• 제목/요약/키워드: Neuro control

검색결과 449건 처리시간 0.026초

수문자료가 Neuro-Fuzzy 기법 결과에 미치는 영향 분석 (Analysis of Impact of Hydrologic Data on Neuro-Fuzzy Technique Result)

  • 지정원;최창원;이재응
    • 대한토목학회논문집
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    • 제33권4호
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    • pp.1413-1424
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    • 2013
  • 최근 우리나라에는 집중호우의 발생 빈도가 잦아지고 있다. 집중호우는 단시간에 발생하여 인명과 재산에 직접적인 피해를 주는 특징이 있다. 이러한 이유로 치수에 대한 관심은 점점 높아지고 있으며 정확한 유량 예측을 바탕으로 홍수에 대비할 수 있는 시스템 개발에 대한 연구가 활발하게 이루어지고 있다. 지금까지 홍수 예보에는 주로 물리적 모형이 사용되어 왔다. 물리적 모형은 매개변수 결정을 위해 많은 자료를 필요로 하고 또 매개변수의 결정 과정에서 많은 불확실성을 포함하고 있기 때문에 계산과정을 거치는 동안 다양한 오차가 반복하여 누적되는 단점이 있다. ANFIS는 인공신경회로망과 퍼지기법을 사용한 자료 지향형 모형으로 기존의 물리적 모형에서 사용한 방대한 양의 물리적 자료를 배제하고 유역의 강우자료와 유량자료만을 사용하여 모형을 구축하고 수위를 예측할 수 있다는 장점이 있다. 그러나 자료 지향형 모형은 입력 자료와 결과 사이의 논리적 상관성을 찾을 수 없다는 단점이 있다. 본 연구에서는 ANFIS 모형에 사용되는 함수의 옵션과 입력자료의 특성의 제한적인 변화에 따른 결과자료 분석을 통해 자료 지향형 모형의 특성을 분석하였다. 또한 일반적으로 많이 사용하는 물리적 모형 중 하나인 HEC-HMS의 유출량 산정 결과와의 비교를 통해 ANFIS의 적용성을 평가하였다. 본 연구는 남한강 상류에 위치한 청미천 유역의 2007년부터 2011년까지의 관측 강우자료와 유량자료를 사용하여 수행하였다.

격자 확률신경망 기법을 이용한 구조물의 능동 제어 (Active Control of Structures Using Lattice Probabilistic Neural Network)

  • 김동현;장성규;권순덕;김두기
    • 한국소음진동공학회논문집
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    • 제17권7호
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    • pp.662-667
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    • 2007
  • A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network(PNN). Therefore. it is the so-called lattice probabilistic neural network(LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However. control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for three story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.

역히스테리시스 모델과 PID-신경회로망 제어기를 이용한 압전구동기의 정밀 위치제어 (Precision Position Control of Piezoactuator Using Inverse Hysteresis Model and Neuro-PID Controller)

  • 김정용;이병룡;양순용;안경관
    • 제어로봇시스템학회논문지
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    • 제9권1호
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    • pp.22-29
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    • 2003
  • A piezoelectric actuator yields hysteresis effect due to its composed ferroelectric. Hysteresis nonlinearty is neglected when a piezoelectric actuator moves with short stroke. However when it moves with long stroke and high frequency, the hysteresis nonlinearty can not be neglected. The hysteresis nonlinearty of piezoelectric actuator degrades the control performance in precision position control. In this paper, in order to improve the control performance of piezoelectric actuator, an inverse modeling scheme is proposed to compensate the hysteresis nonlinearty. And feedforward - feedback controller is proposed to give a good tracking performance. The Feedforward controller is an inverse hysteresis model, base on neural network and the feedback control is implemented with PID control. To show the feasibility of the proposed controller and hysteresis modeling, some experiments have been carried out. It is concluded that the proposed control scheme gives good tracking performance.

격자 확률신경망 기법을 이용한 구조물의 능동 제어 (Active Control of Structures Using Lattice Probabilistic Neural Network)

  • 장성규;김두기;김동현;정희영
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 춘계학술대회논문집
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    • pp.978-982
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    • 2007
  • A new neuro-control scheme for active control of structures is proposed. It utilizes lattice pattern of state vector as training data of probabilistic neural network (PNN). Therefore, it is the so-called lattice probabilistic neural network (LPNN). PNN makes control forces by using all the training patterns. Therefore, it takes much time to obtain a control force in application. This inevitably may delay the control action. However, control force of LPNN is calculated by using only the adjacent information of LPNN input. So, the response of LPNN is greatly faster than PNN. The proposed control algorithm is applied for one story building under California and El Centro earthquakes. Also, control results of the LPNN are compared with those of the conventional PNN. The structural responses have been suppressed effectively by the proposed algorithm.

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Dexamethasone Interferes with Autophagy and Affects Cell Survival in Irradiated Malignant Glioma Cells

  • Komakech, Alfred;Im, Ji-Hye;Gwak, Ho-Shin;Lee, Kyue-Yim;Kim, Jong Heon;Yoo, Byong Chul;Cheong, Heesun;Park, Jong Bae;Kwon, Ji Woong;Shin, Sang Hoon;Yoo, Heon
    • Journal of Korean Neurosurgical Society
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    • 제63권5호
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    • pp.566-578
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    • 2020
  • Objective : Radiation is known to induce autophagy in malignant glioma cells whether it is cytocidal or cytoprotective. Dexamethasone is frequently used to reduce tumor-associated brain edema, especially during radiation therapy. The purpose of the study was to determine whether and how dexamethasone affects autophagy in irradiated malignant glioma cells and to identify possible intervening molecular pathways. Methods : We prepared p53 mutant U373 and LN229 glioma cell lines, which varied by phosphatase and tensin homolog (PTEN) mutational status and were used to make U373 stable transfected cells expressing GFP-LC3 protein. After performing cell survival assay after irradiation, the IC50 radiation dose was determined. Dexamethasone dose (10 μM) was determined from the literature and added to the glioma cells 24 hours before the irradiation. The effect of adding dexamethasone was evaluated by cell survival assay or clonogenic assay and cell cycle analysis. Measurement of autophagy was visualized by western blot of LC3-I/LC3-II and quantified by the GFP-LC3 punctuated pattern under fluorescence microscopy and acridine orange staining for acidic vesicle organelles by flow cytometry. Results : Dexamethasone increased cell survival in both U373 and LN229 cells after irradiation. It interfered with autophagy after irradiation differently depending on the PTEN mutational status : the autophagy decreased in U373 (PTEN-mutated) cells but increased in LN229 (PTEN wild-type) cells. Inhibition of protein kinase B (AKT) phosphorylation after irradiation by LY294002 reversed the dexamethasone-induced decrease of autophagy and cell death in U373 cells but provoked no effect on both autophagy and cell survival in LN229 cells. After ATG5 knockdown, radiation-induced autophagy decreased and the effect of dexamethasone also diminished in both cell lines. The diminished autophagy resulted in a partial reversal of dexamethasone protection from cell death after irradiation in U373 cells; however, no significant change was observed in surviving fraction LN229 cells. Conclusion : Dexamethasone increased cell survival in p53 mutated malignant glioma cells and increased autophagy in PTEN-mutant malignant glioma cell but not in PTEN-wildtype cell. The difference of autophagy response could be mediated though the phosphatidylinositol 3-kinase/AKT/mammalian target of rapamycin signaling pathway.

DASH 환경에서 ANFIS 구조를 이용한 비디오 품질 조절 기법 (A Video-Quality Control Scheme using ANFIS Architecture in a DASH Environment)

  • 손예슬;김현준;김준태
    • 방송공학회논문지
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    • 제23권1호
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    • pp.104-114
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    • 2018
  • 최근 HTTP 기반 비디오 스트리밍 트래픽이 계속해서 증가함에 따라 HTTP 기반 적응적 스트리밍(HTTP-based Adaptive Streaming : HAS) 기술 중 하나인 DASH(Dynamic Adaptive Streaming over HTTP)가 주목받고 있다. 이에 따라 DASH 환경에서 클라이언트에게 높은 QoE(Quality of Experience)를 제공하기 위한 많은 비디오 품질 조절 기법들이 제안되어왔다. 본 논문에서는 뉴로 퍼지 시스템의 구조 중 하나인 ANFIS(Adaptive Network based Fuzzy Inference System)를 이용한 새로운 품질 조절 기법을 제안한다. 제안하는 기법은 ANFIS를 이용하여 클라이언트에게 적절한 세그먼트 비트율을 선택하는 퍼지 파라미터를 찾고, VBR(Variable Bit-Rate) 비디오의 특성을 고려하여 실제 세그먼트의 크기를 이용해 다음 세그먼트 다운로드 시간을 보다 정확하게 예측한다. 그리고 이를 이용해 시변 네트워크에서 적절하게 비디오 품질을 조절한다. NS-3를 이용한 모의실험에서 제안된 기법이 기존 기법들에 비해 높은 평균 세그먼트 비트율과 낮은 비트율 변화 횟수를 보여 클라이언트에게 향상된 QoE를 제공함을 보인다.

Online Automatic Gauge Controller Tuning Method by using Neuro-Fuzzy Model in a Hot Rolling Plant

  • Choi, Sung-Hoo;Lee, Young-Kow;Kim, Sang-Woo;Hong, Sung-Chul
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1539-1544
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    • 2005
  • The gauge control of the fishing mill is very important because more and more accurately sized hot rolled coils are demanded by customers recently. Because the mill constant and the plasticity coefficient vary with the specifications of the mill, the classification of steel, the strip width, the strip thickness and the slab temperature, the variation of these parameters should be considered in the automatic gauge control system(AGC). Generally, the AGC gain is used to minimize the effect of the uncertain parameters. In a practical field, operators set the AGC gain as a constant value calculated by FSU (Finishing-mill Set-Up model) and it is not changed during the operating time. In this paper, the thickness data signals that occupy different frequency bands are respectively extracted by adaptive filters and then the main cause of the thickness variation is analyzed. Additionally, the AGC gain is adaptively tuned to reduce this variation using the online tuning model. Especially ANFIS(Adaptive-Neuro-based Fuzzy Interface System) which unifies both fuzzy logics and neural networks, is used for this gain adjustment system because fuzzy logics use the professionals' experiences about the uncertainty and the nonlinearity of the system. Simulation is performed by using POSCO's data and the results show that proposed on-line gain adjustment algorithm has a good performance.

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A Self-Organizing Model Based Rate Control Algorithm for MPEG-4 Video Coding

  • Zhang, Zhi-Ming;Chang, Seung-Gi;Park, Jeong-Hoon;Kim, Yong-Je
    • 대한전자공학회논문지SP
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    • 제40권1호
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    • pp.72-78
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    • 2003
  • 본 논문에서는 자기구성 뉴로퍼지 네트워크를 이용한 MPEG-4 비트율 제어알고리즘을 제안한다. 경험적인 수식을 바탕으로 rate-distortion(RD) 모델을 구성하는 일반적인 방법과는 달리 제안하는 알고리즘의 기본적인 아이디어는 온라인으로 RD모델을 스스로 구성하고 매 프레임마다 그 구조를 적응적으로 업데이트하는 SOLPN을 이용해 RD 모델을 구현하는 것으로 많은 비트율 제어 방식 중 프레임을 기반으로 한 비트율 제어만을 본 논문에서는 고려한다. 특히 이 알고리즘은 오프라인에서 미리 트레이닝하는 것이 필요가 없기 때문에 실시간 코딩에도 적용 가능하다. VM18.0과의 비교 실험 결과들을 보면 본 논문에서 제안하는 비트율제어 알고리즘이 VMl8.0〔16〕에 비해 주관적인 화질 향상뿐만 아니라 적은 프레임 스킵(franc skip)과 높은 PSNR을 나타낸다.

Positioning control of pzt actuators using neuro control with hysteresis model (ICCAS 2003)

  • Lee, Byung-Ryong;Lee, Soo-Hee;Yang, Soon-Yong;Ahn, Kyung-Kwan
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.382-385
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    • 2003
  • In this paper, in order to improve the control performance of piezoelectric actuator, an integrated control structure is proposed. The control structure consists of inverse hysteresis model , to compensate the hysteresis nonlinearty problem, and feedforward - feedback controller to give a good tracking performance. The inverse hysteresis model and neural network are used as feed-forward controller, and PID controller is used as a feedback controller. From diverse experiments it is concluded that the proposed control scheme gives good tracking performance than the classical control does.

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제진장치 설치 해양구조물의 생애주기 지진위험도 (Lifetime Seismic Risk of Offshore Structures with a Built-in Vibration Control Device)

  • 김동현
    • 한국해양공학회지
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    • 제24권5호
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    • pp.48-54
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    • 2010
  • The analysis of the seismic risk of an offshore structure with a control device is presented. First, a probability density function was developed to represent seismic hazard, and seismic fragility under artificial earthquake conditions was determined. Fragility curves for an offshore structure with both passive and active control devices were determined. Displacement criteria were set to evaluate the performance of the structure. Based on numerical analysis, the seismic risk to the structure was considerably reduced when the structure had a seismic control device. The seismic risk to the actively controlled structure was decreased by 80% compared to the uncontrolled case. Reasonable performance evaluations of offshore structure with control devices can be conducted through risk analysis.