in non-thinned plots, the predicted volumes were approximately 2.1 m3 lower than the actual volumes; however, the agreement remained highly accurate at approximately 99.5%. These findings will contribute to the development of growth prediction models for individual trees using machine learning algorithms.

Development of K-Maryblyt for Fire Blight Control in Apple and Pear Trees in Korea

  • Mun-Il Ahn;Hyeon-Ji Yang;Sung-Chul Yun
    • The Plant Pathology Journal
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    • 제40권3호
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    • pp.290-298
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    • 2024
  • K-Maryblyt has been developed for the effective control of secondary fire blight infections on blossoms and the elimination of primary inoculum sources from cankers and newly emerged shoots early in the season for both apple and pear trees. This model facilitates the precise determination of the blossom infection timing and identification of primary inoculum sources, akin to Maryblyt, predicting flower infections and the appearance of symptoms on various plant parts, including cankers, blossoms, and shoots. Nevertheless, K-Maryblyt has undergone significant improvements: Integration of Phenology Models for both apple and pear trees, Adoption of observed or predicted hourly temperatures for Epiphytic Infection Potential (EIP) calculation, incorporation of adjusted equations resulting in reduced mean error with 10.08 degree-hours (DH) for apple and 9.28 DH for pear, introduction of a relative humidity variable for pear EIP calculation, and adaptation of modified degree-day calculation methods for expected symptoms. Since the transition to a model-based control policy in 2022, the system has disseminated 158,440 messages related to blossom control and symptom prediction to farmers and professional managers in its inaugural year. Furthermore, the system has been refined to include control messages that account for the mechanism of action of pesticides distributed to farmers in specific counties, considering flower opening conditions and weather suitability for spraying. Operating as a pivotal module within the Fire Blight Forecasting Information System (FBcastS), K-Maryblyt plays a crucial role in providing essential fire blight information to farmers, professional managers, and policymakers.

Total Wood Volume Equations for Tectona Grandis Linn F. Stands in Gujarat, India

  • Tewari, Vindhya Prasad;Singh, Bilas
    • Journal of Forest and Environmental Science
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    • 제34권4호
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    • pp.313-320
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    • 2018
  • Tectona grandis (teak) is one of the most important timber species worldwide and India is one of the major teak growing countries. Though some volume equations were developed for teak in India but the models developed were neither evaluated using robust statistical criteria nor validated. Hence, the objective of this study was to develop statistically tested appropriate volume equation to predict total wood volume (over- and under-bark) for teak trees in Gujarat. A total of 41 trees with age varying from 15 to 33 years and diameter at breast height (dbh) from 7.3 to 30.8 cm were felled for the purpose. Linear and non-linear equations were used to model the relationship of the total wood volume with respect to dbh and total height. The equations tested mostly fitted well to the data. Model evaluation and validation indicated that models should be calibrated with local data for greater accuracy in the prediction.