• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.51 no.9
• /
• pp.460-466
• /
• 2002

A reliable fault phase selection algorithm plays a very important role in transmission line protection, Particularly in Extra High Voltage (EHV) networks. The conventional fault phase selection algorithm used the phase difference between positive and negative sequence current excluding load current. But, it is difficult to pick out only fault current since we can not know when a fault occurs and select the fault phase in weak-infeed conditions that dominate zero-sequence current in phase current. The proposed algorithm can select the accurately fault phase using the sum of unit vectors which are calculated by positive-sequence voltage and negative-sequence voltage.

• Journal of IKEEE
• /
• v.22 no.3
• /
• pp.570-577
• /
• 2018

With the increasing number of network nodes, traditional client/server node selection mechanisms are under tremendous pressure. In order to select efficient cooperative nodes in a highly dynamic P2P network topology, this article uses greedy algorithm to translate the overall optimization into multiple local optimal problems, and to quickly select service nodes. Therefore, the service node with the largest comprehensive capacity is selected to reduce the transmission delay and improve the throughput of the service node. The final simulation results show that the node selection strategy based on greedy algorithm can effectively improve the overall performance of P2P streaming media system.

• Journal of Distribution Science
• /
• v.12 no.3
• /
• pp.33-41
• /
• 2014

Purpose - The purpose of this study was to predict the selection of independent auditors in the companies listed on the Tehran Stock Exchange (TSE) using a combination of PSO algorithm and CART. This study involves applied research. Design, approach and methodology - The population consisted of all the companies listed on TSE during the period 2005-2010, and the sample included 576 data specimens from 95 companies during six consecutive years. The independent variables in the study were the financial ratios of the sample companies, which were analyzed using two data mining techniques, namely, PSO algorithm and CART. Results - The results of this study showed that among the analyzed variables, total assets, current assets, audit fee, working capital, current ratio, debt ratio, solvency ratio, turnover, and capital were predictors of independent auditor selection. Conclusion - The current study is practically the first to focus on this topic in the specific context of Iran. In this regard, the study may be valuable for application in developing countries.

• Proceedings of the KIEE Conference
• /
• 2001.07a
• /
• pp.22-24
• /
• 2001

This paper presents a fault phase selection algorithm for transmission line protection by means of the symmetrical components. Accurate fault phase selection is necessary for collect functioning of transmission line relaying, particularly in Extra High Voltage (EHV) networks. The conventional phase selection algorithm used the phase difference between positive and negative sequence current excluding load current. But, it is difficult to abstract only fault current since we can not know the time which a fault occurs. The proposed algorithm can select the accurately fault phase using fault current contained pre-fault current.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.6
• /
• pp.849-855
• /
• 2008

The Diagnostic Unit of CLINAID can infer working diagnoses for general diseases from the information provided by a user. This user-provided information in the form of signs and symptoms, however, is usually not sufficient to make a final decision on a working diagnosis. In order for the Diagnostic Unit to reach a diagnostic conclusion, it needs to select suitable clinical investigations for the patients. Because different investigations can be selected for the same patient, we need a process that can optimize the selection procedure employed by the Diagnostic Unit. This process, called a selection algorithm, must work with the fuzzy relational method because CLINAID uses fuzzy relational structures extensively for its knowledge bases and inference mechanism. In this paper we present steps of the selection algorithm along with simulation results on this algorithm using fuzzy relational products, both harsh product and mean product. The computation results of applying several different fuzzy implication operators are compared and analyzed.

• Journal of Korean Institute of Industrial Engineers
• /
• v.36 no.3
• /
• pp.164-175
• /
• 2010

In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2011.10a
• /
• pp.653-655
• /
• 2011

EPCglobal proposed a Q-algorithm, which is used for selecting a slot-count in the next query round. However, it is impossible to allocate an optimized slot-count because the original Q-algorithm did not define an optimized weight C value. In this paper, we propose an adaptive Q-algorithm, in which we differentiate the weight values with respect to collision and empty slots. The weight values are defined with the identification time as well as the collision probability.

• Communications for Statistical Applications and Methods
• /
• v.7 no.2
• /
• pp.617-631
• /
• 2000

This paper is concerned with suggesting a Bayesian method for variable selection in generalized logit model. It is based on Laplace-Metropolis algorithm intended to propose a simple method for estimating the marginal likelihood of the model. The algorithm then leads to a criterion for the selection of variables. The criterion is to find a subset of variables that maximizes the marginal likelihood of the model and it is seen to be a Bayes rule in a sense that it minimizes the risk of the variable selection under 0-1 loss function. Based upon two examples, the suggested method is illustrated and compared with existing frequentist methods.

• Journal of information and communication convergence engineering
• /
• v.12 no.1
• /
• pp.8-13
• /
• 2014

We consider the sensor selection problem in large sensor networks where the goal is to find the best set of sensors that maximizes application objectives. Since sensor selection typically involves a large number of sensors, a low complexity should be maintained for practical applications. We propose a geometry-based sensor selection algorithm that utilizes only the information of sensor locations. In particular, by observing that sensors clustered together tend to have redundant information, we theorize that the redundancy is inversely proportional to the distance between sensors and seek to minimize this redundancy by searching for a set of sensors with the maximum average distance. To further reduce the computational complexity, we perform an iterative sequential search without losing optimality. We apply the proposed algorithm to an acoustic sensor network for source localization, and demonstrate using simulations that the proposed algorithm yields significant improvements in the localization performance with respect to the randomly generated sets of sensors.

• Journal of the Earthquake Engineering Society of Korea
• /
• v.21 no.4
• /
• pp.171-179
• /
• 2017

For estimating the seismic demand of buildings, most seismic design provisions permit conducting linear and nonlinear response history analysis. In order to obtain reliable results from response history analyses, a proper selection of input ground motions is required. In this study, an accurate algorithm for selecting and scaling ground motions is proposed, which satisfies the ASCE 7-10 criteria. In the proposed algorithm, a desired number of ground motions are sequentially scaled and selected from a ground motion library without iterations.