• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.404-410
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• 1999

We will prove the existence of initial fuzzy closure structures. From this fact we can define subspaces and products of fuzzy closure spaces. Furthermore the family $\Delta$(X) of all fuzzy closure operators on X is a complete lattice. In particular an initial structure of fuzzy topological spaces can be obtained by the initial structure of fuzzy closure spaces induced by those. We suggest some examples of it.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.201-208
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• 2014

Park et al. introduced the concept of generalized intuitionistic fuzzy soft sets, which can be seen as an effective mathematical tool to deal with uncertainties. In this paper, we introduce new operations such as restricted union and restricted intersection and study their basic properties, and deal with the algebraic structure of generalized intuitionistic fuzzy soft sets. The lattice structures of generalized intuitionistic fuzzy soft sets are constructed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.298-301
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• 1996

This paper describes the structure Identification of nonlinear function using Adaptive Neuro-Fuzzy Inference Technique(ANFIS). Nonlinear mapping relationship between inputs and outputs were modeled by Sugeno-Takaki's Fuzzy Inference Method. Specially, the consequent parts were identified using a series of 1st order equations and the antecedent parts using triangular type membership function or bell type ones. According to learning Rules of ANFIS, adjustable parameters were converged rapidly and accurately.

• Structural Engineering and Mechanics
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• v.15 no.4
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• pp.451-462
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• 2003

In this paper, a new block iterative algorithm is presented by using the special feature of the continuous Riccati equation in the optimal shape control. Because the real-time control require that the CPU time should be as short as possible, an appropriate modal control algorithm is sought. The computing cost is less than the one of the all state feedback control. A numerical example is given to illustrate the algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.433-439
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• 1998

In this paper, we present an approach to the structure identification based on the input space partition methods and to the parameter identification by hybrid learning method in neuro-fuzzy system. The structure identification can automatically estimate the number of membership function and fuzzy rule using grid partition, tree partition, scatter partition from numerical input-output data. And then the parameter identification is carried out by the hybrid learning scheme using back-propagation and least squares estimate. Finally, we sill show its usefulness for neuro-fuzzy modeling to truck backer-upper control.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.419-428
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• 2007

This paper describes the development of a six-axis force/moment sensor with rectangular taper beams for an intelligent robot's wrist and ankle. In order to accurately push and pull an object with an intelligent robot's hand, and in order to safely walk with an intelligent robot's foot, the robot's wrist and ankle should measure three forces Fx, Fy, and Fz, and three moments Mx, My, and Mz simultaneously from the mounted six-axis force/moment sensor to the intelligent robot's wrist and ankle. Unfortunately, the developed six-axis force/moment sensor utilized in other industrial fields is not proper for an intelligent robot's wrist and ankle in the size and the rated output of the six-axis force/moment sensor. In this paper, the structure of a six-axis force/moment sensor with rectangular taper beams was newly modeled for an intelligent robot's wrist and ankle, and the sensing elements were designed by using the derived equations, following which the six-axis force/moment sensor was fabricated by attaching strain-gages on the sensing elements. Moreover, the characteristic test of the developed sensor was carried out by using the six-component force/moment sensor testing machine. The rated outputs from the derived equations agree well with those from the experiments. The interference error of the sensor is less than 2.87%.

• Advances in nano research
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• v.13 no.1
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• pp.47-61
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• 2022

The present research investigates the dynamic behavior of a rotating functionally graded (FG) nonlocal cylindrical beam. The cylindrical beam is mathematically modeled via third-order beam theory linked with nonlocal strain gradient theory. The tube structure is made of functionally graded materials composed of Aluminum oxide coated on the Nickel, which the mechanical properties vary in the tube radius direction according to the power law. The bending harmonic force is applied in the tube length middle. The nonlocal spinning equations of the tube are derived via the energy method of the Hamilton principle, and they are solved via a robust numerical procedure for different boundary conditions. The main application of the rotating nanostructures is for the production of small-scale motors and devices and the drug-delivery application, the presented results can help the researcher have a better view regarding the different conditions.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.167-181
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• 2024

The soil-structure relative stiffness is a key factor affecting the seismic response of underground structures. It is of great significance to study the soil-structure relative stiffness for the soil-structure interaction and the seismic disaster reduction of subway stations. In this paper, the dynamic shear modulus ratio and damping ratio of an inhomogeneous soft soil site under different buried depths which were obtained by a one-dimensional equivalent linearization site response analysis were used as the input parameters in a 2D finite element model. A visco-elasto-plastic constitutive model based on the Mohr-Coulomb shear failure criterion combined with stiffness degradation was used to describe the plastic behavior of soil. The damage plasticity model was used to simulate the plastic behavior of concrete. The horizontal and vertical relative stiffness ratios of soil and structure were defined to study the influence of relative stiffness on the seismic response of subway stations in inhomogeneous soft soil. It is found that the compression damage to the middle columns of a subway station with a higher relative stiffness ratio is more serious while the tensile damage is slighter under the same earthquake motion. The relative stiffness has a significant influence on ground surface deformation, ground acceleration, and station structure deformation. However, the effect of the relative stiffness on the deformation of the bottom slab of the subway station is small. The research results can provide a reference for seismic fortification of subway stations in the soft soil area.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.122-125
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• 2003

By advent of NNC(Neural Network Chip), it is possible that process in parallel and discern the importance of signal with learning oneself by experience in external signal. So, the design of general purpose operation unit using VHDL(VHSIC Hardware Description Language) on the existing FPGA(Field Programmable Gate Array) can replaced EN(Expert Network) and learning algorithm. Also, neural network operation unit is possible various operation using learning of NN(Neural Network). This paper present general purpose operation unit using hierarchical structure of EN EN of presented structure learn from logical gate which constitute a operation unit, it relocated several layer The overall structure is hierarchical using a module, it has generality more than FPGA operation unit.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.221-224
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• 2001

In this paper, we propose the initial optimized structure of the Radial Basis Function Network which is more simple in the part on the structure and converges more faster than Neural Network with the analysis method using Time-Frequency Localization and genetic algorithm. When we construct the hidden node with the Radial Basis Function whose localization is similar with an approximation target function in the plane of the Time and Frequency, we have initial structure of RBFN, After that, we evaluate the parameters of RBF in the network and the parameters needed for the network is more a few. Finally, we make a good decision of the initial structure having an ability of approximation.