Search Results - (( parameter estimation based algorithm ) OR ( data integration using algorithm ))
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Mixed Unscented Kalman Filter and differential evolution for parameter identification
Published 2013“…UKF have known to be a typical estimation technique used to estimate the state vectors and parameters of nonlinear dynamical systems and DE is one of the most powerful stochastic real-parameter optimization algorithms. …”
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Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array
Published 2019“…The third methodology is to integrate the proposed controller on FPGA, using a new method to run the design based simulink model. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
Published 2023“…The obtained GWO-PSO models which is model order 2 and model order 4 were verified by using proportional-integral-derivative (PID) based controller. …”
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A Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf.
Published 2013“…This research attempted to develop a new approach to estimate k d in blue and green bands of QuickBird satellite image based on the integration of Lyzenga’s method and updated NASA-k d 490 algorithm. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. …”
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Properties of selected garma models and their estimation procedures
Published 2012“…The focus of this study is to investigate the properties specically the variance and autocovariance of the GARMA (p; q; ±1; ±2) models. We also study the estimation of the parameters of these models. Evaluation of the performance of two estimators based on the Hannan-Rissanen Algorithm Estimator (HRA) and the Whittle's Estimator (WE) through a series of simulation studies have been conducted in this thesis. …”
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Genetic algorithm for control and optimisation of exothermic batch process
Published 2013“…In general, most of the studies use predictive approach to estimate the process behaviour and a slave controller, usually proportional-integral-derivative (PID), is employed to control the process based on the estimated plant behaviour. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir
Published 2020“…In this study, we present a knowledge based seismic acoustic impedance inversion method which employs rule based method for porosity estimation. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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Robust estimation methods for fixed effect panel data model having block-concentrated outliers
Published 2019“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Reference evapotranspiration estimation using adaptive neuro-fuzzy inference system
Published 2011“…It has been found that the minimum required meteorological parameters that gives the low error rate under arid and semi-arid conditions are temperature and wind speed data, and under humid conditions are temperature data and estimated relative humidity data from temperature data (by FAO-56 reduced set approach). …”
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Estimating the total Malaysian road accidents and fatalities using Gauss-Newton method of least squares / Maureen Giman, Siti Zulaikha Muhamad Zuraidi and Syahida Asyikin Moner
Published 2022“…Meanwhile, the Levenberg-Marquadt method uses the gradient descent algorithm, which also has a similar algorithm to the Gauss-Newton method in finding the value for the unknown parameter.…”
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Adaptive template matching of photoplethysmogram pulses to detect motion artefact
Published 2018“…The performance of our algorithm was evaluated using data obtained from two different sources: (i) our own data collected from 19 healthy subjects using the wearable Sotera Visi Mobile system (Sotera Wireless Inc.) as they performed various movement types; and (ii) ICU data provided by the PhysioNet MIMIC II database. …”
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Covariance matrix analysis in simultaneous localization and mapping
Published 2016“…In EKF-based SLAM, measurement data are required at each time step to complete the estimation process. …”
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A Hydrologic Model for Studying the Climate Change Impact on Evapotranspiration and Water Yield in a Humid Tropical Watershed
Published 1998“…A procedure was presented and evaluated for subdividing a watershed into GRUs through the application of an unsupervised pattern recognition algorithm in conjunction with topographic data to Landsat Thematic Mapper (TM) data in a GIS environment. …”
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Modeling of cupping suction system based on system identification method
Published 2022“…Cupping suction plant identification utilizing a nonlinear model based on the modified Sine Cosine Algorithm (mSCA). …”
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Undergraduates Project Papers -
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia
Published 2010“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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