• Title/Summary/Keyword: vector AR model

Search Result 35, Processing Time 0.023 seconds

Assessment of Turbulent Spectral Estimators in LDV (LDV의 난류 스펙트럼 추정치 평가)

  • 이도환;성형진
    • Transactions of the Korean Society of Mechanical Engineers
    • /
    • v.16 no.9
    • /
    • pp.1788-1795
    • /
    • 1992
  • Numerical simulations have been performed to investigate various spectral estimators used in LDV signal processing. In order to simulate a particle arrival time statistics known as the doubly stochastic poisson process, an autoregressive vector model was adopted to construct a primary velocity field. The conditional Poisson process with a random rate parameter was generated through the rescaling time process using the mean value function. The direct transform based on random sampling sequences and the standard periodogram using periodically resampled data by the sample and hold interpolation were applied to obtain power spectral density functions. For low turbulent intensity flows, the direct transform with a constant Poisson intensity is in good agreement with the theoretical spectrum. The periodogram using the sample and hold sequences is better than the direct transform in the view of the stability and the weighting of the velocity bias for high data density flows. The high Reynolds stress and high fluctuation of the transverse velocity component affects the velocity bias which increases the distortion of spectral components in the direct transform.

Forecasting Korean CPI Inflation (우리나라 소비자물가상승률 예측)

  • Kang, Kyu Ho;Kim, Jungsung;Shin, Serim
    • Economic Analysis
    • /
    • v.27 no.4
    • /
    • pp.1-42
    • /
    • 2021
  • The outlook for Korea's consumer price inflation rate has a profound impact not only on the Bank of Korea's operation of the inflation target system but also on the overall economy, including the bond market and private consumption and investment. This study presents the prediction results of consumer price inflation in Korea for the next three years. To this end, first, model selection is performed based on the out-of-sample predictive power of autoregressive distributed lag (ADL) models, AR models, small-scale vector autoregressive (VAR) models, and large-scale VAR models. Since there are many potential predictors of inflation, a Bayesian variable selection technique was introduced for 12 macro variables, and a precise tuning process was performed to improve predictive power. In the case of the VAR model, the Minnesota prior distribution was applied to solve the dimensional curse problem. Looking at the results of long-term and short-term out-of-sample predictions for the last five years, the ADL model was generally superior to other competing models in both point and distribution prediction. As a result of forecasting through the combination of predictions from the above models, the inflation rate is expected to maintain the current level of around 2% until the second half of 2022, and is expected to drop to around 1% from the first half of 2023.

Enhanced Variable Structure Control With Fuzzy Logic System

  • Charnprecharut, Veeraphon;Phaitoonwattanakij, Kitti;Tiacharoen, Somporn
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 2005.06a
    • /
    • pp.999-1004
    • /
    • 2005
  • An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

  • PDF

A SCATTERING MECHANISM IN OYSTER FARM BY POLARIMETRIC AND JERS-l DATA

  • Lee Seung-Kuk;Won Joong Sun
    • Proceedings of the KSRS Conference
    • /
    • 2005.10a
    • /
    • pp.538-541
    • /
    • 2005
  • Tidal flats develop along the south coast ofthe Korean peninsula. These areas are famous for sea farming. Specially, strong and coherent radar backscattering signals are observed over oyster sea farms that consist of artificial structures. Tide height in oyster farm is possible to measure by using interferometric phase and intensity of SAR data. It is assumed that the radar signals from oyster farm could be considered as double-bouncing returns by vertical and horizontal bars. But, detailed backscattering mechanism and polarimetric characteristics in oyster farm had not been well studied. We could not demonstrate whether the assumption is correct or not and exactly understand what the properties of back scattering were in oyster farm without full polarimetric data. The results of AIRSAR L-band POLSAR data, experiments in laboratory and JERS-l images are discussed. We carried out an experiment simulating a target structure using vector network analyser (Y.N.A.) in an anechoic chamber at Niigata University. Radar returns from vertical poles are stronger than those from horizontal poles by 10.5 dB. Single bounce components were as strong as double bounce components and more sensitive to antenna look direction. Double bounce components show quasi-linear relation with height of vertical poles. As black absorber replaced AI-plate in bottom surface, double bounce in vertical pole decreased. It is observed that not all oyster farms are characterized by double bounced scattering in AIRSAR data. The image intensity of the double bounce dominant oyster farm was investigated with respect to that of oyster farm dominated by single bounce in JERS-l SAR data. The image intensity model results in a correlation coefficient (R2 ) of 0.78 in double bounce dominant area while that of 0.54 in single bouncing dominant area. This shows that double bounce dominant area should be selected for water height measurement using In8AR technique.

  • PDF

Heterologous Gene Expression System Using the Cold-Inducible CnAFP Promoter in Chlamydomonas reinhardtii

  • Kim, Minjae;Kim, Jongrae;Kim, Sanghee;Jin, EonSeon
    • Journal of Microbiology and Biotechnology
    • /
    • v.30 no.11
    • /
    • pp.1777-1784
    • /
    • 2020
  • To increase the availability of microalgae as producers of valuable compounds, it is necessary to develop novel systems for gene expression regulation. Among the diverse expression systems available in microalgae, none are designed to induce expression by low temperature. In this study, we explored a cold-inducible system using the antifreeze protein (AFP) promoter from a polar diatom, Chaetoceros neogracile. A vector containing the CnAFP promoter (pCnAFP) was generated to regulate nuclear gene expression, and reporter genes (Gaussia luciferase (GLuc) and mVenus fluorescent protein (mVenus)) were successfully expressed in the model microalga, Chlamydomonas reinhardtii. In particular, under the control of pCnAFP, the expression of these genes was increased at low temperature, unlike pAR1, a promoter that is widely used for gene expression in C. reinhardtii. Promoter truncation assays showed that cold inducibility was still present even when pCnAFP was shortened to 600 bp, indicating the presence of a low-temperature response element between -600 and -477 bp. Our results show the availability of new heterologous gene expression systems with cold-inducible promoters and the possibility to find novel low-temperature response factors in microalgae. Through further improvement, this cold-inducible promoter could be used to develop more efficient expression tools.