• Title/Summary/Keyword: Set-up 예측

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Planning for Reasonable Construction and Expanding of Distribution Substation By Load Forecasting (부하예측에 의한 합리적인 배전용 변전소 증설계획 수립)

  • Choi, Sang-Bong;Kim, Dae-Kyeong;Jeong, Seong-Hwan;Bae, Jeong-Hyo;Ha, Tae-Hyun;Lee, Hyun-Goo;Kim, Ho-Yong
    • Proceedings of the KIEE Conference
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    • 2000.11a
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    • pp.92-94
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    • 2000
  • This paper presents algorithm to plan construction and expanding of substation considering contingency accidents by proposing utilization factor according to configuration of substation bank system. In this paper, above all, proper sphere of supply area by each district which could be standardized with respect to its supply capacity is established under assumption of long term load forecasting which was made by district respectively, and then goal of utilization ratio based on configuration of substation bank was set to keep reliability by remaining sound bank when it happen to one bank accidents. Finally it is set up for optimal construction and expanding of substation considering economy and reliability simultaneously about substation to exceed these ratio.

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Youtube Mukbang and Online Delivery Orders: Analysis of Impacts and Predictive Model (유튜브 먹방과 온라인 배달 주문: 영향력 분석과 예측 모형)

  • Choi, Sarah;Lee, Sang-Yong Tom
    • Journal of Intelligence and Information Systems
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    • v.28 no.4
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    • pp.119-133
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    • 2022
  • One of the most important current features of food related industry is the growth of food delivery service. Another notable food related culture is, with the advent of Youtube, the popularity of Mukbang, which refers to content that records eating. Based on these background, this study intended to focus on two things. First, we tried to see the impact of Youtube Mukbang and the sentiments of Mukbang comments on the number of related food deliveries. Next, we tried to set up the predictive modeling of chicken delivery order with machine learning method. We used Youtube Mukbang comments data as well as weather related data as main independent variables. The dependent variable used in this study is the number of delivery order of fried chicken. The period of data used in this study is from June 3, 2015 to September 30, 2019, and a total of 1,580 data were used. For the predictive modeling, we used machine learning methods such as linear regression, ridge, lasso, random forest, and gradient boost. We found that the sentiment of Youtube Mukbang and comments have impacts on the number of delivery orders. The prediction model with Mukban data we set up in this study had better performances than the existing models without Mukbang data. We also tried to suggest managerial implications to the food delivery service industry.

Study on Prediction System Construction of Fire.Explosion Accident by NG & LPG among Domestic Gas Accidents (국내 가스 사고사례 중 NG 및 LPG의 가스 화재.폭발사고 예측시스템 구축에 관한 연구)

  • Ko Jae-Sun;Kim Hyo
    • Journal of the Korean Institute of Gas
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    • v.10 no.1 s.30
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    • pp.48-55
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    • 2006
  • In order to establish the comprehensively, quantitatively predictable program to the fire and explosion accidents in the urban gas system, and to set up domestic criteria of societal risk, the collected urban gas accident data have been deeply analyzed. The Poisson probability distribution functions with t=5 for the database of the gas accidents in recent 11 year shows that 'careless work-explosion-pipeline' item has the lowest frequency, whereas 'joint loosening & erosion-release-pipeline' item has the highest frequency. And thus the proper counteractions must be carried out. The further works requires setting up successive database on the fire and explosion accidents systematically to obtain reliable analyses.

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Performance Analysis of Coding According to the Interpolation filter in Inter layer Intra Prediction of H.264/SVC (H.264/SVC의 계층간 화면내 예측에서 보간법에 따른 부호화 성능 분석)

  • Gil, Dae-Nam;Cheong, Cha-Keon
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.225-227
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    • 2009
  • International standard specification, H.264/SVC improved from H.264/AVC, is set up so as to promote free use of huge multimedia data in various channel environments.;H.264/AVC is a international standard speicification for video compression, adopted and commercialized as standard for DMB broadcasting by JVT of ISO/IEC MPEG and ITU-T VCEG. SVC standard uses 'intra/inter prediction' in AVC as well as 'inter-layer intra prediction', 'inter-layer motion prediction' and 'inter-layer residual prediction' to improve efficiency of encoding. Among prediction technologies, 'inter-layer intra prediction' is to use co-located block of up sampled sublevels as a prediction signal. At this time, application of interpolation is one of the most important factors to determine encoding efficiency. SVC's currently using poly-phase FIR filter of 4-tap and 2-tap respectively to luma components. This paper is written for the purpose of analyzing encoding performance according to the interpolation. For this purpose, we applied poly-phase FIR filter of '2-tap', '4-tap' and '6-tap' respectively to luma components and then measured bit-rate, PNSR and running time of interpolation filter. We're expecting that the analysis results of this paper will be utilized for effective application of interpolation filter. SVC standard uses 'intra/inter prediction' in AVC as well as 'inter-layer intra prediction', 'inter-layer motion prediction' and 'inter-layer residual prediction' to improve efficiency of encoding.

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발사전 가열 해석 - Delta II 자료 분석

  • Choi, Sang-Ho;Kim, Seong-Lyong;Kim, In-Sun
    • Aerospace Engineering and Technology
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    • v.4 no.2
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    • pp.126-134
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    • 2005
  • Before the launch, launch vehicle is set up a few days ago at launch pad to check process and to supply fuels, etc. During the prelaunch process, the payload is exposed to the thermal environments. The purpose of a prelaunch thermal analysis is to predict maximum/minimum liftoff temperature of payload fairing and to evaluate air conditioning performance. The prelaunch thermal analysis of Delta II PLF is performed using Sinda/fluint, general thermal/fluid analyzer. The results are analyzed and compared with Delta II report.

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A Study on The Feliability Predication Model of Gyroscope (자이로의 신뢰성 예측모델에 관한 연구)

  • 백순흠;문홍기;김호룡
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1993.10a
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    • pp.475-481
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    • 1993
  • The objective of this study is to develope the reliability prediction model for Float Rated Integrating Gyroscope( :FRIG) at maximum loading. The equation of motion for FRIG is firstly derived to set up the reliability prediction model. To analysis reliability or all parts of the gyro is not easy due to their complicated structure. Therefore the failure parts are chosen by Failure Mode Effective Analysis (:FMEA). F.E.M is utilized to calculate loads for the selseced rotating assembly and pivot / jewel. The technical reliability is calculated by applying reliability design theory with these results and the performance reliability is sought through distribution estimation with error test data. The bulk reliability of gyroscope is sought by applying the two results. The present prediction results are compared with the accumulation time in good agreement.

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A Study on the Using Information of Measuring Data for Safe Construction (안전한 건설공사를 위한 계측정보 활용)

  • 정대석;김춘호
    • The Journal of Information Technology
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    • v.3 no.1
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    • pp.1-8
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    • 2000
  • Recently, many large structures have been constructed so it has been occurred small or big problem. One of problems in a safe construction is that behavior of underground is different between design and construction. Therefore, the purposes this study are that set up measuring equiptments in the site of construction and analyze information of measuring data for removing this problem, and measuring data use for similar method of construction in the engineering of ground.

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A Development of Hotel Bankruptcy Prediction Model on Artificial Neural Network (인공신경망 기반 호텔 부도예측모형 개발)

  • Choi, Sung-Ju;Lee, Sang-Won
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.10
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    • pp.125-133
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    • 2014
  • This paper develops a bankruptcy prediction model on an Artificial Neural Network for hotel management. A bankruptcy prediction model has a specific feature to predict a bankruptcy of the whole hotel business after evaluate bankruptcy possibility on the basis of business performance data of each branch. here are many traditional statistical models for bankruptcy prediction such as Multivariate Discriminant Analysis or Logit Analysis. However, we chose Artificial Neural Network because the method has accuracy rates of prediction better than those of other methods. We first selected 100 good enterprises and 100 bankrupt enterprises as experimental data and set up a bankruptcy prediction model by use of a tool for Artificial Neural Network, NeuroShell. The model and its experiments, which demonstrated high efficiency, can certainly provide great help in decision making in the field of hotel management and in deciding on the bankruptcy or financial solidity of each branch of serviced residence hotel.

A Study on the Cutting Force Simulation for Ball-end Milling Operation (볼-엔드 밀링가공시 절삭력의 시뮬레이션에 관한 연구)

  • 홍민성;김종민
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.12 no.6
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    • pp.84-91
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    • 2003
  • In metal cutting operation, it is very important that predict cutting force and work surface. Vibration is an unstable cutting phenomenon which is due to the interaction of the dynamics of the chip removal process and the structural dynamics of machine tool. When vibration on, it reduces tool life, results in poor surface roughness and low productivity of the machining process. In this study, the experiments were conducted in machining center without cutting fluid to investigate the phenomenon of vibration. In the experiments, accelerometers were set up at the tail stock and tool holder and signals were picked up. Surface roughness profiles are generated under the ideal condition and the occurrence of vibration based on the surface shaping simulation model.

A Study of Traffic Accident Analysis Model on Highway in Accordance with the Accident Rate of Trucks (화물차사고 비율에 따른 고속도로 교통사고 분석모형에 대한 연구)

  • Yang, Sung-Ryong;Yoon, Byoung-jo;Ko, Eun-Hyeok
    • Journal of the Society of Disaster Information
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    • v.13 no.4
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    • pp.570-576
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    • 2017
  • Trucks take up more portions than cars on highways. Due to this, road use relatively diminish and it serves locally as a threatening factor to nearby drivers. Baggage car accident has distinct characteristics so that it needs the application of different analysis opposed to ordinary accidents. Accident prediction model, one of accident analyses, is used to predict the numbers of accident in certain parts, establish traffic plans as well as accident prevention methods, and diagnose the danger of roads. Thus, this study aims to apply the accident rate of baggage car on highways and calculate the correction factor to be put in the accident prediction models. Accident data based on highway was collected and traffic amounts and accident documents between 2014 and 2016 were utilized. The author developed an accident prediction model based on numbers of annual accidents and set mean annual and daily traffic amounts. This study intends to identify the practical accident prediction model on highway and present an appropriate solution by comparing the prediction model in accords with the accident rate between baggage cars.