Search Results - (( parameter estimation path algorithm ) OR ( model estimation method algorithm ))
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1
All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…The results also show that the proposed method outperforms other LMS algorithm without secondary path modelling. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…This paper presents a study to estimate future Health Index (HI) of transformer population based on Hidden Markov Model (HMM). …”
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4
A new hybrid multiaxial fatigue life model based on critical plane continuum damage mechanics and genetic algorithm
Published 2015“…The proposed model serves as path-independent fatigue life estimating tool hence can be used with any type of loading conditions. …”
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5
Genetic algorithm for control and optimisation of exothermic batch process
Published 2013“…Therefore, genetic algorithm (GA) is proposed in this work since precise mathematical model is not required. …”
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6
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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7
Composite nonlinear feedback control with multi-objective particle swarm optimization for active front steering system
Published 2024journal::journal article -
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Reconfigurable Stewart Platform for Spiral Contours
Published 2011“…The results obtained are to be validated for singularity-free path planning and attempt has to be made to estimate the computational efficiency of the algorithm. …”
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9
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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10
Embedded Dual Band Rfid Based Blood Glucose Monitoring System For Internet Of Medical Things
Published 2020“…These two parameters are then taken into account in experimental setup for performance evaluation of the enhanced CSMA/CA (EN-CSMA/CA) algorithm that uses an external interrupt mechanism and a cross layer approach. …”
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11
Enhancing navigation accuracy of Turtlebot3 Burger mobile robot
Published 2024“…The basic navigation of the robot requires a significant amount of data and resources to process the output path. To address this challenge, the Kalman Filter algorithm is implemented in this robot, as it is widely used for mobile robot navigation and system integration. …”
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12
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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13
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak
Published 2018“…The algorithm works if the quadrotor undergoes a deviation, an admissible trajectory path is generated for the quadrotor rapidly return on the straight-line route. …”
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15
An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Based on the results, the QOBLESS method can be used as an efficient parameter estimation method in large-scale kinetic model building.…”
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Development of robust control scheme for wheeled mobile robot in restricted environment
Published 2021“…A novel algorithm so called laser simulator logic (LSL) has been develo ped to estimate the inertia moment when the environment is noisy and cannot use fuzzy logic algorithm. …”
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18
Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System
Published 2008“…The model has estimated the runoff using the Soil Conservation Service-Curve Numbers (SCS-CN), determined by the land use/ land cover and the hydrological soil group found in each grid. …”
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19
Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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