• Smart Structures and Systems
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• 제24권2호
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• pp.193-207
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• 2019

This study concerns with morphing structures, e.g. as applied in the aerospace industry. A morphing aerofoil structure capable of variable geometry was developed, which was shown to be able to cater for the different aerodynamic requirements at different stages of flight. In this work, the useful and relatively simple method has been applied, which provides a direct method for calculating required morphing shape displacements via finding the most effective bar through calculating bar sensitivity to displacement and calculating set of length actuations for bar assembly to control/adjust shape imperfection of prestressable structural assemblies including complex elements ("macro-elements", e.g., the pantographic element), involving Matrix Condensation. The technique has been verified by experiments on the physical model of an aerofoil shaped morphing pantographic structure. Overall, experimental results agree well with theoretical prediction. Furthermore, the technique of multi-iteration adjustment was presented that effective in eliminating errors that occur in the practical adjustment process itself. It has been demonstrated by the experiments on the physical model of pantographic morphing structure. Finally, the study discusses identification of the most effective bars with the objective of minimal number of actuators or minimum actuation.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.243-246
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• 1994

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

• International Journal of Advanced Culture Technology
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• 제11권1호
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• pp.325-331
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• 2023

In this paper, we propose a mixed neural network structure of CNN and LSTM that can be used to detect or predict odor occurrence, which is most required in manufacturing industry or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data such as hydrogen sulfide, ammonia, benzene, and toluene in real time, and applies this data to an inference model to detect and predict odor conditions. The proposed model evaluated the prediction accuracy of the learning model through performance indicators according to accuracy, and the evaluation result showed an average performance of 94% or more.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.383-388
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• 2005

In the construction industry, complex works are carried out with significant resources under non-linear circumstances where clear concepts of project management could be of benefit to all parties and personnel involved. In this paper, we define the optimum project management configuration for construction management by using DSM (Design Structure Matrix). Furthermore DSM can be visualized as a network model, and then Graph Theory provides us the numerical results.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.32-41
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• 2017

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering demanding environment platforms locate and complex topsides structure platforms own. Evacuation planning on platforms is usually challenging. The computational tool is a good choice to plan evacuation by emergency simulation. However, the complex structure of platforms and varied evacuation behaviors usually weaken the advantages of computational simulation. Therefore, this study developed a simulation model for OOGPs to evaluate different evacuation plans to improve evacuation performance by integrating building information modeling (BIM) and agent-based model (ABM). The developed model consists of four parts: evacuation model input, simulation environment modeling, agent definition, and simulation and comparison. Necessary platform information is extracted from BIM and then used to model simulation environment by integrating matrix model and network model. During agent definition, in addition to basic characteristics, environment sensing and dynamic escape path planning functions are also developed to improve simulation performance. An example OOGP BIM topsides with different emergent scenarios is used to illustrate the developed model. The results showed that the developed model can well simulate evacuation on OOGPs and improve evacuation performance. The developed model was also suggested to be applied to other industries such as the architecture, engineering, and construction industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3284-3306
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• 2018

This study proposes a method to develop an authoring system(GeoMaTree) for diverse trees that constitute a virtual landscape. The GeoMaTree system enables the simple, intuitive production of an efficient structure, and supports real-time processing. The core of the proposed system is a procedural modeling based on a mathematical model and an application that supports digital content creation on diverse platforms. The procedural modeling allows users to control the complex pattern of branch propagation through an intuitive process. The application is a multi-resolution 3D model that supports appropriate optimization for a tree structure. The application and a compatible function, with commercial tools for supporting the creation of realistic synthetic images and virtual landscapes, are implemented, and the proposed system is applied to a variety of 3D image content.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2687-2689
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• 2000

In many cases the systems are so complex that it is not possible to obtain reasonable models using physical insight. Also a model based on physical insight contains a number of unknown parameters even if the structure is derived from physical laws. These problems can be solved by system identification. In this paper, Arago's disk system which has both stable and unstable regions is selected as an example for identification and a state-space model is identified using tailor-made model structure of this system. In stable region, a state-space model of Arago's disk system is identified through open loop experiment and a state-space model of unstable region is identified through closed loop experiment after using fuzzy controller to stabilize unstable system.

• Structural Engineering and Mechanics
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• 제22권1호
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• pp.85-105
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• 2006

Control of structural response due to seismic excitation in a manner of coupling adjacent buildings has been actively developed, and most attention focused on those buildings of similar height. However, with the rapid development of some modern cities, multi-story buildings constructed with an auxiliary low-rise podium structure to provide extra functions to the complex become a growing construction scheme. Being inspired by the positively examined coupling control approach for buildings with similar height, this paper aims to provide a comprehensive analytical study on control effectiveness of using friction dampers to link the two buildings with significant height difference to supplement the recent experimental investigation carried out by the writers. The analytical model of a coupled building system is first developed with passive friction dampers being modeled as Coulomb friction. To highlight potential advantage of coupling the main building and podium structure with control devices that provide a lower degree of coupling, the inherent demerit of rigid-coupled configuration is then evaluated. Extensive parametric studies are finally performed. The concerned parameters influencing the design of optimal friction force and control efficiency include variety of earthquake excitation and differences in floor mass, story number as well as number of dampers installed between the two buildings. In general, the feasibility of interaction control approach applied to the complex structure for vibration reduction due to seismic excitation is supported by positive results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.1030-1050
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• 2021

The edges with "bridge characteristic" play the role of connecting the communication between regions in power optical cable network. To solve the problem of mining edges with "bridge characteristic" in provincial power optical cable network, the complex power optical cable network model is constructed. Firstly, to measure the generated potential energy of all nodes in n-level neighborhood local structure for one edge, the n-level neighborhood local structure topological potential is designed. And the minimum connected chain attenuation is designed to measure the attenuation degree caused by substituted edges. On the basis of that, the minimum connected chain attenuation topological potential based measurement is designed. By using the designed measurement, a bridge-edges mining algorithm is proposed to mine edges with "bridge characteristic". The experiments are conducted on the physical topology of the power optical cable network in Jilin Province. Compared with that of other three typical methods, the network efficiency and connectivity of the proposed method are decreased by 3.58% and 28.79% on average respectively. And the proposed method can not only mine optical cable connection with typical "bridge characteristic" but also can mine optical cables without obvious characteristics of city or voltage, but it have "bridge characteristic" in the topology structure.