• Journal of Information Processing Systems
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• v.12 no.3
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• pp.358-380
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• 2016

In order to considerably reduce the ambiguity rate, we propose in this article a disambiguation approach that is based on the selection of the right diacritics at different analysis levels. This hybrid approach combines a linguistic approach with a multi-criteria decision one and could be considered as an alternative choice to solve the morpho-lexical ambiguity problem regardless of the diacritics rate of the processed text. As to its evaluation, we tried the disambiguation on the online Alkhalil morphological analyzer (the proposed approach can be used on any morphological analyzer of the Arabic language) and obtained encouraging results with an F-measure of more than 80%.

• 한국전산유체공학회:학술대회논문집
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• 2009.04a
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• pp.112-115
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• 2009

In this paper, flow simulation algorithms for utilizing unstructured hybrid meshes are introduced. First, various types of meshes are introduced. Advantages and disadvantages of each type of meshes are discussed. Unstructured hybrid mesh approach, that is best suited for high speed viscous flow simulation, is presented. Lastly, various types of flow simulations using unstructured hybrid meshes are introduced.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2008.10b
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• pp.463-467
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• 2008

Heuristic optimization using hybrid algorithms have provided a robust and efficient approach for solving many optimization problems. In this paper, a new hybrid algorithm using adaptive genetic algorithm (aGA) and particle swarm optimization (PSO) is proposed. The proposed hybrid algorithm is applied to solve numerical optimization functions. The results are compared with those of GA and other conventional PSOs. Finally, the proposed hybrid algorithm outperforms others.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.201-208
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• 2005

Neuro-Fuzzy modeling approach is proposed to predict the dynamic behavior of a single-degree-of-freedom structure that is equipped with hybrid base isolation system. Hybrid base isolation system consists of friction pendulum systems (FPS) and a magnetorheological (MR) damper. Fuzzy model of the M damper is trained by ANFIS using various displacement, velocity, and voltage combinations that are obtained from a series of performance tests. Modelling of the FPS is carried out with a nonlinear analytical equation that is derived in this study and neuro-fuzzy training. Fuzzy logic controller is employed to control the command voltage that is sent to MR damper. The dynamic responses or experimental structure subjected to various earthquake excitations are compared with numerically simulated results using neuro-fuzzy modeling method. Numerical simulation using neuro-fuzzy models of the MR damper and FPS predict response of the hybrid base isolation system very well.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.8
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• pp.1088-1094
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• 2002

A channel flow with a high Reynolds number but coarse grids is numerically studied to investigate the prediction possibility of its turbulence which is three-dimensional and time-dependent. In the present paper, a Reynolds-Averaged Navier-Stokes (RANS) model, a Large Eddy Simulation (LES) and a Navier-Stokes equation with no model are tested with a new approach of hybrid RANS/LES, which reduces to RANS model in the boundary layers and at separation, and to Smagorinsky-like LES downstream of separation, and then compared with each other. It is found that the simulations of hybrid RANS/LES method sustain turbulence like those of LES and with no model, and the results are stable and fairly accurate. This indicates strongly that gradual improvements could lead to a simple, stable, and accurate approach to predict turbulence phenomena of wall-bounded flow.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.54-60
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• 2001

In this paper, a shape-based block layout (SBL) approach is presented to solve the facility layout problem with unequal-area and fixed shapes. The SBL approach employs hybrid genetic algorithm (Hybrid-GA) to find a good solution and the concept of bay structure is used. In the typical facility layout problem with unequal area and fixed shapes, the given geometric constraints of unequal-area and fixed shapes are mostly approximated to original shape by aspect ratio. Thus, the layout results require extensive manual revision to create practical layouts and it produces irregular building shapes and too much unusable spaces. Experimental results show that a SBL model is able to produce better solution and to create more practical layouts than those of existing approaches.

• Steel and Composite Structures
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• v.7 no.3
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• pp.241-251
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• 2007

The purpose of this study is to calculate the torsional rigidity of arbitrarily shaped composite sections on the basis of hybrid finite element approach. An analogy is used between the torsion problem and deformation of a plate which exhibits only shear behavior. In the analysis a simple hybrid finite element based on Hellinger-Reissner functional is presented and a set of numerical examples are performed to demonstrate and asses the performance of the developed element in practical applications.

• Journal of the Semiconductor & Display Technology
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• v.10 no.3
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• pp.75-81
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• 2011

This paper presents a novel method for image classification based on a hybrid genetic algorithm (GA) and support vector machine (SVM) approach which can significantly improve the classification performance for content-based image retrieval (CBIR). Though SVM has been widely applied to CBIR, it has some problems such as the kernel parameters setting and feature subset selection of SVM which impact the classification accuracy in the learning process. This study aims at simultaneously optimizing the parameters of SVM and feature subset without degrading the classification accuracy of SVM using GA for CBIR. Using the hybrid GA and SVM model, we can classify more images in the database effectively. Experiments were carried out on a large-size database of images and experiment results show that the classification accuracy of conventional SVM may be improved significantly by using the proposed model. We also found that the proposed model outperformed all the other models such as neural network and typical SVM models.

• Ocean Systems Engineering
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• v.8 no.4
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• pp.381-407
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• 2018

This paper presents a hybrid numerical approach, which combines a two-phase Navier-Stokes model (NS) and the fully nonlinear potential theory (FNPT), for modelling wave-structure interaction. The former governs the computational domain near the structure, where the viscous and turbulent effects are significant, and is solved by OpenFOAM/InterDyMFoam which utilising the finite volume method (FVM) with a Volume of Fluid (VOF) for the phase identification. The latter covers the rest of the domain, where the fluid may be considered as incompressible, inviscid and irrotational, and solved by using the Quasi Arbitrary Lagrangian-Eulerian finite element method (QALE-FEM). These two models are weakly coupled using a zonal (spatially hierarchical) approach. Considering the inconsistence of the solutions at the boundaries between two different sub-domains governed by two fundamentally different models, a relaxation (transitional) zone is introduced, where the velocity, pressure and surface elevations are taken as the weighted summation of the solutions by two models. In order to tackle the challenges associated and maximise the computational efficiency, further developments of the QALE-FEM have been made. These include the derivation of an arbitrary Lagrangian-Eulerian FNPT and application of a robust gradient calculation scheme for estimating the velocity. The present hybrid model is applied to the numerical simulation of a fixed horizontal cylinder subjected to a unidirectional wave with or without following current. The convergence property, the optimisation of the relaxation zone, the accuracy and the computational efficiency are discussed. Although the idea of the weakly coupling using the zonal approach is not new, the present hybrid model is the first one to couple the QALE-FEM with OpenFOAM solver and/or to be applied to numerical simulate the wave-structure interaction with presence of current.

• Journal of the Korean Geosynthetics Society
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• v.22 no.1
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• pp.67-74
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• 2023

In order to monitor the stability of slopes, research on data-based slope failure prediction and early warning is increasing. However, most papers overlook the quality of data. Poor data quality can cause problems such as false alarms. Therefore, this paper proposes a two-step hybrid approach consisting of rules and machine learning models for quality control of data collected from slopes. The rule-based has the advantage of high accuracy and intuitive interpretation, and the machine learning model has the advantage of being able to derive patterns that cannot be explicitly expressed. The hybrid approach was able to take both of these advantages. Through a case study, the performance of using the two methods alone and the case of using the hybrid approach was compared, and the hybrid method was judged to have high performance. Therefore, it is judged that using a hybrid method is more appropriate than using the two methods alone for data quality control.