• 제목/요약/키워드: Tree Modeling

검색결과 337건 처리시간 0.022초

Tree species migration to north and expansion in their habitat under future climate: an analysis of eight tree species Khyber Pakhtunkhwa, Pakistan

  • Muhammad Abdullah Durrani;Rohma Raza;Muhammad Shakil;Shakeel Sabir;Muhammad Danish
    • Journal of Ecology and Environment
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    • 제48권1호
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    • pp.96-109
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    • 2024
  • Background: Khyber Pakhtunkhwa government initiated the Billion Tree Tsunami Afforestation Project including regeneration and afforestation approaches. An effort was made to assess the distribution characteristics of afforested species under present and future climatic scenarios using ecological niche modelling. For sustainable forest management, landscape ecology can play a significant role. A significant change in the potential distribution of tree species is expected globally with changing climate. Ecological niche modeling provides the valuable information about the current and future distribution of species that can play crucial role in deciding the potential sites for afforestation which can be used by government institutes for afforestation programs. In this context, the potential distribution of 8 tree species, Cedrus deodara, Dalbergia sissoo, Juglans regia, Pinus wallichiana, Eucalyptus camaldulensis, Senegalia modesta, Populus ciliata, and Vachellia nilotica was modeled. Results: Maxent species distribution model was used to predict current and future distribution of tree species using bioclimatic variables along with soil type and elevation. Future climate scenarios, shared socio-economic pathways (SSP)2-4.5 and SSP5-8.5 were considered for the years 2041-2060 and 2081-2100. The model predicted high risk of decreasing potential distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios for years 2041-2060 and 2081-2100, respectively. Recent afforestation conservation sites of these 8 tree species do not fall within their predicted potential habitat for SSP2-4.5 and SSP5-8.5 climate scenarios. Conclusions: Each tree species responded independently in terms of its potential habitat to future climatic conditions. Cedrus deodara and P. ciliata are predicted to migrate to higher altitude towards north in present and future climate scenarios. Habitat of D. sissoo, P. wallichiana, J. regia, and V. nilotica is practiced to be declined in future climate scenarios. Eucalyptus camaldulensis is expected to be expanded its suitability area in future with eastward shift. Senegalia modesta habitat increased in the middle of the century but decreased afterwards in later half of the century. The changing and shifting forests create challenges for sustainable landscapes. Therefore, the study is an attempt to provide management tools for monitoring the climate change-driven shifting of forest landscapes.

연속 어휘 인식 시스템에서 어휘 클러스터링 모델의 성능 지원을 위한 검색 시스템 (Retrieve System for Performance support of Vocabulary Clustering Model In Continuous Vocabulary Recognition System)

  • 오상엽
    • 디지털융복합연구
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    • 제10권9호
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    • pp.339-344
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    • 2012
  • 기존의 연속 어휘 인식 시스템에서는 의사 결정 트리 기반 공유 모델링 방법을 사용하여 인식률 향상 시킬 수 있었으나 이들 음소 데이타에 대한 검색을 지원할 수 없는 문제로 인해 시스템 모델의 정확성을 확보하지 못한다는 단점이 있다. 이를 개선하기 위하여 연속 어휘 클러스터링 모델에서 음소 단위로 확률 모델을 검색할 수 있는 시스템을 모델링하였다. 본 논문에서 제안한 시스템을 적용한 결과 시스템 성능에서 95.88%의 인식률을 나타내었다.

THRESHOLD MODELING FOR BIFURCATING AUTOREGRESSION AND LARGE SAMPLE ESTIMATION

  • Hwang, S.Y.;Lee, Sung-Duck
    • Journal of the Korean Statistical Society
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    • 제35권4호
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    • pp.409-417
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    • 2006
  • This article is concerned with threshold modeling of the bifurcating autoregressive model (BAR) originally suggested by Cowan and Staudte (1986) for tree structured data of cell lineage study where each individual $(X_t)$ gives rise to two off-spring $(X_{2t},\;X_{2t+1})$ in the next generation. The triplet $(X_t,\;X_{2t},\;X_{2t+1})$ refers to mother-daughter relationship. In this paper we propose a threshold model incorporating the difference of 'fertility' of the mother for the first and second off-springs, and thereby extending BAR to threshold-BAR (TBAR, for short). We derive a sufficient condition of stationarity for the suggested TBAR model. Also various inferential methods such as least squares (LS), maximum likelihood (ML) and quasi-likelihood (QL) methods are discussed and relevant limiting distributions are obtained.

신규 가입자망 기술의 경제성 평가를 위한 망 구조모형과 그 응용 (Modeling of Access Networks and Applications for the Economics of New Access Network Technology)

  • 류태규;이정동;김태유
    • 기술혁신학회지
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    • 제4권2호
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    • pp.157-171
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    • 2001
  • This paper discusses the economics of local loop architecture focusing on existing technologies, ADSL, HFC, and new one, PLC, and suggests a new modeling approach of access network system and the numerical equations. To modelize access network system and drive the numerical equations, we consider the double star and the tree & branch architecture and made block diagram of each access system. In addition, we introduce the density of subscriber as a variable and the equation of seeking the optimal number of cell in a service area. The economics of local loop architecture is analyzed in two ways, i.e. with and without consideration of the cost of cable and infrastructure. From the numerical analysis, we find that in case of not including the cost of cable and infrastructure, there is no much difference in the cost per one subscriber, while, in case of including it, there is remarkable difference among technologies. Therefore we conclude that the economics of local loop architecture is depend on the density of subscriber and existing network infrastructures.

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Implementation of the virtual reforestation system using spatial data

  • Kim Sung-Jae;Jo Myung-Hee;Kim Joon-Bum;Lee Myung-Bo;Lim Joo-Hoon
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.77-80
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    • 2004
  • In this study the spatial distribution characters of burnt forest site was first considered by analyzing spatial data and monitoring forest landscape before/after lire to restore the site. Then suitable tree species on each forest site should be selected through the weighted score analysis of GIS analysis methods. Finally. the best forest stand arrangement method could be simulated on the system for the advanced reforestation technology in Korea. For this purpose, the virtual reforestation system was implemented by using the concept of virtual GIS and CBD (Component Based Development) method. By use of this system the change of forest landscape of burnt forest area some years after reforestation practice could be detected and monitored by applying the site index and 3D modeling method.

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시간 공간 통합 본원적 데이터 모델링 및 그 구현에 관한 연구 (Modeling and Implementation for Generic Spatio-Temporal Incorporated Information)

  • 이우기
    • Journal of Information Technology Applications and Management
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    • 제12권1호
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    • pp.35-48
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    • 2005
  • An architectural framework is developed for integrating geospatial and temporal data with relational information from which a spatio-temporal data warehouse (STDW) system is built. In order to implement the STDW, a generic conceptual model was designed that accommodated six dimensions: spatial (map object), temporal (time), agent (contractor), management (e.g. planting) and tree species (specific species) that addressed the 'where', 'when', 'who', 'what', 'why' and 'how' (5W1H) of the STDW information, respectively. A formal algebraic notation was developed based on a triplet schema that corresponded with spatial, temporal, and relational data type objects. Spatial object structures and spatial operators (spatial selection, spatial projection, and spatial join) were defined and incorporated along with other database operators having interfaces via the generic model.

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혼합 데이터 마이닝 기법인 불일치 패턴 모델의 특성 연구 (Characteristics on Inconsistency Pattern Modeling as Hybrid Data Mining Techniques)

  • 허준;김종우
    • Journal of Information Technology Applications and Management
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    • 제15권1호
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    • pp.225-242
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    • 2008
  • PM (Inconsistency Pattern Modeling) is a hybrid supervised learning technique using the inconsistence pattern of input variables in mining data sets. The IPM tries to improve prediction accuracy by combining more than two different supervised learning methods. The previous related studies have shown that the IPM was superior to the single usage of an existing supervised learning methods such as neural networks, decision tree induction, logistic regression and so on, and it was also superior to the existing combined model methods such as Bagging, Boosting, and Stacking. The objectives of this paper is explore the characteristics of the IPM. To understand characteristics of the IPM, three experiments were performed. In these experiments, there are high performance improvements when the prediction inconsistency ratio between two different supervised learning techniques is high and the distance among supervised learning methods on MDS (Multi-Dimensional Scaling) map is long.

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A Semantic Content Retrieval and Browsing System Based on Associative Relation in Video Databases

  • Bok Kyoung-Soo;Yoo Jae-Soo
    • International Journal of Contents
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    • 제2권1호
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    • pp.22-28
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    • 2006
  • In this paper, we propose new semantic contents modeling using individual features, associative relations and visual features for efficiently supporting browsing and retrieval of video semantic contents. And we implement and design a browsing and retrieval system based on the semantic contents modeling. The browsing system supports annotation based information, keyframe based visual information, associative relations, and text based semantic information using a tree based browsing technique. The retrieval system supports text based retrieval, visual feature and associative relations according to the retrieval types of semantic contents.

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A Multi-Stage 75 K Fuzzy Modeling Method by Genetic Programming

  • Li Bo;Cho Kyu-Kab
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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    • pp.877-884
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    • 2002
  • This paper deals with a multi-stage TSK fuzzy modeling method by using Genetic Programming (GP). Based on the time sequence of sampling data the best structural change points of complex systems are detemined by using GP, and also the moving window is simultaneously introduced to overcome the excessive amount of calculation during the generating procedure of GP tree. Therefore, a multi-stage TSK fuzzy model that attempts to represent a complex problem by decomposing it into multi-stage sub-problems is addressed and its learning algorithm is proposed based on the Radial Basis Function (RBF) network. This approach allows us to determine the model structure and parameters by stages so that the problems ran be simplified.

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Dependency Structure Applied to Language Modeling for Information Retrieval

  • Lee, Chang-Ki;Lee, Gary Geun-Bae;Jang, Myung-Gil
    • ETRI Journal
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    • 제28권3호
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    • pp.337-346
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    • 2006
  • In this paper, we propose a new language model, namely, a dependency structure language model, for information retrieval to compensate for the weaknesses of unigram and bigram language models. The dependency structure language model is based on the first-order dependency model and the dependency parse tree generated by a linguistic parser. So, long-distance dependencies can be naturally captured by the dependency structure language model. We carried out extensive experiments to verify the proposed model, where the dependency structure model gives a better performance than recently proposed language models and the Okapi BM25 method, and the dependency structure is more effective than unigram and bigram in language modeling for information retrieval.

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