• Structural Engineering and Mechanics
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• 제29권2호
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• pp.117-134
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• 2008

A new adaptive dual reciprocity boundary element method for dynamic analysis of 3-D structures is presented in this paper. It is based on finding the best approximation function of a radial basis function (RBF) group $f=r^n+c$ which minimize the error of displacement field expansion. Also, the effects of some parameters such as the existence of internal points, number of RBF functions and position of collocation nodes in discontinuous elements are investigated in this adaptive procedure. Three numerical examples show improvement in dynamic response of structures with adaptive RBF in dual reciprocity with respect to ordinary BEM.

• 대한전기학회논문지
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• 제45권2호
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• pp.175-184
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• 1996

In this paper the newly developed discrete-time adaptive sliding mode control method is proposed and applied to the power system stabilization problem. In contrast to the conventional continuous-time sliding mode controller, the proposed method is developed in the discrete-time domain and based on the input/output measurements instead of the continuous-time and the full-states feedback, respectively. Because the proposed control method has the adaptivity property in addition to the natural robustness property of the sliding mode control, it is possible to design the power system stabilizer which can overcome both the minor variations of the parameters of the power system and the diverse operating conditions and faults of the power system. Mathematical proof and the various computer simulations are done to verify the performance and stability of the proposed method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.244-247
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• 1993

In this paper, Fuzzy-Neural Network Control system that has the characteristic of fuzzy control to be controlled easily end the good characteristic of a artificial neural network to control the plant due to its learning is presented. A fuzzy rule to be applied is selected automatically by the allocated neurons. The neurons correspond to Fuzzy rules which ere created by a expert. To adaptivity, the more precise modeling is implemented by error beck-propagation learning of adjusting the link-weight of fuzzy membership function in Fuzzy-Neural Network. The more classified fuzzy rule is used to include the property of Dual Mode Method. To test the effectiveness of the algorithm presented above, the simulation for position end velocity of DC servo motor is implemented.

• Journal of Welding and Joining
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• 제16권1호
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• pp.98-105
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• 1998

The accuracy of the finite element method depends upon the mesh that is used in the analysis. The temperature around the arc is higher than the melting point of the materials, and it drops sharply in the regions just away from the arc. This requires an extremely fine mesh in the confined high temperature region to predict the temperature accurately in that region. But the computational time increases with the fineness of mesh. Since fine mesh is required only around the arc source, adaptivity of the input mesh according to the position of the arc source is efficient. The remeshing technique gives a fine mesh in the high temperature region around the arc and a coarse mesh in other region at any time step. With this it is possible to achieve desired accuracy with less computation time. In this study a transient adaptive mesh, remeshing technique, is developed and calculated temperature for a sample problem.

• Structural Engineering and Mechanics
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• 제73권1호
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• pp.1-16
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• 2020

Finite elements based on the partition of unity (PU) approximation have powerful capabilities for p-adaptivity and solutions with high smoothness without remeshing of the domain. Recently, the PU approximation was successfully applied to the three-node shell finite element, properly eliminating transverse shear locking and showing excellent convergence properties and solution accuracy. However, the enrichment with the PU approximation results in a significant increase in the number of degrees of freedom; therefore, it requires greater computational cost, thus making it less suitable for practical engineering. To circumvent this disadvantage, we propose a new strategy to decrease the total number of degrees of freedom in the existing PU-based shell element, without loss of optimal convergence and accuracy. To alleviate the locking phenomenon, we use the method of mixed interpolation of tensorial components and perform convergence studies to show the accuracy and capability of the proposed shell element. The excellent performances of the new shell elements are illustrated in three benchmark problems.

• Structural Engineering and Mechanics
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• 제10권6호
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• pp.635-650
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• 2000

In this paper, the adaptive nodal generation procedure based on the estimated local and global error in the element-free Galerkin (EFG) method is proposed. To investigate the possibility of h-type adaptivity of EFG method, a simple nodal refinement scheme is used. By adding new node along the background cell that is used in numerical integration, both of the local and global errors can be controlled adaptively. These errors are estimated by calculating the difference between the values of the projected stresses and original EFG stresses. The ultimate goal of this study is to develop the reliable nodal generator based on the local and global errors that is estimated posteriori. To evaluate the performance of proposed adaptive procedure, the convergence behavior is investigated for several examples.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• Structural Engineering and Mechanics
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• 제88권6호
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• pp.535-549
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• 2023

Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2861-2880
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• 2018

Mobile Ad hoc Networks (MANETs) have become a viable platform owing to their potential of providing communication without any pre-existing infrastructure and central administrating authority. Mutual support and co-operation among nodes are prerequisites for performing functions in such networks. The scarcity of resources makes it economical for nodes to conserve their resources and misbehave by avoiding participation in the network. Therefore, a mechanism is required to detect and handle such misbehaving nodes and promote co-operation in the network. Existing techniques for handling misbehaving nodes focus only on their current behaviour without considering the antecedent behaviour of nodes. In real world, a node may dynamically change its behaviour in accordance to its requirements. Hence, an efficient mechanism is required for providing security against such misbehaviour. This paper proposes an Adaptive Security Model which contemplates the present as well as anterior behaviour of nodes for providing security against dynamic node behaviour. The adaptivity of the model is nested in its ability to requite well-behaving nodes and penalize misbehaving ones in conformity with their overall behaviour. Simulation results indicate the efficiency of proposed scheme in securing the network from the menace of dynamic behaviour of nodes.

• 대한기계학회논문집A
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• 제20권7호
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• pp.2067-2077
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• 1996

In adaptive finite element analysis, r- and h-methods are generally used on the basis of a discretization error estimator. In this paper, an rh-method is proposed as a new adaptive method which can improve the adaptivity performance by using both of them. This suggested rh-method moves nodal coordinates of initially given model to adjust element discretization errors and thereafter performes the h-method tdo obtain the specified accuracy of finite element solutions. Numerical experiments for various plane problems were performed using 4-noded isoparametric quadrilateral elements. As a result, the rh-method has been shown to be an accurate and efficient adaptive analysis method to obtain as improved solution.