• Title/Summary/Keyword: model-based method

Search Result 19,606, Processing Time 0.05 seconds

SOC Estimation Based on OCV for NiMH Batteries Using an Improved Takacs Model

  • Windarko, Novie Ayub;Choi, Jae-Ho
    • Journal of Power Electronics
    • /
    • v.10 no.2
    • /
    • pp.181-186
    • /
    • 2010
  • This paper presents a new method for the estimation of State of Charge (SOC) for NiMH batteries. Among the conventional methods to estimate SOC, Coulomb Counting is widely used, but this method is not precise due to error integration. Another method that has been proposed to estimate SOC is by using a measurement of the Open Circuit Voltage (OCV). This method is found to be a precise one for SOC estimation. In NiMH batteries, the hysteresis characteristic of OCV is very strong compared to other type of batteries. Another characteristic of NiMH battery to be considered is that the OCV of a NiMH battery under discharging mode is lower than it is under charging mode. In this paper, the OCV is modeled by a simple method based on a hyperbolic function which well known as Takacs’s model. The OCV model is then used for SOC estimation. Although the model is simple, the error is within 10%.

TSK Fuzzy Model Based Hybrid Adaptive Control of Nonlinear Systems (비선형 시스템의 TSK 퍼지모델 기반 하이브리드 적응제어)

  • Kim, You-Keun;Kim, Jae-Hun;Hyun, Chang-Ho;Kim, Eun-Tai;Park, Mi-Gnon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
    • /
    • 2004.10a
    • /
    • pp.211-216
    • /
    • 2004
  • In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

  • PDF

The Development of the Composite Index as a method of rate adjustment (의료보험수가 조정을 위한 복합지표 개발에 관한 연구)

  • 김한중;조우현;이해종
    • Health Policy and Management
    • /
    • v.3 no.1
    • /
    • pp.84-101
    • /
    • 1993
  • The current method of rate adjustment is based on the evaluation of the financial performance of hospitals. The method has the disadvantages such as too complicated, expensive process as well as low reliability due to small sample size. This study, therefore, develops a new model for the rate adjustment with the use of the composite index. In addition to that, it examines the validity of the model by comparing the result of the new method with that of the conventional method. The idea of the new model comes from the Medicare Economic Index(MEI) on which physician fees for the Medicare patients are adjusted periodically in the United States. Medical costs are classified into three groups : labor costs, materials and other expenses. Labor costs are subdivided into physicians and other personnels. Materials are subdivided into drugs and others. Other expenses are subdivided into 5 items. Macro economic indices are selected for each cost item in order to reflect the cost inflation during the specific period. Then the composite index which integrate all items according to the ration of each item in the total costs is calculated. The result from the application of empirical data to the new model is very similar to that of the current method. Furthermore, this method is very simple and also to easy to get social concensus. This model can be replaced the current method based on the analysis of the financial performance for the adjustment of medical fees.

  • PDF

Updating Algorithms of Finite Element Model Using Singular Value Decomposition and Eigenanalysis (특이값 분해와 고유치해석을 이용한 유한요소모델의 개선)

  • 김홍준;박영필
    • Journal of KSNVE
    • /
    • v.9 no.1
    • /
    • pp.163-173
    • /
    • 1999
  • Precise and reasonable modelling is necessary and indispensable to the analysis of dynamic characteristics of mechanical structures. Also. the effective prediction of the change of modal properties due to the variation of design parameters is required especially for the application of finite element method to the structural dynamics problems. To meet those necessity and requirement, three model updating algorithms are proposed for finite element methods. Those algorithms are based on sensitivity analysis of the modal data obtained from experimental modal analysis(EMA) and analytical modal analysis(AMA). The adapted sensitivity analysis methods of the algorithms are 1)eigensensitivity(EGNS) method. 2)frequency response function sensitivity(FRFS) method. 3)sensitivity based element-by-element method (SBEEM), Singular value decomposition(SVD) is used for performing eigenanalysis and parameter estimation in the updating process. Those algorithms are applied to finite element of a plate and the updating capability of each algorithm is compared in terms of accuracy. reliability and stability of the updating process. It is shown that the model updating method using frequency response function is superior to the other methods in view of various updating capabilities.

  • PDF

A Study on the Improvement of Performance of Concept-Based Information Retrieval Model Using a Distributed Subject Knowledge Base (주제별 분산 지식베이스에 의한 개념기반 정보검색시스템의 성능향상에 관한 연구)

  • 노영희
    • Journal of the Korean Society for information Management
    • /
    • v.19 no.1
    • /
    • pp.47-69
    • /
    • 2002
  • The concept based retrieval model has shown a higher performance than those of the simple matching function method or the P-norm retrieval method introduced to compensate the demerits of the Boolean retrieval model. However. it takes too long to create a semantic-net knowledge base, which is essential in concept exploration. In order to solve such demerits. a method was sought out by creating a distributed knowledge base by subjects to reduce construction time without hindering the performance of retrieval.

Machine Printed and Handwritten Text Discrimination in Korean Document Images

  • Trieu, Son Tung;Lee, Guee Sang
    • Smart Media Journal
    • /
    • v.5 no.3
    • /
    • pp.30-34
    • /
    • 2016
  • Nowadays, there are a lot of Korean documents, which often need to be identified in one of printed or handwritten text. Early methods for the identification use structural features, which can be simple and easy to apply to text of a specific font, but its performance depends on the font type and characteristics of the text. Recently, the bag-of-words model has been used for the identification, which can be invariant to changes in font size, distortions or modifications to the text. The method based on bag-of-words model includes three steps: word segmentation using connected component grouping, feature extraction, and finally classification using SVM(Support Vector Machine). In this paper, bag-of-words model based method is proposed using SURF(Speeded Up Robust Feature) for the identification of machine printed and handwritten text in Korean documents. The experiment shows that the proposed method outperforms methods based on structural features.

Performance Evaluation of a Feature-Importance-based Feature Selection Method for Time Series Prediction

  • Hyun, Ahn
    • Journal of information and communication convergence engineering
    • /
    • v.21 no.1
    • /
    • pp.82-89
    • /
    • 2023
  • Various machine-learning models may yield high predictive power for massive time series for time series prediction. However, these models are prone to instability in terms of computational cost because of the high dimensionality of the feature space and nonoptimized hyperparameter settings. Considering the potential risk that model training with a high-dimensional feature set can be time-consuming, we evaluate a feature-importance-based feature selection method to derive a tradeoff between predictive power and computational cost for time series prediction. We used two machine learning techniques for performance evaluation to generate prediction models from a retail sales dataset. First, we ranked the features using impurity- and Local Interpretable Model-agnostic Explanations (LIME) -based feature importance measures in the prediction models. Then, the recursive feature elimination method was applied to eliminate unimportant features sequentially. Consequently, we obtained a subset of features that could lead to reduced model training time while preserving acceptable model performance.

Positioning of Wireless Base Station using Location-Based RSRP Measurement

  • Cho, Seong Yun;Kang, Chang Ho
    • Journal of Positioning, Navigation, and Timing
    • /
    • v.8 no.4
    • /
    • pp.183-192
    • /
    • 2019
  • In fingerprint-based wireless positioning, it is necessary to establish a DB of the unmeasured area. To this end, a method of estimating the position of a base station based on a signal propagation model, and a method of estimating the information of the received signal in the unmeasured area based on the estimated position of the base station have been investigating. The purpose of this paper is to estimate the position of the base station using the measured information and to analyze the performance of the positioning. Vehicles equipped with a GPS receiver and signal measuring equipment travel the service area and acquire location-based Reference Signal Received Power (RSRP) measurements. We propose a method of estimating the position of the base station using the measured information. And the performance of the proposed method is analyzed on a simulation basis. The simulation results confirm that the accuracy of the positioning is affected by the measured area and the Dilution of Precision (DOP), the accuracy of the position information obtained by the GPS receiver, and the errors of the signal included in the RSRP. Based on the results of this paper, we can expect that the position of the base station can be estimated and the DB of the unmeasured area can be constructed based on the estimated position of the base stations and the signal propagation model.

Creep strain modeling for alloy 690 SG tube material based on modified theta projection method

  • Moon, Seongin;Kim, Jong-Min;Kwon, Joon-Yeop;Lee, Bong-Sang;Choi, Kwon-Jae;Kim, Min-Chul
    • Nuclear Engineering and Technology
    • /
    • v.54 no.5
    • /
    • pp.1570-1578
    • /
    • 2022
  • During a severe accident, steam generator (SG) tubes undergo rapid changes in the pressure and temperature. Therefore, an appropriate creep model to predict a short term creep damage is essential. In this paper, a novel creep model for Alloy 690 SG tube material was proposed. It is based on the theta (θ) projection method that can represent all three stages of the creep process. The original θ projection method poses a limitation owing to its inability to represent experimental creep curves for SG tube materials for a large strain rate in the tertiary creep region. Therefore, a new modified θ projection method is proposed; subsequently, a master curve for Alloy 690 SG material is also proposed to optimize the creep model parameters, θi (i = 1-5). To adapt the implicit creep scheme to the finite element code, a partial derivative of incremental creep with respect to the stress is necessary. Accordingly, creep model parameters with a strictly linear relationship with the stress and temperature were proposed. The effectiveness of the model was validated using a commercial finite element analysis software. The creep model can be applied to evaluate the creep rupture behavior of SG tubes in nuclear power plants.

A mechanism for Converting BPMN model into Feature model based on syntax (구조 기반 BPMN 모델의 Feature 모델로 변환 기법)

  • Song, Chee-Yang;Kim, Chul-Jin
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.17 no.1
    • /
    • pp.733-744
    • /
    • 2016
  • The legacy methods for converting a business model to a feature model make it difficult to support an automatic transformation due to a dependence on a domain analyzers' intuitions, which hinders the feature oriented development for the integration of feature modeling in business modeling. This paper proposes a method for converting a BPMN business model into a feature model based on syntax. To allow the conversion between the heterogeneous models from BPMN to the FM(Feature Model), it defines the grouping mechanism based activities' syntax, and then makes translation rules and a method based on the element (represent business function) and structure (relationships and process among elements), which are common constructs of their models. This method was applied to an online shopping mall system as a case study. With this mechanism, it will help develop a mechanical or automated structure transformation from the BPMN model to the FM.