• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.140-147
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• 2008

This paper describes a Neural Network based PD control scheme for motion control of pneumatic servo cylinder. Pneumatic systems have inherent nonlinearities such as compressibility of air and nonlinear frictions present in cylinder. The conventional linear controller is limited in some applications where the affection of nonlinear factor is dominant. A self-excited oscillation method is applied to derive the dynamic design parameters of linear model. Based on the parameters thus identified, a PD feedback compensator is designed first and then a neural network is incorporated. The experiments of a trajectory tracking control using the proposed control scheme are performed and a significant reduction in tracking error is achieved by comparing with those of a PD control.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.253-257
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• 2000

the objective of this study is to design and evaluate a methodology for diagnosing the appendicitis in a fuzzy neural network that integrates the partition of input space by fuzzy entropy and the generation of fuzzy control rules and learning algorithm. In particular the diagnosis of appendicitis depends on the rule of thumb of the experts such that it associates with the region, the characteristics, the degree of the ache and the potential symptoms. In this scheme the basic idea is to realize the fuzzy rle base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by back propagation learning rule. To eliminate the number of the parameters of the rules, the output of the consequences of the control rules is expressed by the network's connection weights. As a result we obtain a method for reducing the system's complexities. Through computer simulations the effectiveness of the proposed strategy is verified for the diagnosis of appendicitis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.168-171
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• 2002

A neural network model for predicting the quality or soundness of the injected plastic aspherical lens based on process parameters has been developed. The approach uses a Real Time Recurrent Neural Network 4-5-2 (RTRN) trained based on input/output data that were taken from FE analysis worts carried out through a CAE software. The system has been developed to search an optimum set of process parameters and reduce the time required for planning the conditions of plastic injection molding at the design stage.

• Structural Engineering and Mechanics
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• v.29 no.1
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• pp.77-89
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• 2008

Presence of high degree of orthotropy enhances shear lag phenomenon in laminated composite box-beams and it persists till failure. In this paper three key parameters governing shear lag behavior of laminated composite box beams are identified and defined by simple expressions. Uniqueness of the identified key parameters is proved with the help of finite element method (FEM) based studies. In addition to this, for the sake of generalization of prediction of shear lag effect in symmetrical laminated composite box beams a feed forward back propagation neural network (BPNN) model is developed. The network is trained and tested using the data base generated by extensive FEM studies carried out for various b/D, b/tF, tF/tW and laminate configurations. An optimum network architecture has been established which can effectively learn the pattern. Computational efficiency of the developed ANN makes it suitable for use in optimum design of laminated composite box-beams.

• Nuclear Engineering and Technology
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• v.31 no.3
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• pp.276-286
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• 1999

A computer code PARS2 is developed for the analysis of PSDRS, which is the safety grade RHRS of HAMMER, and applied to the investigation of the relation between design parameters and performance of PSDRS. The concept of the heat transfer resistance network is applied in assessing the importance of the various heat transfer modes. From the analysis results, the qualitative relations between the PSDRS performance and design parameters are found and guidelines for the PSDRS design procedures are also proposed.

• Computers and Concrete
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• v.3 no.5
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• pp.357-373
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• 2006

The concepts of four parameters of nominal water-cement ratio, equivalent water-cement ratio, average paste thickness, fly ash-binder ratio were introduced. It was verified that the four parameters and the mix proportion of mortar can be transformed each other. The behaviors (strength, workability, et al.) of mortar primarily determined by the mix proportion of mortar now depend on the four parameters. The prediction models of strength and workability of mortar were built based on artificial neural networks (ANNs). The calculation models of average paste thickness and equivalent water-cement ratio of mortar can be obtained by the reversal deduction of the two prediction models, respectively. A mortar mix proportion design algorithm was proposed. The proposed mortar mix proportion design algorithm is expected to reduce the number of trial and error, save cost, laborers and time.

• Proceedings of the KIEE Conference
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• 1994.07a
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• pp.444-446
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• 1994

This paper describes the design of a digital multifunction controller for the intelligent high voltage customer switchboard and proposes a relaying algorithm for high impedance faults using back-propagation neural network. The hardware design uses the three microprocessors and global memory architecture to achive real time operation and control 4 feeders. The controller uses a 64-point radix-4 DIF FFT algorithm to measure the harmonic and relay parameters. Synthesized fault current waveforms are used to train and test the back - propagation network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.291-300
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• 2006

In this study a statistical water quality monitoring network design of Kyung-An stream is proposed. Water quality data for the design is obtained by QUAL2E model simulation. The observed monthly average water quality data from March to November in Kyung-An stream has been applied to this study. HEC-RAS model is also used for QUAL2E hydrauric parameter estimation. Before QUAL2E water quality parameter estimation, FORA is performed to reduce the number of parameters to be estimated, and then water quality parameters are calibrated with a observed monthly average data. Using these simulated water quality data, the number of gage station and its location are estimated by kriging theory and branch & boundary method. Such a network design is based on two case; average flow and low flow case, respectively. Next, proportional sampling method is applied to estimate the sampling frequency.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.63-68
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• 2015

Pattern layout design is very important to the automation of apparel industry. Until now, the genetic algorithm and Tabu search method have been applied to layout design automation. With the genetic algorithm and Tabu search method, the obtained values are not always consistent depending on the initial conditions, number of iterations, and scheduling. In addition, the selection of various parameters for these methods is not easy. This paper presents a hybrid search method that uses a neural network and simulated annealing to solve these problems. The layout of pattern elements was optimized to verify the potential application of the suggested method to apparel pattern layout design.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.2
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• pp.63-68
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• 2004

This paper presents an approach to optimum design of Moving Magnet Type Linear Oscillatory Actuator(MM-LOA). The Finite Element Method is applied to characteristic parameters for characteristic analysis and in order to reduce modeling time and efforts, the moving model node technique is used. In addition the neural network is used to reduce computational time of analysis according to changing design variable. To confirm the validity of this study, optimum design results are compared with results of analysis procedure that is verified by experiment.