• Title/Summary/Keyword: Improvement of prediction performance

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Data Preprocessing Technique and Service Operation Architecture for Demand Forecasting of Electric Vehicle Charging Station (전기자동차 충전소 수요 예측 데이터 전처리 기법 및 서비스 운영 아키텍처)

  • Joongi Hong;Suntae Kim;Jeongah Kim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.23 no.2
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    • pp.131-138
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    • 2023
  • Globally, the eco-friendly industry is developing due to the climate crisis. Electric vehicles are an eco-friendly industry that is attracting attention as it is expected to reduce carbon emissions by 30~70% or more compared to internal combustion engine vehicles. As electric vehicles become more popular, charging stations have become an important factor for purchasing electric vehicles. Recent research is using artificial intelligence to identify local demand for charging stations and select locations that can maximize economic impact. In this study, in order to contribute to the improvement of the performance of the electric vehicle charging station demand prediction model, nationwide data that can be used in the artificial intelligence model was defined and a pre-processing technique was proposed. In addition, a preprocessor, artificial intelligence model, and service web were implemented for real charging station demand prediction, and the value of data as a location selection factor was verified.

Macroblock-based Adaptive Interpolation Filter Method Using New Filter Selection Criterion in H.264/AVC (H.264/AVC에서 새로운 필터 선택 기준을 이용한 매크로 블록 기반 적응 보간 필터 방법)

  • Yoon, Kun-Su;Moon, Yong-Ho;Kim, Jae-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.4C
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    • pp.312-320
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    • 2008
  • The macroblock-based adaptive interpolation filter method has been considered to be able to achieve high coding efficiency in H.264/AVC. In this method, although the filter selection criterion considered in terms of rate and distortion have showed a good performance, it still leaves room for improvement. To improve high coding efficiency better than conventional method, we propose a new filter selection criterion which considers two bit rates, motion vector and prediction error, and reconstruction error. In addition, the algorithm for reducing the overhead of transmitting the selected filter information is presented. Experimental results show that the proposed method significantly improves the coding efficiency compared to ones using conventional criterion. It leads to about a 5.19% (1 reference frame) and 5.14% (5 reference frames) bit rate savings on average compared to H.264/AVC, respectively.

A Performance Improvement of Cognitive User by Using Bandwidth Reallocation in Cognitive Radio Systems (인지 라디오 시스템에서 대역폭 재할당을 이용한 인지 사용자의 성능향상)

  • Lee, Jin-Yi
    • Journal of Advanced Navigation Technology
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    • v.18 no.5
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    • pp.415-420
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    • 2014
  • Another crucial issue is a providing secondary user(SU) with the its guaranteed quality of service(QoS) in cognitive radio systems, from the SU view to be allowed to opportunistically utilize the primary user(PU) spectrum on non-interfering. In this paper, we propose a bandwidth reallocation scheme for reducing SU dropping rate through renegotiation of requested channel numbers when available bandwidth is not enough for accepting the spectrum handoff SUs. We categorize SU calls into two types : the first priority and the second priority SU, and the first SU' service is supported by bandwidth reservation based on ARMA prediction model for PU arrivals, while the second SU's bandwidth demands for spectrum handoff is to be reallocated through their renegotiation. Simulation results show that our scheme can improve SU dropping rate and system resource utilization efficiency by bandwidth reallocation.

Comparative assessment of frost event prediction models using logistic regression, random forest, and LSTM networks (로지스틱 회귀, 랜덤포레스트, LSTM 기법을 활용한 서리예측모형 평가)

  • Chun, Jong Ahn;Lee, Hyun-Ju;Im, Seul-Hee;Kim, Daeha;Baek, Sang-Soo
    • Journal of Korea Water Resources Association
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    • v.54 no.9
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    • pp.667-680
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    • 2021
  • We investigated changes in frost days and frost-free periods and to comparatively assess frost event prediction models developed using logistic regression (LR), random forest (RF), and long short-term memory (LSTM) networks. The meteorological variables for the model development were collected from the Suwon, Cheongju, and Gwangju stations for the period of 1973-2019 for spring (March - May) and fall (September - November). The developed models were then evaluated by Precision, Recall, and f-1 score and graphical evaluation methods such as AUC and reliability diagram. The results showed that significant decreases (significance level of 0.01) in the frequencies of frost days were at the three stations in both spring and fall. Overall, the evaluation metrics showed that the performance of RF was highest, while that of LSTM was lowest. Despite higher AUC values (above 0.9) were found at the three stations, reliability diagrams showed inconsistent reliability. A further study is suggested on the improvement of the predictability of both frost events and the first and last frost days by the frost event prediction models and reliability of the models. It would be beneficial to replicate this study at more stations in other regions.

Performance improvement of artificial neural network based water quality prediction model using explainable artificial intelligence technology (설명가능한 인공지능 기술을 이용한 인공신경망 기반 수질예측 모델의 성능향상)

  • Lee, Won Jin;Lee, Eui Hoon
    • Journal of Korea Water Resources Association
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    • v.56 no.11
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    • pp.801-813
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    • 2023
  • Recently, as studies about Artificial Neural Network (ANN) are actively progressing, studies for predicting water quality of rivers using ANN are being conducted. However, it is difficult to analyze the operation process inside ANN, because ANN is form of Black-box. Although eXplainable Artificial Intelligence (XAI) is used to analyze the computational process of ANN, research using XAI technology in the field of water resources is insufficient. This study analyzed Multi Layer Perceptron (MLP) to predict Water Temperature (WT), Dissolved Oxygen (DO), hydrogen ion concentration (pH) and Chlorophyll-a (Chl-a) at the Dasan water quality observatory in the Nakdong river using Layer-wise Relevance Propagation (LRP) among XAI technologies. The MLP that learned water quality was analyzed using LRP to select the optimal input data to predict water quality, and the prediction results of the MLP learned using the optimal input data were analyzed. As a result of selecting the optimal input data using LRP, the prediction accuracy of MLP, which learned the input data except daily precipitation in the surrounding area, was the highest. Looking at the analysis of MLP's DO prediction results, it was analyzed that the pH and DO a had large influence at the highest point, and the effect of WT was large at the lowest point.

Wavelet Video Coding Using Low-Band-Shift Method and Multiresolution Motion Estimation (저대역 이동법과 다해상도 움직임 추정을 이용한 웨이블릿 동영상 부호화)

  • 박영덕;서석용;고형화
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.3
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    • pp.17-24
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    • 2004
  • In this paper, the wavelet video coding using Low-Band-Shift(LBS) method and multiresolution motion estimation(MRME) is proposed. To overcome shift- variant property on wavelet coefficients, the LBS was proposed. LBS method previously has superior performance in terms of rate-distortion characteristic. However, this method needs more memory and computational complexity. Therefore to reduce computational complexity of video coding using LBS, we combine MRME with LBS. When mm is applied only, it has 7 times as much as existing method's motion vector because each subband has different motion vector using property of LBS, number of motion vector decreases. Proposed method decreases motion vector, and it decreases motion compensated Prediction error by detailed motion estimation. And then it shows better coding performance. Also this method reduces computational amount by smaller search area in higher resolution. The computational complexity of the proposed method is 12.1% of that of existing method at 3-level wavelet transform. The experimental results with the proposed method show about 0.2∼9.7% improvement of MAD performance in case of lossless coding, and 0.1∼2.0㏈ improvement of PSNR performance at 4he same bit rate in case of lossy coding.

Analysis of the Likelihood of Successful Defibrillation as a Change of Cardiopulmonary Resuscitation Transition using Support Vector Machine (서포트 벡터 머신을 이용한 심폐소생술 변이의 변화에 따른 제세동 성공률 분석)

  • Jang, Seung-Jin;Hwang, Sung-Oh;Lee, Hyun-Sook;Yoon, Young-Ro
    • Journal of Biomedical Engineering Research
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    • v.28 no.4
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    • pp.556-568
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    • 2007
  • Unsatisfied results of return of spontaneous circulation (ROSC) estimates were caused by the fact that the predictability of the predictors was insufficient. This unmet estimate of the predictors may be affected by transitional events due to behaviors which occur during cardiopulmonary resuscitation (CPR). We thus hypothesized that the discrepancy of ROSC estimates found in statistical characteristics due to transitional CPR events, may affect the performance of the predictors, and that the performance of the classifier dichotomizing between ROSC and No-ROSC might be different during CPR. In a canine model (n=18) of prolonged ventricular fibrillation (VF), standard CPR was provided with administration of two doses of epinephrine 0 min or 3 min later of the onset of CPR. For the analysis of the likelihood of a successful defibrillation during CPR, Support Vector Classification was adopted to evaluate statistical peculiarity combining time and frequency based predictors: median frequency, frequency band-limited power spectrum, mean segment amplitude, and zero crossing rates. The worst predictable period showed below about 1 min after the onset of CPR, and the best predictable period could be observed from about 1.5 min later of the administering epinephrine through 2.0-2.2 min. As hypothesized, the discrepancy of statistical characteristics of the predictors was reflected in the differences of the classification performance during CPR. These results represent a major improvement in defibrillation prediction can be achieved by a specific timing of the analysis, as a change in CPR transition.

Evaluation of Nonlinear Seismic Performance Using Equivalent Responses of Multistory Building Structures (대표응답을 이용한 건축구조물의 비선형 지진응답 분석 및 내진성능평가)

  • 이동근;최원호
    • Journal of the Earthquake Engineering Society of Korea
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    • v.5 no.6
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    • pp.65-76
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    • 2001
  • Determination of ductility demand and prediction of nonlinear seismic responses of a structure under the earthquake ground motions have become a very important subject for evaluation of seismic performance in the performance based seismic design. In this study, the system ductility demand and nonlinear seismic responses of the steel moment framed structures by the nonlinear time history analysis are estimated and compared with those obtained from the capacity spectrum method suggested in ATC-40 and proposed method that is an improvement on the capacity spectrum method using the equivalent responses derived directly from a multi degree of freedom system. the adequacy and validity of the proposed method is verified by comparing the results evaluated by the method proposed in this study and the results obtained from method suggested in ATC-40 to the nonlinear seismic responses of the example structures from the nonlinear time history analysis.

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A study on the improvement of the heat pipe performance with non metallic circumferential wick (非金屬 環狀윅을 갖는 히이트파이프 性能개선에 관한 연구)

  • 서정일;장영석
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.10 no.5
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    • pp.713-723
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    • 1986
  • The purpose of this research was to study the heat transfer characteristics of heat pipe which used non-metallic(SiO$_{2}$), circumferential wick and meshed slab wick as ADI method and experimental results. Compared wick experimental data and results by ADI method showed the good agreement and ADI method was utilized in pridicting the performance of heat pipe. Also, ADI method was applied to predict heat pipe performance according to the various volume ratios of metallic bond. The heat transfer characteristics of heat pipe could be predicted by heat flux and superheat term below the maximum heat flux limit. According to the addition ratio of metallic bond, heat transfer ratio could be improved as 2-3 times and when heat conductivity ratio(K$_{b}$/K$_{a}$) was increased at 4-12 ratio, heat transfer was in creased as 1.7-2.4 times, and the prediction of heat transfer could be show as exponential type. In producting non-metallic wick used to low heat pipe, metallic bond which is the conductivity of good quality and enduring for high temperature will be improved as in important problem.

A Design of Multimedia Application SoC based with Processor using BTB (BTB를 이용한 프로세서 기반 멀티미디어 응용 SoC 설계)

  • Jung, Younjin;Lee, Byungyup;Ryoo, Kwangki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.397-400
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    • 2009
  • This paper describes ASIC design of Multimedia application SoC platform based RISC processor with BTB(Branch Target Buffer). For performance enhancement of platform, we use a simple branch prediction scheme, BTB structure, that stores a target address for branch instruction to remove pipeline harzard. Also, the platform includes a number of peripheral such as VGA controller, AC97 controller, UART controller, SRAM interface and Debug interface. The platform is designed and verified on a Xilinx VERTEX-4 FPGA using a number of test programs for functional tests and timing constraints. Finally, the platform is implemented into a single ASIC chip which can be operated at 100MHz clock frequency using the Chartered 0.18um process. As a result of performance estimation, the proposed platform shows about 5~9% performance improvement in comparison with the previous SoC Platform.

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