• 제목/요약/키워드: Global Error

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수도권 도시 환경 요인에 따른 범죄 발생 건수 예측 (Prediction of the Number of Crimes according to Urban Environmental Factors in the Metropolitan Area)

  • 장예원;김예림;박시현;이재영;문유진
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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    • pp.321-322
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    • 2023
  • 본 논문에서는 Scikit-learn 패키지의 LinearRegression 모델과 Keras 딥러닝 모델을 활용하여 수도권 도시 환경 요인에 따른 범죄 발생 건수를 예측 모델을 제안한다. 연구 방법으로 범죄 발생과 유의미한 관계가 있다고 파악되는 수도권의 각 자치구 별 데이터셋을 분석하여, CCTV, 파출소, 가로등의 수가 범죄 발생에 유의미한 영향을 끼치는 것을 확인하였다. 독립 변수들 간에 Scale을 줄이고자 정규화를 진행했고, 종속변수의 정규성 확보를 위해 로그변환을 취했다. 손실 함수는 회귀문제에서 사용되는 'relu'함수를 사용했고 모델의 성능을 확인할 수 있는 지표로 MSE(Mean Squared Error)를 사용해 모델을 구성하였다. 본 논문에서 설계한 이 프로그램은 범죄 발생율이 높은 지역구에 경찰 인력의 추가적 배치, 안전 시설 확충 등 실무적 조치를 취함에 있어 근거를 제공할 수 있을 것으로 사료된다.

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SPATIAL AND TEMPORAL INFLUENCES ON SOIL MOISTURE ESTIMATION

  • Kim, Gwang-seob
    • Water Engineering Research
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    • 제3권1호
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    • pp.31-44
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    • 2002
  • The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

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Development of Precise Point Positioning Method Using Global Positioning System Measurements

  • Choi, Byung-Kyu;Back, Jeong-Ho;Cho, Sung-Ki;Park, Jong-Uk;Park, Pil-Ho
    • Journal of Astronomy and Space Sciences
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    • 제28권3호
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    • pp.217-223
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    • 2011
  • Precise point positioning (PPP) is increasingly used in several parts such as monitoring of crustal movement and maintaining an international terrestrial reference frame using global positioning system (GPS) measurements. An accuracy of PPP data processing has been increased due to the use of the more precise satellite orbit/clock products. In this study we developed PPP algorithm that utilizes data collected by a GPS receiver. The measurement error modelling including the tropospheric error and the tidal model in data processing was considered to improve the positioning accuracy. The extended Kalman filter has been also employed to estimate the state parameters such as positioning information and float ambiguities. For the verification, we compared our results to other of International GNSS Service analysis center. As a result, the mean errors of the estimated position on the East-West, North-South and Up-Down direction for the five days were 0.9 cm, 0.32 cm, and 1.14 cm in 95% confidence level.

Analysis of Radiosonde Daily Bias by Comparing Precipitable Water Vapor Obtained from Global Positioning System and Radiosonde

  • Park, Chang-Geun;Cho, Jung-Ho
    • Journal of Astronomy and Space Sciences
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    • 제27권4호
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    • pp.367-375
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    • 2010
  • In this study, we compared the precipitable water vapor (PWV) data derived from the radiosonde observation data at Sokcho Observatory and the PWV data at Sokcho Global Positioning System (GPS) Observatory provided by Korea Astronomy and Space Science Institute, from 0000 UTC, June 1, 2007 to 1200 UTC, May 31, 2009, and analyzed the radiosonde bias between the day and the night. In the scatter diagram of the daytime and nighttime radiosonde PWV data and the GPS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study. In addition, for all the rainfall events, the tendency that the wet bias of the radiosonde PWV increased as the GPS PWV decreased and the dry bias of the radiosonde PWV increased as the GPS PWV increased was significantly less distinctive in nighttime than in daytime. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the second year, regardless of nighttime or daytime rainfall, and the non-rainfall root mean square error (RMSE) was similar to that of the previous studies, while the rainfall RMSE was larger to a certain extent.

운량 및 일조시간을 이용한 우리나라의 시간당 전일사량의 평가 (Global Hourly Solar Irradiation Estimation using Cloud Cover and Sunshine Duration in South Korea)

  • 이관호
    • KIEAE Journal
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    • 제11권1호
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    • pp.15-20
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    • 2011
  • Computer simulation of buildings and solar energy systems is being used increasingly in energy assessments and design. For the six locations (Seoul, Incheon, Daejeon, Deagu, Gwangju and Busan) in South Korea where the global hourly solar irradiation (GHSI) is currently measured, GHSI was calculated using a comparatively simple cloud cover radiation model (CRM) and sunshine fraction radiation model (SFRM). The result was that the measured and calculated values of GHSI were similar for the six regions. Results of cloud cover and sunshine fraction models have been compared with the measured data using the coefficient of determination (R2), root-mean-square error (RMSE) and mean bias error (MBE). The strength of correlation R2 varied within similar ranges: 0.886-0.914 for CRM and 0.908-0.934 for SFRM. Average MBE for the CRM and SFRM were 6.67 and 14.02 W/m2, respectively, and average RMSE 104.36 and 92.15 W/m2. This showed that SFRM was slightly accurate and used many regions as compared to CRM for prediction of GHSI.

일조시간 및 운량을 이용한 태양고도에 따른 수평면 전일사 산출 (Generation of Horizontal Global Irradiance using the Cloud Cover and Sunshine Duration According to the Solar Altitude)

  • 이관호;재프 리버모어
    • 한국태양에너지학회 논문집
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    • 제40권2호
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    • pp.37-48
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    • 2020
  • This study compares cloud radiation model (CRM) and sunshine fraction radiation model (SFRM) according to the solar altitude using hourly sunshine duration (SD) and cloud cover (CC) data. Solar irradiance measurements are not easy for the expensive measuring equipment and precise measuring technology. The two models with the site fitting and South Korea coefficients have been analyzed for fourteen cities of South Korea during the period (1986-2015) and evaluated using the root mean square error (RMSE) and the mean bias error (MBE). From the comparison of the results, it is found that the SFRM with the site fitting coefficients could be the best method for fourteen locations. It may be concluded that the SFRM models of South Korea coefficients generated in this study may be used reasonably well for calculating the hourly horizontal global irradiance (HGI) at any other location of South Korea.

An Exploration of Dynamic Relationships between Macroeconomic Variables and Stock Prices in Korea Revisited

  • LEE, Jung Wan;BRAHMASRENE, Tantatape
    • The Journal of Asian Finance, Economics and Business
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    • 제7권10호
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    • pp.23-34
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    • 2020
  • The paper revisits the author's previous paper to examine short-run and long-run dynamic relationships between macroeconomic variables and stock prices in Korea. The data is updated to the period for which monthly data are available from January 1986 to June 2018 (390 observations) retrieved from the Bank of Korea. The results of Johansen cointegration test indicate that at least one cointegrating equation exists, confirming there is a long-run equilibrium relationship between macroeconomic variables and stock prices in Korea. The results of vector error correction estimates confirm that: 1) the coefficient of the error correction term is significant with a negative sign, which is, a long-run dynamic relationship is observed between macroeconomic variables and stock prices; 2) for short-run dynamics, the nominal exchange rate of the Korean won per the US dollar is positively related to stock prices, while interest rates are negatively related to stock prices in the short-run; 3) the coefficient of global financial crises is insignificant, that is, the changes of stock prices are determined largely by their own dynamics in the model. The results suggest only that the global financial crises neither cause instability in the cointegrating vector, nor affect significant changes in the endogenous variables in the model.

Inter-Process Correlation Model based Hybrid Framework for Fault Diagnosis in Wireless Sensor Networks

  • Zafar, Amna;Akbar, Ali Hammad;Akram, Beenish Ayesha
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권2호
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    • pp.536-564
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    • 2019
  • Soft faults are inherent in wireless sensor networks (WSNs) due to external and internal errors. The failure of processes in a protocol stack are caused by errors on various layers. In this work, impact of errors and channel misbehavior on process execution is investigated to provide an error classification mechanism. Considering implementation of WSN protocol stack, inter-process correlations of stacked and peer layer processes are modeled. The proposed model is realized through local and global decision trees for fault diagnosis. A hybrid framework is proposed to implement local decision tree on sensor nodes and global decision tree on diagnostic cluster head. Local decision tree is employed to diagnose critical failures due to errors in stacked processes at node level. Global decision tree, diagnoses critical failures due to errors in peer layer processes at network level. The proposed model has been analyzed using fault tree analysis. The framework implementation has been done in Castalia. Simulation results validate the inter-process correlation model-based fault diagnosis. The hybrid framework distributes processing load on sensor nodes and diagnostic cluster head in a decentralized way, reducing communication overhead.

MAXIMUM TOLERABLE ERROR BOUND IN DISTRIBUTED SIMULATED ANNEALING

  • Hong, Chul-Eui;McMillin, Bruce M.;Ahn, Hee-Il
    • ETRI Journal
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    • 제15권3_4호
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    • pp.1-26
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    • 1994
  • Simulated annealing is an attractive, but expensive, heuristic method for approximating the solution to combinatorial optimization problems. Attempts to parallel simulated annealing, particularly on distributed memory multicomputers, are hampered by the algorithm's requirement of a globally consistent system state. In a multicomputer, maintaining the global state S involves explicit message traffic and is a critical performance bottleneck. To mitigate this bottleneck, it becomes necessary to amortize the overhead of these state updates over as many parallel state changes as possible. By using this technique, errors in the actual cost C(S) of a particular state S will be introduced into the annealing process. This paper places analytically derived bounds on this error in order to assure convergence to the correct optimal result. The resulting parallel simulated annealing algorithm dynamically changes the frequency of global updates as a function of the annealing control parameter, i.e. temperature. Implementation results on an Intel iPSC/2 are reported.

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An Extended Scalar Adaptive Filter for Mitigating Sudden Abnormal Signals of Guided Missile

  • Lim, Jun-Kyu;Park, Chan-Gook
    • International Journal of Aeronautical and Space Sciences
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    • 제12권1호
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    • pp.37-42
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    • 2011
  • An extended scalar adaptive filter for guided missiles using a global positioning system receiver is presented. A conventional scalar adaptive filter is adequate filter for eliminating sudden abnormal jumping measurements. However, if missile or vehicle velocities have variation, the conventional filter cannot eliminate abnormal measurements. The proposed filter utilizes an acceleration term, which is an improvement not used in previous conventional scalar adaptive filters. The proposed filter continuously estimates noise measurement variance, velocity error variance and acceleration error variance. For estimating the three variances, an innovation method was used in combination with the least square method for the three variances. Results from the simulations indicated that the proposed filter exhibited better position accuracy than the conventional scalar adaptive filter.