• 제목/요약/키워드: output prediction

검색결과 733건 처리시간 0.03초

A SENSITIVITY ANALYSIS OF THE KEY PARAMETERS FOR THE PREDICTION OF THE PRESTRESS FORCE ON BONDED TENDONS

  • Jang, Jung-Bum;Lee, Hong-Pyo;Hwang, Kyeong-Min;Song, Young-Chul
    • Nuclear Engineering and Technology
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    • 제42권3호
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    • pp.319-328
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    • 2010
  • Bonded tendons have been used in reactor buildings at some operating nuclear power plants in Korea. Assessing prestress force on these bonded tendons has become an important pending problem in efforts to assure continued operation beyond their design life. The System Identification (SI) technique was thus developed to improve upon the existing indirect assessment technique for bonded tendons. As a first step, this study analyzed the sensitivity of the key parameters to prestress force, and then determined the optimal parameters for the SI technique. A total of six scaled post-tensioned concrete beams with bonded tendons were manufactured. In order to investigate the correlation of the natural frequency and the displacement to prestress force, an impact test, a Single Input Multiple Output (SIMO) sine sweep test, and a bending test using an optical fiber sensor and compact displacement transducer were carried out. These tests found that both the natural frequency and the displacement show a good correlation with prestress force and that both parameters are available for the SI technique to predict prestress force. However, displacements by the optical fiber sensor and compact displacement transducer were shown to be more sensitive than the natural frequency to prestress force. Such displacements are more useful than the natural frequency as an input parameter for the SI technique.

단인 통과 라만레이저의 집속 조건에 따른 출력 특성 (Focusing Geometry Dependence of Single Pass Raman Shifer)

  • 고춘수
    • 한국광학회지
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    • 제4권4호
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    • pp.434-441
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    • 1993
  • 단일 통과 라만레이저에서 접속 조건에 따른 1차 Stokes 파의 출력특성을 조사하였다. 펌푸빔으로는 Q-switched Nd-YAG 레이저의 기본파인 파장 $1.06{\mu}m$의 빔을 사용하였고 매질로는 고압 메탄을 사용하엿다. 실험 결과 펌프빔을 라만셀로 집속하는 조건에 따라 큰 출력의 치이를 보였는데, 집속상수가 클수록 Stokes 출력이 증가하였다. 이러한 결과는 Stokes와 anti-Stokes의 결합에 의한 이득감소로 이해할 수 있는데, 여기서는 간단한 이론을 통해 집속 조건에 따른 Stokes와 anti-Stokes의 결합의 정도를 알아보고 이득감소 현상을 피하기 위한 집속상수의 기준을 제시하였다. 라만 산란에 수반되는 유도 Brillouin 산란을 측정한 결과 문턱에너지가 집속상수에 비례하여 증가하였고, 이론적으로 이는 다중 모드 레이저를 펌프로 사용할 때 상호작용 거리가 간석성 거리로 제한되어 나타나는 현상으로 이해할 수 있으면 간섭성 거리를 2mm라 했을 때 실험 결과와 비교적 잘 일치하였다.

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조광제어 시스템 적용시 실내조도의 변동예측을 위한 포토센서의 주광조도 분석 (Analyses on Photosensor Illuminance for Prediction of Fluctuating Illuminance by Daylight Dimming Control Systems)

  • 김수영
    • 설비공학논문집
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    • 제22권11호
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    • pp.788-797
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    • 2010
  • This study examines the influence of fluctuating daylight illuminance on daylight dimming control systems. Field measurements were performed for a full-scale mocked-up model under various daylight conditions in winter. Fluctuating ranges for a partially-shielded photosensor were great when the variation of sky ratio was great. When solar altitude was lower the illuminance and fluctuating range of illuminance were great due to the influence of direct components of daylight and the interrefelction between surfaces in rear area of space. It implies that daylight dimming system would not function effectively, unless the desktop illuminance by daylight is enough. Fluctuation ranges of photosensor illuminance were lower than 50 lx under clear sky conditions, but they were greater than 100 lx under partly-cloudy sky conditions. It means that the fluctuation range of electric light output of lighting fixture would greater under the partly-cloudy conditions and cause potential visual annoyance to occupants. Outdoor vertical illuminance reaching the windows would be an effective factor that can be used to predict the fluctuation of photosensor signals for effective controls of daylight dimming system.

차량 연료 소모량 예측을 위한 신경회로망 기반 모델링 (Neural Network-Based Modeling for Fuel Consumption Prediction of Vehicle)

  • 이민구;정경권;이상회
    • 전자공학회논문지 IE
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    • 제48권2호
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    • pp.19-25
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    • 2011
  • 본 논문에서는 연료 소모량을 예측하기 위해 차량 데이터를 이용한 신경회로망 모델링 방식을 제안하였다. 제안한 신경회로망의 훈련과 시험 데이터를 획득하기 위해 시내를 중형 가솔린 차량을 주행하였고, OBD-II 포트에서 입력 데이터로 속도, 엔진 RPM, 쓰로틀 위치 센서(TPS), 흡기 공기량(MAF)을 측정하였고, 목표값으로 연료 소모량을 측정하였다. 입력과 출력 데이터의 빈선형 맵핑을 위해 다층 퍼셉트론 네트워크를 사용하였다. 신경회로망 모델은 평균 제곱오차가 $1.306{\times}10^{-6}$로 연료 소모량을 매우 잘 예측함을 확인하였다.

Estimation of Concrete Strength Using Improved Probabilistic Neural Network Method

  • Kim Doo-Kie;Lee Jong-Jae;Chang Seong-Kyu
    • 콘크리트학회논문집
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    • 제17권6호
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    • pp.1075-1084
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    • 2005
  • The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network(PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Improved probabilistic neural network was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment (DDA) algorithm. The conventional PNN and the PNN with DDA algorithm(IPNN) were applied to predict the compressive strength of concrete using actual test data of two concrete companies. IPNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

편측 인공와우 이식자의 보청기 사용 (Use of Hearing Aids in Unilateral Cochlear Implantee)

  • 허승덕;김리석;정동근;최아현;고도홍;김현기
    • 음성과학
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    • 제12권4호
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    • pp.197-202
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    • 2005
  • The cochlear implantation(CI) as an useful tool for aural rehabilitation in bilateral severe to profound hearing impairment. However, CI prefer to usually one ear in spite of bilateral hearing impaired. because of the various characteristics of hearing loss, the hearing conservation for the future possibility, and socioeconomic condition of hearing impaired person and their families. The unilateral CI has limitations such as a directional loss, a difficult speech understanding in noise and a neural plasticity. These limitations will be overcome by hearing aid(HA) which is familiar with hearing impairer. but HA fitting for bimodal-binaural hearing are difficult because the difference output characteristic of HA and CI. This study will be confirm realities of use of HA in unilateral cochlear implantee. For this goal, 25(m:f=10:15) child participated who are used to HA for 1 to 17 months. We had telephone interviews with their mother about use of HA, change of auditory performance and own voice. As the results, hearing threshold levels of unimplanted ear, the use of a appropriate HA, implanted and aided hearing threshold level(HTL) are must be considered for successful biomodal-binaural hearing. Especially, implanted and aided HTL should be very useful parameter for a prediction of HA effect and a criterion of selection for bilateral cochlear implantation.

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소프트웨어 정의 모바일 에지 차량 네트워크(SDMEVN)의 센싱 데이터 수집 전략 (A Sensing Data Collection Strategy in Software-Defined Mobile-Edge Vehicular Networks (SDMEVN))

  • 라이오넬;장종욱
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 추계학술대회
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    • pp.62-65
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    • 2018
  • This paper comes out with the study on sensing data collection strategy in a Software-Defined Mobile Edge vehicular networking. The two cooperative data dissemination are Direct Vehicular cloud mode and edge cell trajectory prediction decision mode. In direct vehicular cloud, the vehicle observe its neighboring vehicles and sets up vehicular cloud for cooperative sensing data collection, the data collection output can be transmitted from vehicles participating in the cooperative sensing data collection computation to the vehicle on which the sensing data collection request originate through V2V communication. The vehicle on which computation originate will reassemble the computation out-put and send to the closest RSU. The SDMEVN (Software Defined Mobile Edge Vehicular Network) Controller determines how much effort the sensing data collection request requires and calculates the number of RSUs required to support coverage of one RSU to the other. We set up a simulation scenario based on realistic traffic and communication features and demonstrate the scalability of the proposed solution.

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Analyzing the compressive strength of clinker mortars using approximate reasoning approaches - ANN vs MLR

  • Beycioglu, Ahmet;Emiroglu, Mehmet;Kocak, Yilmaz;Subasi, Serkan
    • Computers and Concrete
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    • 제15권1호
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    • pp.89-101
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    • 2015
  • In this paper, Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) models were discussed to determine the compressive strength of clinker mortars cured for 1, 2, 7 and 28 days. In the experimental stage, 1288 mortar samples were produced from 322 different clinker specimens and compressive strength tests were performed on these samples. Chemical properties of the clinker samples were also determined. In the modeling stage, these experimental results were used to construct the models. In the models tricalcium silicate ($C_3S$), dicalcium silicate ($C_2S$), tricalcium aluminate ($C_3A$), tetracalcium alumina ferrite ($C_4AF$), blaine values, specific gravity and age of samples were used as inputs and the compressive strength of clinker samples was used as output. The approximate reasoning ability of the models compared using some statistical parameters. As a result, ANN has shown satisfying relation with experimental results and suggests an alternative approach to evaluate compressive strength estimation of clinker mortars using related inputs. Furthermore MLR model showed a poor ability to predict.

결함검출을 위한 실험적 연구

  • 목종수
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 1996년도 춘계학술대회 논문집
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    • pp.24-29
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    • 1996
  • The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

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Statistical Prediction of Wake Fields on Propeller Plane by Neural Network using Back-Propagation

  • Hwangbo, Seungmyun;Shin, Hyunjoon
    • Journal of Ship and Ocean Technology
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    • 제4권3호
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    • pp.1-12
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    • 2000
  • A number of numerical methods like Computational Fluid Dynamics(CFD) have been developed to predict the flow fields of a vessel but the present study is developed to infer the wake fields on propeller plane by Statistical Fluid Dynamics(SFD) approach which is emerging as a new technique over a wide range of industrial fields nowadays. Neural network is well known as one prospective representative of the SFD tool and is widely applied even in the engineering fields. Further to its stable and effective system structure, generalization of input training patterns into different classification or categorization in training can offer more systematic treatments of input part and more reliable result. Because neural network has an ability to learn the knowledge through the external information, it is not necessary to use logical programming and it can flexibly handle the incomplete information which is not easy to make a definition clear. Three dimensional stern hull forms and nominal wake values from a model test are structured as processing elements of input and output layer respectively and a neural network is trained by the back-propagation method. The inferred results show similar figures to the experimental wake distribution.

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