• MALSORI
• /
• no.45
• /
• pp.117-126
• /
• 2003

Decision tree-based state tying has been proposed in recent years as the most popular approach for clustering the states of context-dependent hidden Markov model-based speech recognition. The aims of state tying is to reduce the number of free parameters and predict state probability distributions of unseen models. But, when doing state tying, the size of a decision tree is very important for word independent recognition. In this paper, we try to construct optimized decision tree based on the average of feature vectors in state pool and the number of seen modes. We observed that the proposed optimal decision tree is effective in predicting the state probability distribution of unseen models.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.10A
• /
• pp.1004-1014
• /
• 2007

In sensor networks, it is crucial to reliably and energy-efficiently deliver sensed information from each source to a sink node. Specifically, in mobile sink (user) applications, due to the sink mobility, a stationary dissemination path may no longer be effective. The path will have to be continuously reconfigured according to the current location of the sink. Moreover, the dynamic optimal path from each source to the sink is required in order to reduce end-to-end delay and additional energy wastage. In this paper, an Adaptive Reversal Optimal path Tree (AROT) protocol is proposed. Information delivery from each source to a mobile sink can be easily achieved along the AROT without additional control overhead, because the AROT proactively performs adaptive sink mobility management. In addition, the dynamic path is optimal in terms of hop counts and the AROT can maintain a robust tree structure by quickly recovering the partitioned tree with minimum packet transmission. Finally, the simulation results demonstrate that the AROT is a considerably energy-efficient and robust protocol.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.8 no.5
• /
• pp.1089-1095
• /
• 2004

The genetic algorithms have been used to take a near optimal solution because The generation of the optimal Steiner tree from a given network is NP-hard problem,. The chromosomes in genetic algorithm are represented with the floating point representation instead of the existing binary string for solving this problem. A spanning tree was obtained from a given network using Prim's algorithm. Then, the new Steiner point was computed using genetic algorithm with the chromosomes in the floating point representation, and it was added to the tree for approaching the result. After repeating these evolving steps, the near optimal Steiner tree was obtained. Using this method, the tree is quickly and exactly approached to the near optimal Steiner tree compared with the existing genetic algorithms using binary string.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.40 no.2
• /
• pp.19-29
• /
• 2015

The purpose of this study is to suggest the grid search method for selecting an optimal decision tree model. It chooses optimal values for the maximum depth of tree and the minimum number of observations that must exist in a node in order for a split to be attempted. Therefore, the grid search method guarantees building a decision tree model that shows more precise and stable classifying performance. Through empirical analysis using data of job satisfaction of workplace reserve force commanders, we show that the grid search method helps us generate an optimal decision tree model that gives us hints for the improvement direction of labor conditions of Korean workplace reserve force commanders.

• East Asian mathematical journal
• /
• v.38 no.3
• /
• pp.277-292
• /
• 2022

This study investigates the convergence of the optimal consumption and investment policies in a binomial-tree model to those in the continuous-time model of Merton (1969). We provide the convergence in explicit form and show that the convergence rate is of order ∆t, which is the length of time between consecutive time points. We also show by numerical solutions with realistic parameter values that the optimal policies in the binomial-tree model do not differ significantly from those in the continuous-time model for long-term portfolio management with a horizon over 30 years if rebalancing is done every 6 months.

• Proceedings of the Korea Association of Information Systems Conference
• /
• 2002.11a
• /
• pp.289-312
• /
• 2002

This study suggests the Link weight analysis approach to choose input variables and an integrated model to make more accurate bankruptcy prediction model. the Link weight analysis approach is a method to choose input variables to analyze each input node's link weight which is the absolute value of link weight between an input nodes and a hidden layer. There are the weak-linked neurons elimination method, the strong-linked neurons selection method in the link weight analysis approach. The Integrated Model is a combined type adapting Bagging method that uses the average value of the four models, the optimal weak-linked-neurons elimination method, optimal strong-linked neurons selection method, decision-making tree model, and MDA. As a result, the methods suggested in this study - the optimal strong-linked neurons selection method, the optimal weak-linked neurons elimination method, and the integrated model - show much higher accuracy than MDA and decision making tree model. Especially the integrated model shows much higher accuracy than MDA and decision making tree model and shows slightly higher accuracy than the optimal weak-linked neurons elimination method and the optimal strong-linked neurons selection method.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.04a
• /
• pp.677-679
• /
• 2017

Data convergecast is an indispensable task for any WSN applications. Typically, scheduling in the WSN consists of two phases: tree construction and scheduling. The optimal tree structure and scheduling for the network is proven NP-hard. This paper focuses on the delay optimality while constructing the data convergecast tree. The algorithm can take any tree as the input, and by performing the switches (i.e. a node changes its parent), the expected aggregation delay is potentially reduced. Note that while constructing the tree, only the in-tree collisions between the child nodes sending data to their common parent is considered.

• Journal of applied mathematics & informatics
• /
• v.5 no.2
• /
• pp.427-432
• /
• 1998

When an undirected tree T and a vertex ${\gamma}$ in the tree are given the problem to transform T into a rooted tree with ${\gamma}$ as its root is considered. Using Euler tour and prefix sum an optimal algorithm has been developed [2,3]. We will present another parallel algorithm which is optimal also on EREW PRAM. Our approach resuces the given tree step by step by pruning and pointer jumping. That is the tree structure is retained during algorithm processing such that than other tree computations can be carried out in parallel.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.22 no.2
• /
• pp.1-12
• /
• 2019

Open space planners and designers should consider scientific and quantified functions of trees when they have to locate where to plant the tree. However, until now, most planners and designers could not consider them because of lack of tool for considering scientific and quantitative tree functions. This study introduces a tree location supporting tool which focuses on the multi-objective including scientific function using ACO (Ant colony optimization). We choose shading effect (scientific function), shielding, and openness as objectives for test application. The results show that when the user give a high weight to a particular objective, they can obtain the optimal results with high value of that objective. When we allocate higher weight for the shading effect, the tree plans provide larger shadow value. Even when compared with current tree plan, the study result has a larger shading effect plan. This result will reduce incident radiation to the ground and make thermal friendly open space in the summer. If planners and designers utilize this tool and control the objectives, they would get diverse optimal tree plans and it will allow them to make use of the many environmental benefits from trees.

• Journal of information and communication convergence engineering
• /
• v.22 no.3
• /
• pp.215-220
• /
• 2024

This paper presents an efficient method for expanding interconnections in scenarios involving the reconstruction of interconnections across arbitrarily divided planes. Conventionally, such situations necessitate rebuilding interconnections based on all targets, ensuring minimal cost but incurring substantial time expenditure. In this paper, we present a tinkered tree algorithm designed to efficiently expand interconnections within a Euclidean plane divided into m randomly generated regions. The primary objective of this algorithm is to construct an optimal tree by utilizing the minimum spanning tree (MST) of each region, resulting in swift interconnection expansion. Interconnection construction is applied in various design fields. Notably, in the context of ad hoc networks, which lack a fixed-wired infrastructure and communicate solely with mobile hosts, the heuristic proposed in this paper is anticipated to significantly reduce costs while establishing rapid interconnections in scenarios involving expanded connection targets.