• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2228-2239
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• 2015

A novel integrated optimization method based on the Generalized Bender’s Decomposition (GBD) is proposed to combine both generation and transmission expansion problems. Most of existing researches on the integrated expansion planning based on the GBD theory incorporate DC power flow model to guarantee the convergence and improve the computation time. Inherently the GBD algorithm based on DC power flow model cannot consider variables and constraints related bus voltages and reactive power. In this paper, an integrated optimization method using the GBD algorithm based on a linearized AC power flow model is proposed to resolve aforementioned drawback. The proposed method has been successfully applied to Garver’s six-bus system and the IEEE 30-bus system which are frequently used power systems for transmission expansion planning studies.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1202-1209
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• 2014

A novel integrated optimization method is proposed to combine both generation and transmission line expansion problem considering bus voltage limit. Most of the existing researches on the combined generation and transmission expansion planning cannot consider bus voltages and reactive power flow limits because they are mostly based on the DC power flow model. In this paper the AC power flow model and nonlinear constraints related to reactive power are simplified and modified to improve the computation time and convergence. The proposed method has been successfully applied to Garver's six-bus system which is one of the most frequently used small scale sample systems to verify the transmission expansion method.

• KIISE Transactions on Computing Practices
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• v.22 no.9
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• pp.461-466
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• 2016

Topic expansion is an expansion method that reflects external data for improving quality of learned topic. The online learning topic model is not appropriate for topic expansion using external data, because it does not reflect unseen words to learned topic model. In this study, we proposed topic expansion method using infinite vocabulary online LDA. When unseen words appear in learning process, the proposed method allocates unseen word to topic after calculating semantic correlation between unseen word and each topic. To evaluate the proposed method, we compared with existing topic expansion method. The results indicated that the proposed method includes additional information that is not contained in broadcasting script by reflecting external documents. Also, the proposed method outperformed on coherence evaluation.

• Transactions of Materials Processing
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• v.23 no.3
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• pp.164-170
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• 2014

To predict the deformation and fracture during tube expansion using the finite element (FE) method, a material model is considered that incorporates the damage evolution due to the deformation. In the current study, a Rice-Tracey model was used as the damage model with inclusion of the hydrostatic stress term. Since OFHC Cu is not significantly affected by strain rate, a Hollomon flow stress model was used. The material parameters in each model were obtained by using an optimization method. The objective function was defined as the difference between the experimental measurements and FE simulation results. The parameters were determined by minimizing the objective function. To verify the validity of the FE modeling, cross-verification was conducted through a tube expansion test. The simulation results show reasonable agreement with the experiments. The design for a minimum diameter of expansion tube using the FE modeling was verified by a simplified tube expansion test and simulation results.

• ETRI Journal
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• v.39 no.4
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• pp.455-466
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• 2017

This study focuses on a method for sequential data augmentation in order to alleviate data sparseness problems. Specifically, we present corpus expansion techniques for enhancing the coverage of a language model. Recent recurrent neural network studies show that a seq2seq model can be applied for addressing language generation issues; it has the ability to generate new sentences from given input sentences. We present a method of corpus expansion using a sentence-chain based seq2seq model. For training the seq2seq model, sentence chains are used as triples. The first two sentences in a triple are used for the encoder of the seq2seq model, while the last sentence becomes a target sequence for the decoder. Using only internal resources, evaluation results show an improvement of approximately 7.6% relative perplexity over a baseline language model of Korean text. Additionally, from a comparison with a previous study, the sentence chain approach reduces the size of the training data by 38.4% while generating 1.4-times the number of n-grams with superior performance for English text.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.115-124
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• 2024

To detect and prevent structural damage caused by various loads on marine structures and ships, structural health monitoring procedure is essential. Estimating loads acting on the structures which are measured by sensors that are mounted properly are crucial for structural health monitoring. However, attaching an excessive number of sensors to the structure without consideration can be inefficient due to the high costs involved and the potential for inducing structural instability. In this study, we introduce a method to determine the optimal number of sensors and their optimized locations for strain measurement sensors, allowing for accurate load estimation throughout the structure using model expansion method. To estimate the loads exerted on the entire structure with minimal sensors, we construct a strain-load interpolation matrix using the strain mode shapes of the finite element (FE) model and select the optimal sensor locations by applying D-Optimal Design and the row exchange algorithm. Finally, we estimate the loads exerted on the entire structure using the model expansion method. To validate the proposed method, we compare the results obtained by applying the optimal sensor placement and model expansion method to an FE model subjected to arbitrary loads with the loads exerted on the entire FE model, demonstrating efficiency and accuracy.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.540-549
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• 2018

This paper proposes the method of active distribution network expansion planning considering distributed generation integration and distribution network reconfiguration. The distribution network reconfiguration is taken as the expansion planning alternative with zero investment cost of the branches. During the process of the reconfiguration in expansion planning, all the branches are taken as the alternative branches. The objective is to minimize the total costs of the distribution network in the planning period. The expansion alternatives such as active management, new lines, new substations, substation expansion and Distributed Generation (DG) installation are considered. Distribution network reconfiguration is a complex mixed-integer nonlinear programming problem, with integration of DGs and active managements, the active distribution network expansion planning considering distribution network reconfiguration becomes much more complex. This paper converts the dual-level expansion model to Second-Order Cone Programming (SOCP) model, which can be solved with commercial solver GUROBI. The proposed model and method are tested on the modified IEEE 33-bus system and Portugal 54-bus system.

• Communications of the Korean Mathematical Society
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• v.28 no.3
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• pp.615-633
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• 2013

We use a power series expansion method to get an analytic approximation value for the quanto option price under the Hull and White stochastic volatility model, which turns out to be accurate enough by comparing with the simulation prices using Monte Carlo method.

• Journal of Korean Society of Rural Planning
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• v.10 no.4 s.25
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• pp.9-18
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• 2004

The purpose or this study is to simulate spatially the urban expansion phenomena with a cellular automata (CA) technique using GIS. A study area, Suwon city, was selected for test of model verification and application with the classified land-use maps of three data years: 1986, 1996, and 2000. The urbanized potential maps were generated with seven criteria of one geographic factor (slope of land), and six accessibility factors (time distances from city, national road, Seoul, station, and built-up boundary), considering their weighting values, which were optimized by WSM (weighted scenario method for intensity order) combined a ranking method and a AHP technique. The optimized weighting values at the urban expansion between 1986 and 1996 were applied to verify the CA model for the other expansion between 1996 and 2000. The results of model application showed that urban sprawl phenomena of the urban expansion toward rural area can be simulated spatially and temporally with several boundary conditions considering various scenarios for the criteria and parameters of the model. Ultimately, this study can contribute to reference data for land-use planning of urban fringe areas.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.26-43
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• 2008

We propose a new query expansion method in the extended Boolean model that improves precision without degrading recall. For improving precision, our method promotes the ranks of documents having more query terms since users typically prefer such documents. The proposed method consists of the following three steps: (1) expanding the query by adding new terms related to each term of the query, (2) further expanding the query by adding augmented terms, which are conjunctions of the terms, (3) assigning a weight on each term so that augmented terms have higher weights than the other terms. We conduct extensive experiments to show the effectiveness of the proposed method. The experimental results show that the proposed method improves precision by up to 102% for the TREC-6 data compared with the existing query expansion method using a thesaurus proposed by Kwon et al.