• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.4
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• pp.348-359
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• 1989

The multitree pattern recognition algorithm proposed by [1] and [2] is modified in order to improve its performance. The basic idea of the multitree pattern classification algorithm is that the binary dceision tree used to classify an unknow pattern is constructed for each feature and that at each stage, classification rule decides whether to classify the unknown pattern or to extract the feature value according to the feature ordet. So the feature ordering needed in the calssification procedure is simple and the number of features used in the classification procedure is small compared with other classification algorithms. Thus the algorithm can be easily applied to real pattern recognition problems even when the number of features and that of the classes are very large. In this paper, the wighting factor assignment scheme in the decision procedure is modified and various classification rules are proposed by means of the weighting factor. And the branch and bound method is applied to feature subset selection and feature ordering. Several experimental results show that the performance of the multitree pattern classification algorithm is improved by the proposed scheme.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.12
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• pp.409-414
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• 2015

The energy conservation is the most important subject for long run operation of the sensor nodes with limited power resources. Clustering is one of most energy efficient technique to grouped the sensor nodes into distinct cluster. But, in a cluster based WSN, CHs and gateways bear an extra work load to send the processed data to the sink. The inappropriate cluster formation may cause gateways overloaded and may increase latency in communication. In this paper, we propose a novel load balanced clustering model for improving energy efficiency and giving a guarantee of long network lifetime. We show the result of performance measurement experiments that designs using a branch and bound algorithm and a multi-start local search algorithm to compare with the existing load balanced clustering model.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.71-89
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• 2003

Although many studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective in the classification problems. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques. This study proposes the linearly combining methodology of different classification techniques. The methodology is developed to find the optimal combining weight and compute the weighted-average of different techniques' outputs. The proposed methodology is represented as the form of mixed integer programming. The objective function of proposed combining methodology is to minimize total misclassification cost which is the weighted-sum of two types of misclassification. To simplify the problem solving process, cutoff value is fixed and threshold function is removed. The form of mixed integer programming is solved with the branch and bound methods. The result showed that proposed methodology classified more accurately than any of techniques individually did. It is confirmed that Proposed methodology Predicts significantly better than individual techniques and the other combining methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5A
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• pp.466-473
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• 2010

Several protocols which are based on tree topology to guarantee the important metrics such as energy efficiency in sensor networks have been proposed. However, studies on the effect of topologies in sensor networks, where base node has a high mobility, are very few. In this paper, we propose a minimum Wiener index tree as a suitable topology to the wireless sensor networks with high mobile base node. The minimum Wiener index spanning tree problem which aims to find a tree with minimum Wiener index from a given weighted graph was proved to be NP-hard. We designed a branch and bound algorithm for this problem. To evaluate the performance of proposed tree, the comparisons with minimum spanning tree in terms of transmission distance, energy consumption during one round, and network lifetime was performed by simulations. Our proposed tree outperformed in transmission distance and energy efficiency but underperformed in lifetime.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9A
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• pp.1091-1100
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• 2004

In this paper, we present a reducing power conswnption of a scheduling for module selection under the time constraint. The proposed low power scheduling executes FDS_LP considering low power to exist the FDS scheduling by inputted the behavioral language. The proposed FDS_LP perfonns lower power consumption with dynamic power which is minimized the switching activity, based on force conception In the time step of module selection, an optimal RT(Register Transfer) library is composed by exploration of the parameters such as power, area, and delay. To find optimal parameters of RT library, an optimal module selection algorithm using Branch and Bound algorithm is also proposed. In the comparison and experimental results, The proposed FDS_LP algorithm reduce maximum power saving up to 23.9% comparing to previous FDS algorithm.

• Journal of the Korea Society of Computer and Information
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• v.15 no.7
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• pp.19-26
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• 2010

In this paper, we suggest a efficient handwritten character verification method in on-line environments which automatically analyses two input character string and computes their similarity degrees. The proposed algorithm first applies the circular projection method to input handwritten strings and extracts their representative features including shape, directions, etc. It then calculates the similarity between two character strings by using an improved dynamic time warping (DTW) algorithm. We improved the conventional DTW algorithm efficiently through adopting the branch-and-bound policy to the existing DTW algorithm which is well-known to produce good results in the various optimization problems. The experimental results to verify the performance of the proposed system show that the suggested handwritten character verification method operates more efficiently than the existing DTW and DDTW algorithms in terms of the speed.

• Computational Structural Engineering
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• v.10 no.2
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• pp.255-263
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• 1997

The optimum design of most structural systems used in practice requires considering design variables as discrete quantities. The present paper shows that the linear approximation method is very effective as a tool for the discrete optimum designs of unsymmetric composite laminates. The formulated design problem is subjected to a multiple in-plane loading condition due to shear and axial forces, bending and twisting moments, which is controlled by maximum strain criterion for each of the plys of a composite laminate. As an initial approach, the process of continuous variable optimization by FDM is required only once in operating discrete optimization. The nonlinear discrete optimization problem that has the discrete and continuous variables is transformed into the mixed integer programming problem by SLDP. In numerical examples, the discrete optimum solutions for the unsymmetric composite laminates consisted of six plys according to rotated stacking sequence were found, and then compared the results with the nonlinear branch and bound method to verify the efficiency of present method.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.45-57
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• 2009

BTL (Build-Transfer-Lease) Project for Education Facilities are contracted as a package which consists of several education facilities. The general maintenance period of BTL project for education facilities is 20 years. Thus, total cost variation largely depends on the accuracy of the maintenance cost forecasting in the early stage in the life cycle of the BTL Project. This research develops a cost forecasting system using complete linkage algorithm and branch & bound algorithm to help in finding optimal bundling combination. This system helps owner's decision-making to estimate the total project cost with various constraints changing. The result of this research suggests more reasonable and effective forecasting model for the maintenance facilities package in the BTL project.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.195-207
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• 2007

The urban railways connecting between the inner city and suburb of Seoul metropolitan area, has lost the competitiveness against cars because too many stops deteriorated operating speed and passenger's level of service. This paper suggests that an express train should be introduced into the urban railway system in order to sort out such a complication. There are two considerations in the present study. Firstly, train schedule problem should be taken into account. In this regard, a new model for urban railway system was developed by revising the existing models dealing with single line freight railway. Approximate branch and bound algorithm based on conflict group rather than a single conflict was adopted. Consequently, it was found that the time saving in calculating the optimal schedule is the most meaningful contribution of the algorithm. The second consideration is associated with the application of the model. A case study was carried out using the actual operation data from Ansan line. In conclusion, the operation speed of the line can increase considerably with minimal number of new sidings.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.71-77
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• 2019

This paper defines a multi-selection knapsack problem and presents an algorithm for seeking its optimal solution. Multi-selection means that all members of the particular group be selected or excluded. Our branch-and-bound algorithm introduces a simplex containing the feasible region of the original problem to exploit the fact that the most tightly underestimating function on the simplex is linear. In bounding operation, the subproblem defined over the candidate simplex is minimized. During the branching process the candidate simplex is splitted into two one-less dimensional subsimplices by being projected onto two hyperplanes. The approach of this paper can be applied to solving the global minimization problems under various types of the knapsack constraints.