• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.261-264
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• 2001

This paper relates to a node structure of a multiway search tree and a search method using the node structure and, more particularly, to a search method for accelerating its search speed by reducing the depth of each small tree in a multi-way search tree. The proposed idea can increase the number of keys capable of being recorded on a cache line by using one pointer at a node of the multi-way search tree so that the number of branches in a network address search is also increased and thus the tree depth is reduced. As a result, this idea can accelerate the search speed and the speed of the forwarding engine and accomplish a further speed-up by decreasing required memories and thus increasing a memory rate.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.637-647
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• 2018

In this paper, we propose a method to search candidates of network reconfiguration to restore distribution system with distributed energy resources using a level-based tree search algorithm. First, we introduce a method of expressing distribution network with distributed energy resources for fault restoration, and to represent the distribution network into a simplified graph. Second, we explain the tree search algorithm, and introduce a method of performing the tree search on the basis of search levels, which we call a level-based tree search in this paper. Then, we propose a candidate search method for fault restoration, and explain it using an example. Finally, we verify the proposed method using computer simulations.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.315-332
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• 2013

This paper presents an approach for improving the use of VP-tree in video indexing and searching. A vantage-point tree or VP-tree is one of the metric space-based indexing methods used in multimedia database searches and data retrieval. Instead of relying on the Euclidean distance as a measure of search space, the proposed approach focuses on the trigonometric inequality for compressing the search range, which thus, improves the search performance. A test result of using 10,000 video files shows that this method reduced the search time by 5-12%, as compared to the existing method that uses the AESA algorithm.

• MALSORI
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• no.50
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• pp.123-137
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• 2004

In this paper, we consider the implementation of connected digit recognition system using tree structured lexicon model. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with lexical tree search algorithm that is used for general speech recognition system for fast search and large vocabulary systems. To find the efficient modeling of digit recognition system, we investigate some performance changes when the lexical tree search is applied.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.269-272
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• 2001

Since Multi-way Search Tree reduces the number of the memory access by increasing the branch factor, it is considered a method to archive the high-speed IP address lookup. Using the combination of initial 16 bit may and Multi-way Search Tree, it also reduces the search time of If address lookup. Multi-way Search Tree consists of K keys and K＋1 key pointers. This paper shows how the E update of Multi-way Search Tree which consists of the one pointer within a node can be performed. Using the one pointer within a node, it increases the number of keys within a node and reduces the search time of IP lookup. We also describes IP updating methods such as modification, Insertion and Deletion of address entries. Our update scheme performs better than the method which rebuilds the entire IP routing table when IP update processes.

• Spatial Information Research
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• v.18 no.4
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• pp.109-120
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• 2010

Recently, due to rapid increasement of spatial data collected from various geosensors in u-GIS environments, the importance of spatial index for efficient search of large spatial data is rising gradually. Especially, researches based R-Tree to improve search performance of spatial data have been actively performed. These previous researches focus on reducing overlaps between nodes or the height of the R -Tree. However, these can not solve an unnecessary node access problem efficiently occurred in tree traversal. In this paper, we propose a MR-Tree(Mapping-based R-Tree) to solve this problem and to support efficient search of large spatial data. The MR-Tree can improve search performance by using a mapping tree for direct access to leaf nodes of the R-Tree without tree traversal. The mapping tree is composed with MBRs and pointers of R-Tree leaf nodes associating each partition which is made by splitting data area repeatedly along dimensions. Especially, the MR-Tree can be adopted in various variations of the R-Tree easily without a modification of the R-Tree structure. In addition, because the mapping tree is constructed in main memory, search time can be greatly reduced. Finally, we proved superiority of MR-Tree performance through experiments.

• The Journal of the Acoustical Society of Korea
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• v.14 no.2E
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• pp.43-49
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• 1995

In this paper a space search technique is used to detect and locate the faults of the circuit interconnections. The circuit interconnections are represented by the tree structure and the tree space is searched to detect and locate the open faults of the circuit interconnections. The breadth search is used to detect the open faults and reduce the space size. The depth search is used to locate the open faults.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.12
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• pp.756-763
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• 2014

In this paper, we introduce a new sparse signal recovery algorithm referred to as the matching pursuit with greedy tree search (GTMP). The tree search in our proposed method is implemented to minimize the cost function to improve the recovery performance of sparse signals. In addition, a pruning strategy is employed to each node of the tree for efficient implementation. In our performance guarantee analysis, we provide the condition that ensures the exact identification of the nonzero locations. Through empirical simulations, we show that GTMP is effective for sparse signal reconstruction and outperforms conventional sparse recovery algorithms.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.363-371
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• 1994

This thesis investigates an expert system(ES) to propose fault restoration plan by utilizing tree search strategies. In order to cope with an extensive amount of data and frequent breaker switching operations in distribution systems, the database of system configuration is constructed by using binary trees. This remarkably enhances the efficiency of search algorithm and makes the proposed ES easily adaptable to system changes due to switching operations. The rule-base is established to fully utilize the meris of tree-structured database. The inferring strategy is developed mainly based on the best-first search algorithm to increase computation efficiency. The proposed ES has been implemented to efficiently deal with large distribution systems by reducing computational burden remarkably compared with the conventional ES's.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.437-444
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• 2012

In this paper, we propose a method for predicting a user's location based on their past movement patterns. There is no restriction on the length of past movement patterns when using this method to predict the current location. For this purpose, a modified search tree has been devised. The search tree is constructed in an effective manner while it additionally learns the movement patterns of a user one by one. In fact, the time complexity of the learning process for a movement pattern is linear. In this process, the search tree expands to take into consideration more details about the movement patterns when a pattern that conflicts with an existing trained pattern is found. In this manner, the search tree is trained to make an exact matching, as needed, for location prediction. In the experiments, the results showed that this method is highly accurate in comparison with more complex and sophisticated methods. Also, the accuracy deviation of users of this method is significantly lower than for any other methods. This means that this method is highly stable for the variations of behavioral patterns as compared to any other method. Finally, 1.47 locations were considered on average for making a prediction with this method. This shows that the prediction process is very efficient.