• Title/Summary/Keyword: Demand-Based Tree

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Replica Update Propagation Using Demand-Based Tree for Weak Consistency in the Grid Database

  • Ge, Ruixuan;Jang, Yong-Il;Park, Soon-Young;Bae, Hae-Young
    • Journal of Korea Multimedia Society
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    • v.9 no.12
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    • pp.1542-1551
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    • 2006
  • In the Grid Database, some replicas will have more requests from the clients than others. A fast consistency algorithm has been presented to satisfy the high demand nodes in a shorter period of time. But it has poor performance in multiple regions of high demand for forming the island of locally consistent replicas. Then, a leader election method is proposed, whereas it needs much additional cost for periodic leader election, information storage, and message passing, Also, false leader can be created. In this paper, we propose a tree-based algorithm for replica update propagation. Leader replicas with high demand are considered as the roots of trees which are interconnected. All the other replicas are sorted and considered as nodes of the trees. Once an update occurs at any replica, it need be transmitted to the leader replicas first. Every node that receives the update propagates it to its children in the tree. The update propagation is optimized by cost reduction for fixed propagation schedule. And it is also flexible for the dynamic model in which the demand conditions change with time.

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Short-term demand forecasting Using Data Mining Method (데이터마이닝을 이용한 단기부하예측)

  • Choi, Sang-Yule;Kim, Hyoung-Joong
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.21 no.10
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    • pp.126-133
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    • 2007
  • This paper proposes information technology based data mining to forecast short term power demand. A time-series analyses have been applied to power demand forecasting, but this method needs not only heavy computational calculation but also large amount of coefficient data. Therefore, it is hard to analyze data in fast way. To overcome time consuming process, the author take advantage of universally easily available information technology based data-mining technique to analyze patterns of days and special days(holidays, etc.). This technique consists of two steps, one is constructing decision tree, the other is estimating and forecasting power flow using decision tree analysis. To validate the efficiency, the author compares the estimated demand with real demand from the Korea Power Exchange.

Prediction of the number of public bicycle rental in Seoul using Boosted Decision Tree Regression Algorithm

  • KIM, Hyun-Jun;KIM, Hyun-Ki
    • Korean Journal of Artificial Intelligence
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    • v.10 no.1
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    • pp.9-14
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    • 2022
  • The demand for public bicycles operated by the Seoul Metropolitan Government is increasing every year. The size of the Seoul public bicycle project, which first started with about 5,600 units, increased to 3,7500 units as of September 2021, and the number of members is also increasing every year. However, as the size of the project grows, excessive budget spending and deficit problems are emerging for public bicycle projects, and new bicycles, rental office costs, and bicycle maintenance costs are blamed for the deficit. In this paper, the Azure Machine Learning Studio program and the Boosted Decision Tree Regression technique are used to predict the number of public bicycle rental over environmental factors and time. Predicted results it was confirmed that the demand for public bicycles was high in the season except for winter, and the demand for public bicycles was the highest at 6 p.m. In addition, in this paper compare four additional regression algorithms in addition to the Boosted Decision Tree Regression algorithm to measure algorithm performance. The results showed high accuracy in the order of the First Boosted Decision Tree Regression Algorithm (0.878802), second Decision Forest Regression (0.838232), third Poison Regression (0.62699), and fourth Linear Regression (0.618773). Based on these predictions, it is expected that more public bicycles will be placed at rental stations near public transportation to meet the growing demand for commuting hours and that more bicycles will be placed in rental stations in summer than winter and the life of bicycles can be extended in winter.

Multicast Tree Generation using Meta Reinforcement Learning in SDN-based Smart Network Platforms

  • Chae, Jihun;Kim, Namgi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3138-3150
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    • 2021
  • Multimedia services on the Internet are continuously increasing. Accordingly, the demand for a technology for efficiently delivering multimedia traffic is also constantly increasing. The multicast technique, that delivers the same content to several destinations, is constantly being developed. This technique delivers a content from a source to all destinations through the multicast tree. The multicast tree with low cost increases the utilization of network resources. However, the finding of the optimal multicast tree that has the minimum link costs is very difficult and its calculation complexity is the same as the complexity of the Steiner tree calculation which is NP-complete. Therefore, we need an effective way to obtain a multicast tree with low cost and less calculation time on SDN-based smart network platforms. In this paper, we propose a new multicast tree generation algorithm which produces a multicast tree using an agent trained by model-based meta reinforcement learning. Experiments verified that the proposed algorithm generated multicast trees in less time compared with existing approximation algorithms. It produced multicast trees with low cost in a dynamic network environment compared with the previous DQN-based algorithm.

Short-term Water Demand Forecasting Algorithm Based on Kalman Filtering with Data Mining (데이터 마이닝과 칼만필터링에 기반한 단기 물 수요예측 알고리즘)

  • Choi, Gee-Seon;Shin, Gang-Wook;Lim, Sang-Heui;Chun, Myung-Geun
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.10
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    • pp.1056-1061
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    • 2009
  • This paper proposes a short-term water demand forecasting algorithm based on kalman filtering with data mining for sustainable water supply and effective energy saving. The proposed algorithm utilizes a mining method of water supply data and a decision tree method with special days like Chuseok. And the parameters of MLAR (Multi Linear Auto Regression) model are estimated by Kalman filtering algorithm. Thus, we can achieve the practicality of the proposed forecasting algorithm through the good results applied to actual operation data.

A Study of 2D Multimedia Content Generation using R* Tree Index (R* tree 인덱스를 이용한 2D 멀티미디어 컨텐츠 생성에 관한 연구)

  • Lee, Hyun-Chang;Han, Sung-Kook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.815-816
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    • 2009
  • Owing to the development of computer technologies, to process data derived from various sensors is recently demanding. It is also increasing to demand the moving object based servies like the services of location based and mobile application services. That's why it is needed the processing of visualizing the services for education aspects. In this paper, we show the implemented results about $R^*$ tree algorithm to insert, delete and search a object in two dimension environment.

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A Hierarchical Cluster Tree Based Address Assignment Method for Large and Scalable Wireless Sensor Networks (대규모 무선 센서 네트워크를 위한 계층적 클러스터 트리 기반 분산 주소 할당 기법)

  • Park, Jong-Jun;Jeong, Hoon;Hwang, So-Young;Joo, Seong-Soon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.12B
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    • pp.1514-1523
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    • 2009
  • It is well known that the current wireless sensor networks addressing methods do not work efficiently in networks more than a few hundred nodes. A standard protocol in ZigBee-Standard feature in ZigBee 2007 gives balanced tree based address assignment method with distributed manner. However, it was limited to cover less than hundreds of sensor nodes due to the wasteful use of available address space, because composed sensor networks usually make an unbalanced tree topology in the real deployment. In this paper, we proposed the hierarchical cluster tree based address assignment method to support large and scalable networks. This method provides unique address for each node with distributed manner and supports hierarchical cluster tree on-demand. Simulation results show that the proposed method reduces orphan nodes due to the address exhaustion and supports larger network with limited address space compared with the ZigBee distributed address assignment method defined in ZigBee-Standard feature in ZigBee 2007.

k-Interest Places Search Algorithm for Location Search Map Service (위치 검색 지도 서비스를 위한 k관심지역 검색 기법)

  • Cho, Sunghwan;Lee, Gyoungju;Yu, Kiyun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.4
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    • pp.259-267
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    • 2013
  • GIS-based web map service is all the more accessible to the public. Among others, location query services are most frequently utilized, which are currently restricted to only one keyword search. Although there increases the demand for the service for querying multiple keywords corresponding to sequential activities(banking, having lunch, watching movie, and other activities) in various locations POI, such service is yet to be provided. The objective of the paper is to develop the k-IPS algorithm for quickly and accurately querying multiple POIs that internet users input and locating the search outcomes on a web map. The algorithm is developed by utilizing hierarchical tree structure of $R^*$-tree indexing technique to produce overlapped geometric regions. By using recursive $R^*$-tree index based spatial join process, the performance of the current spatial join operation was improved. The performance of the algorithm is tested by applying 2, 3, and 4 multiple POIs for spatial query selected from 159 keyword set. About 90% of the test outcomes are produced within 0.1 second. The algorithm proposed in this paper is expected to be utilized for providing a variety of location-based query services, of which demand increases to conveniently support for citizens' daily activities.

New Strategy of Forest Tree Breeding for Society, Forest Science, and Forestry in Korea

  • Choi, Yong-Eui;Kim, Chul-Woo;Yi, Jae-Seon
    • Journal of Forest and Environmental Science
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    • v.24 no.1
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    • pp.15-25
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    • 2008
  • Social and scientific changes, i.e., global warming, desertification, pollution, biodiversity, bioenergy, plant variety protection, biotechnology, timber demand, reforestation in North Korea, and etc., were reviewed for new strategy of forest tree breeding in Korea. Diversified breeding goals, globalization of breeding target species, multidisciplinary research approaches, manpower networking, establishment of new administrative and research units in KFS and KFRI were proposed. Principles suggested for new tree breeding strategy are: 1) multi-disciplinary approach in settlement of objectives, breeding methods, and etc., 2) expansion of target trees including foreign species, 3) fulfillment of both domestic and international demands for forest tree breeding, 4) establishment of breeding program well-grounded on genetic resources conservation, 5) acknowledgement of breeding products (i.e., variety, technique, gene, and etc.) as goods, and 6) provision of more research opportunities for young scientists. Lastly, ongoing tree breeding project in Indonesia and NTFP R&D Center at the College of Forest and Environmental Sciences, Kangwon National University were introduced as examples of desirable breeding projects based on target species diversification, multidisciplinary approach, and manpower networking.

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Solving Nonlinear Fixed Charge Transportation Problem by Spanning Tree-based Genetic Algorithm (신장트리 기반 유전자 알고리즘에 의한 비선형 fcTP 해법)

  • Jo, Jung-Bok;Ko, Suc-Bum;Gen, Mitsuo
    • Journal of KIISE:Software and Applications
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    • v.32 no.8
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    • pp.752-758
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    • 2005
  • The transportation problem (TP) is known as one of the important problems in Industrial Engineering and Operational Research (IE/OR) and computer science. When the problem is associated with additional fixed cost for establishing the facilities or fulfilling the demand of customers, then it is called fixed charge transportation problem (fcTP). This problem is one of NP-hard problems which is difficult to solve it by traditional methods. This paper aims to show the application of spanning-tree based Genetic Algorithm (GA)approach for solving nonlinear fixed charge transportation problem. Our new idea lies on the GA representation that includes the feasibility criteria and repairing procedure for the chromosome. Several numerical experimental results are presented to show the effectiveness of the proposed method.