• Title/Summary/Keyword: Position Prediction

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Development of Prediction Model for Fill Slope Failure of Forest Road (임도성토사면(林道盛土斜面)의 붕괴예측(崩壞豫測)모델 개발(開發))

  • Cha, Du Song;Ji, Byoung Yun
    • Journal of Korean Society of Forest Science
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    • v.90 no.3
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    • pp.324-330
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    • 2001
  • This study was carried out to develop prediction model for fill slope failure of forest road in igneous rock area using fuzzy theory which is non-linear model. The results were summarized as follows. The importance weight of factors on fill slope failure was ranked in the order of fill slope length, fill slope gradient, soil type, aspect, road position and longitudinal slope form. The degree of potential slope failure was high mainly under the such conditions as fill slope length greater than 8m, fill slope gradients steeper than $40^{\circ}$, constituent material with weathered rock, aspect of NE and road on ridge position. The optimal prediction model was developed with 0.15 of optimal coefficient(c) and 3.1165 of ${\lambda}$-value when fuzzy integral value of slope failure possibility is more than 0.5. And the discriminant accuracy was 86.8%, which shows the high availability for discrimination.

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Analysis of prediction model for solar power generation (태양광 발전을 위한 발전량 예측 모델 분석)

  • Song, Jae-Ju;Jeong, Yoon-Su;Lee, Sang-Ho
    • Journal of Digital Convergence
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    • v.12 no.3
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    • pp.243-248
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    • 2014
  • Recently, solar energy is expanding to combination of computing in real time by tracking the position of the sun to estimate the angle of inclination and make up freshly correcting a part of the solar radiation. Solar power is need that reliably linked technology to power generation system renewable energy in order to efficient power production that is difficult to output predict based on the position of the sun rise. In this paper, we analysis of prediction model for solar power generation to estimate the predictive value of solar power generation in the development of real-time weather data. Photovoltaic power generation input the correction factor such as temperature, module characteristics by the solar generator module and the location of the local angle of inclination to analyze the predictive power generation algorithm for the prediction calculation to predict the final generation. In addition, the proposed model in real-time national weather service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

A Study on the Estimation of Ship Location Information in the Intelligent Maritime Traffic Information System (지능형 해상교통정보시스템의 선박 위치 정보 추정 연구)

  • Deuk-Jae Cho
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.313-314
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    • 2022
  • The intelligent maritime traffic information service provides a service to prevent collisions and stranding of ships based on the location information of ships periodically collected from ship equipment such as LTE-Maritime transceivers and AIS installed on ships. provided in real time. However, the above service may reduce the reliability of ship location information because GPS location information for measuring the ship's location may be cut off during transmission through LTE-Maritime or AIS networks, or phenomena such as location jumps and delays may occur. This study aims to estimate reliable position information to some extent even in an abnormal section through ship position prediction based on the existing received position information using the Kalman filter, which is an optimal estimation filter based on probability.

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Evaluating Distress Prediction Models for Food Service Franchise Industry (외식프랜차이즈기업 부실예측모형 예측력 평가)

  • KIM, Si-Joong
    • Journal of Distribution Science
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    • v.17 no.11
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    • pp.73-79
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    • 2019
  • Purpose: The purpose of this study was evaluated to compare the predictive power of distress prediction models by using discriminant analysis method and logit analysis method for food service franchise industry in Korea. Research design, data and methodology: Forty-six food service franchise industry with high sales volume in the 2017 were selected as the sample food service franchise industry for analysis. The fourteen financial ratios for analysis were calculated from the data in the 2017 statement of financial position and income statement of forty-six food service franchise industry in Korea. The fourteen financial ratios were used as sample data and analyzed by t-test. As a result seven statistically significant independent variables were chosen. The analysis method of the distress prediction model was performed by logit analysis and multiple discriminant analysis. Results: The difference between the average value of fourteen financial ratios of forty-six food service franchise industry was tested through t-test in order to extract variables that are classified as top-leveled and failure food service franchise industry among the financial ratios. As a result of the univariate test appears that the variables which differentiate the top-leveled food service franchise industry to failure food service industry are income to stockholders' equity, operating income to sales, current ratio, net income to assets, cash flows from operating activities, growth rate of operating income, and total assets turnover. The statistical significances of the seven financial ratio independent variables were also confirmed by logit analysis and discriminant analysis. Conclusions: The analysis results of the prediction accuracy of each distress prediction model in this study showed that the forecast accuracy of the prediction model by the discriminant analysis method was 84.8% and 89.1% by the logit analysis method, indicating that the logit analysis method has higher distress predictability than the discriminant analysis method. Comparing the previous distress prediction capability, which ranges from 75% to 85% by discriminant analysis and logit analysis, this study's prediction capacity, which is 84.8% in the discriminant analysis, and 89.1% in logit analysis, is found to belong to the range of previous study's prediction capacity range and is considered high number.

ARMA-based data prediction method and its application to teleoperation systems (ARMA기반의 데이터 예측기법 및 원격조작시스템에서의 응용)

  • Kim, Heon-Hui
    • Journal of Advanced Marine Engineering and Technology
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    • v.41 no.1
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    • pp.56-61
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    • 2017
  • This paper presents a data prediction method and its application to haptic-based teleoperation systems. In general, time delays inevitably occur during data transmission in a network environment, which degrades the overall performance of haptic-based teleoperation systems. To address this situation, this paper proposes an autoregressive moving average (ARMA) model-based data prediction algorithm for estimating model parameters and predicting future data recursively in real time. The proposed method was applied to haptic data captured every 5 ms while bilateral haptic interaction was carried out by two users with an object in a virtual space. The results showed that the prediction performance of the proposed method had an error of less than 1 ms when predicting position-level data 100 ms ahead.

Verification of Validity of Governing Factors in High Accurate Prediction of Welding Distortion (용접변형의 고정도 예측을 위한 지배인자의 정당성 검증)

  • Lee, Jae-Yik;Chang, Kyong-Ho;Kim, You-Chul
    • Journal of Welding and Joining
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    • v.31 no.5
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    • pp.7-14
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    • 2013
  • The legitimacy of dominating factor in the high accuracy prediction of welding distortion was investigated for butt welding and fillet welding. When out-of-plane distortion was measured by the experiment objecting to butt welding, if tack welding was easily performed, the position of a neutral axis was variously changed by the irregularity. Then, there have been a case that out-of-plane distortion was generated in the unexpected direction. This case should be especially noted. New model for the experiment was proposed so as to solve this problem. As it was elucidated by the case of fillet welding, it was verified that the analysis should be carried out with satisfying the yield condition (especially at high temperature above 700 degree Celsius) and with closely simulating the penetration shape (heat input in weld metal) in order to solve the proposition that is the high accuracy prediction of welding distortion. It was confirmed that residual stress is highly predicted because welding distortion is highly predicted, too.

Sums-of-Products Models for Korean Segment Duration Prediction

  • Chung, Hyun-Song
    • Speech Sciences
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    • v.10 no.4
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    • pp.7-21
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    • 2003
  • Sums-of-Products models were built for segment duration prediction of spoken Korean. An experiment for the modelling was carried out to apply the results to Korean text-to-speech synthesis systems. 670 read sentences were analyzed. trained and tested for the construction of the duration models. Traditional sequential rule systems were extended to simple additive, multiplicative and additive-multiplicative models based on Sums-of-Products modelling. The parameters used in the modelling include the properties of the target segment and its neighbors and the target segment's position in the prosodic structure. Two optimisation strategies were used: the downhill simplex method and the simulated annealing method. The performance of the models was measured by the correlation coefficient and the root mean squared prediction error (RMSE) between actual and predicted duration in the test data. The best performance was obtained when the data was trained and tested by ' additive-multiplicative models. ' The correlation for the vowel duration prediction was 0.69 and the RMSE. 31.80 ms. while the correlation for the consonant duration prediction was 0.54 and the RMSE. 29.02 ms. The results were not good enough to be applied to the real-time text-to-speech systems. Further investigation of feature interactions is required for the better performance of the Sums-of-Products models.

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Development of GIS Interconnected Corrosion Prediction System for Underground Metallic Structures (기존 GIS에 연계한 지하금속매설물의 부식예측시스템 개발)

  • Ha, Tae-Hyun;Kim, Dae-Kyeong;Bae, Jeong-Hyo;Lee, Hyun-Goo;Choi, Sang-Bong;Jeong, Seong-Hwan
    • Proceedings of the KIEE Conference
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    • 1999.11c
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    • pp.769-771
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    • 1999
  • In general, the most of GIS is only deal with the material and geometric data which are position, radius, length etc except a corrosion data. In present, the owner of metallic structures having an interest in that my structures do corrode or not and how many life time is there? So, we need the development of GIS interconnected corrosion prediction system on the view point of the efficiency of operation and the protection for big accident. The results of development of its system are described in this paper. It can do life prediction and interference analysis and also newest corrosion data should be updated regularly.

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A Study on the Propagation Prediction Model for the Microcell Mobile Communication (마이크로셀 이동통신의 전파예측 모델에 관한 연구)

  • 노순국;최동우;박창균
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.8
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    • pp.100-107
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    • 1999
  • When a subscriber service composed along the central street of urban in microcell and picocell mobile communication of cellular method, we proposed the propagation prediction model that mobile communication environment of urban can analyze exactly and faster men than a precedent. We simulate the proposed propagation prediction model under the urban propagation environment of PCS mobile communication and analyze distribution of received field strength in cell. As a results, we show the optimal condition of the transmitting power and the position of the base station in the microcell and the picocell mobile communication.

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Design of Path Prediction Smart Street Lighting System on the Internet of Things

  • Kim, Tae Yeun;Park, Nam Hong
    • Journal of Integrative Natural Science
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    • v.12 no.1
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    • pp.14-19
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    • 2019
  • In this paper, we propose a system for controlling the brightness of street lights by predicting pedestrian paths, identifying the position of pedestrians with motion sensing sensors and obtaining motion vectors based on past walking directions, then predicting pedestrian paths through the route prediction smart street lighting system. In addition, by using motion vector data, the pre-treatment process using linear interpolation method and the fuzzy system and neural network system were designed in parallel structure to increase efficiency and the rough set was used to correct errors. It is expected that the system proposed in this paper will be effective in securing the safety of pedestrians and reducing light pollution and energy by predicting the path of pedestrians in the detection of movement of pedestrians and in conjunction with smart street lightings.