• Title/Summary/Keyword: Input-output method

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Modeling of Self-Constructed Clustering and Performance Evaluation (자기-구성 클러스터링의 모델링 및 성능평가)

  • Ryu Jeong woong;Kim Sung Suk;Song Chang kyu;Kim Sung Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.6C
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    • pp.490-496
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    • 2005
  • In this paper, we propose a self-constructed clustering algorithm based on inference information of the fuzzy model. This method makes it possible to automatically detect and optimize the number of cluster and parameters by using input-output data. The propose method improves the performance of clustering by extended supervised learning technique. This technique uses the output information as well as input characteristics. For effect the similarity measure in clustering, we use the TSK fuzzy model to sent the information of output. In the conceptually, we design a learning method that use to feedback the information of output to the clustering since proposed algorithm perform to separate each classes in input data space. We show effectiveness of proposed method using simulation than previous ones

PWM Controlled Cycloconverter (PWM 제어형 Cycloconverter)

  • Lee, Jong-Moo;Koo, Heun-Hoi;Kim, Young-Seok
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.518-521
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    • 1989
  • Recently, PWM cycloconverters that are frequency conversion system have been studied for eliminating do links of conventional converter and inverter systems. A new real-time method for generating PWM patterns is proposed in this paper. This method realizes sinusoidal input and output currents, controllable input displacement factor regardless of load power factor, and maximum output voltage range. Finally, feasibility of the proposed method is confirmed by simulation and experiments.

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Quadratic Loss Support Vector Interval Regression Machine for Crisp Input-Output Data

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.449-455
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    • 2004
  • Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval regression models for crisp input-output data. The proposed method is based on quadratic loss SVM, which implements quadratic programming approach giving more diverse spread coefficients than a linear programming one. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function. Experimental result is then presented which indicate the performance of this algorithm.

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Input Variable Importance in Supervised Learning Models

  • Huh, Myung-Hoe;Lee, Yong Goo
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.239-246
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    • 2003
  • Statisticians, or data miners, are often requested to assess the importances of input variables in the given supervised learning model. For the purpose, one may rely on separate ad hoc measures depending on modeling types, such as linear regressions, the neural networks or trees. Consequently, the conceptual consistency in input variable importance measures is lacking, so that the measures cannot be directly used in comparing different types of models, which is often done in data mining processes, In this short communication, we propose a unified approach to the importance measurement of input variables. Our method uses sensitivity analysis which begins by perturbing the values of input variables and monitors the output change. Research scope is limited to the models for continuous output, although it is not difficult to extend the method to supervised learning models for categorical outcomes.

Runoff Analysis Using the Discrete, Linear, Input-Output Model (선형 이산화 입력-출력 모형에 의한 유출해석)

  • Kwak, Ki Seok;Kang, In Shik;Jeong, Yeon Tae;Kang, Ju Bok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.14 no.4
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    • pp.859-866
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    • 1994
  • It is difficult to make an exact estimate of the peak discharge or the runoff depth of flood and establish the proper measure for the flood protection since the water stage or discharge has been nearly measured at most medium or small river basins. The objective of this study is to estimate parameters of the discrete, linear, input-output model for medium or small river basin. The On-Cheon River basin in Pusan was selected for the study area. The runoff data used in the study has been observed since June 1993, and the effective rainfall was determined using the storage function method. The parameter sets of the discrete, linear, input-output model were estimated using the least squares method and the correlation function method, respectively. The calculated hydrographs by the discrete, linear, input-output model regenerated the observed outflow hydrographs well, and also the simulated flood hydrograph was comparable to the observed one. Therefore, it is believed that the discrete, linear, input-output model is simpler than other runoff analysis methods, and can be applied to a medium or small river basin.

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A Control Strategy to Obtain Sinusoidal Input Currents of Matrix Converter under Unbalanced Input Voltages

  • Nguyen, Thanh-Luan;Lee, Hong-Hee
    • Proceedings of the KIPE Conference
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    • 2018.07a
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    • pp.114-116
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    • 2018
  • This paper presents a control strategy to achieve the balanced sinusoidal output currents, as well as sinusoidal input currents for the matrix converter (MC) under unbalanced input voltages. By regulating the modulation index of the converter according to the instantaneous input voltages, the output currents are kept balanced and sinusoidal. In order to obtain sinusoidal input currents, the input power factor angle should be dynamically calculated based on the positive and negative sequence components of the input voltages. This paper proposes a simple method to construct the expected input power factor angle without the complicated sequence component extraction of input voltages. Simulation results are given to validate the effectiveness of the proposed control strategy.

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DSP Based Series-Parallel Connected Two Full-Bridge DC-DC Converter with Interleaving Output Current Sharing

  • Sha, Deshang;Guo, Zhiqiang;Lia, Xiaozhong
    • Journal of Power Electronics
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    • v.10 no.6
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    • pp.673-679
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    • 2010
  • Input-series-output-parallel (ISOP) connected DC-DC converters enable low voltage rating switches to be used in high voltage input applications. In this paper, a DSP is adopted to generate digital phase-shifted PWM signals and to fulfill the closed-loop control function for ISOP connected two full-bridge DC-DC converters. Moreover, a stable output current sharing control strategy is proposed for the system, with which equal sharing of the input voltage and the load current can be achieved without any input voltage control loops. Based on small signal analysis with the state space average method, a loop gain design with the proposed scheme is made. Compared with the conventional IVS scheme, the proposed strategy leads to simplification of the output voltage regulator design and better static and dynamic responses. The effectiveness of the proposed control strategy is verified by the simulation and experimental results of an ISOP system made up of two full-bridge DC-DC converters.

Input-output Coupler System with 45-degree Slant Angle Based on Bragg Hologram

  • Phan, Anh-Hoang;Kim, Nam;Park, Jae-Hyeung;Lee, Kwon-Yeon
    • Journal of the Optical Society of Korea
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    • v.13 no.1
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    • pp.123-130
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    • 2009
  • In this paper, we designed and fabricated an input-output coupler system using two or three volume gratings at 632.8nm wavelength. The additional third grating is added at the output coupler to enhance the overall efficiency. The experimental results show that the total system throughput reaches 63% with two-grating and 75% with three-grating input-output coupler. We also present a design method to obtain the desired output power ratio between the gratings.

Fuzzy control system design by data clustering in the input-output subspaces (입출력 부공간에서의 데이터 클러스터링에 의한 퍼지제어 시스템 설계)

  • 김민수;공성곤
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.12
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    • pp.30-40
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    • 1997
  • This paper presents a design method of fuzzy control systems by clustering the data in the subspace of the input-output produyct space. In the case of servo control, most input-outputdata are concentrated in thye steady-state region, and the the clustering will result in only steady-state fuzzy rules. To overcome this problem, we divide the input-output product space into some subspaces according to the state of input variables. The fuzzy control system designed by the subspace clustering showed good transient response and smaller steady-state error, which is comparable with the reference fuzzy system.

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Identification of continuous time-delay systems using the genetic algorithm

  • Hachino, Tomohiro;Yang, Zi-Jiang;Tsuji, Teruo
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.1-6
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    • 1993
  • This report proposes a novel method of identification of continuous time-delay systems from sampled input-output data. By the aid of a digital pre-filter, an approximated discrete-time estimation model is first derived, in which the system parameters remain in their original form and the time delay need not be an integral multiple of th sampling period. Then an identification method combining the common linear least squares(LS) method or the instrumental variable(IV) method with the genetic algorithm(GA) is proposed. That is, the time-delay is selected by the GA, and the system parameters are estimated by the LS or IV method. Furthermore, the proposed method is extended to the case of multi-input multi-output systems where the time-delays in the individual input channels may differ each other. Simulation resutls show that our method yields consistent estimates even in the presence of high measurement noises.

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