Search Results - (( parameter estimation mining algorithm ) OR ( parameter estimation mead algorithm ))
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Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia
Published 2023“…Nelder-Mead outperforms the other optimization algorithm with the least error. …”
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Tree-based contrast subspace mining method
Published 2020“…Hence, this thesis presents the optimization of parameters values for the tree-based method by genetic algorithm. …”
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Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Poisson Transmuted Exponential Distribution For Count Data With Skewed, Dispersed And Excess Zero
Published 2024“…Different Moment-Based Mathematical Properties Of The New Proposed Distributions Are Obtained. Different Algorithms Are Used To Assess The Maximum Likelihood Estimates For The Parameters Of The Proposed Distributions.The Newton-Raphson And The Nelder-Mead, With Minimum Iterations For Convergence And Log-Likelihood Values, Provide Optimum Estimates. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. The effectiveness of this algorithm is verified by applying it on the unconstrained and constrained test functions through a simulation study. …”
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6
Simulation of COVID-19 outbreaks via graphical user interface (GUI)
Published 2021“…An improved SIRD model was solved via the 4th order Runge-Kutta (RK4) method and 14 unknown parameters were estimated by using Nelder- Mead algorithm and pattern-search technique. …”
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Nonlinear partial differential equations model related to ethanol production
Published 2019“…Since the model is nonlinear partial differential equations (PDEs), Gear's algorithm, a numerical method was employed to solve the system while the Nelder-Mead method is utilised to estimate the value of the parameters. …”
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Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
Published 2015“…The purpose of this project is to research more about the flood occurrence in Temerloh, Pahang. The data mining approaches using artificial neural network (ANN) techniques will be use to conduct this research for flood estimation. …”
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Undergraduates Project Papers -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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11
Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…This current study proposes an intelligent data mining approach for the Machine Learning- Adaptive Distance Relay (ML-ADR) fault classification model using novel extracted 1-cycle transient voltage and current signals hidden knowledge from both healthy and faulty lines parameters. …”
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Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak
Published 2022“…Waikato Environment for Knowledge Analysis (WEKA) version 3.8 was adopted for data mining analysis at two levels of classification stages. …”
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Identification of debris flow initiation zones using topographic model and airborne laser scanning data
Published 2017“…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the third step, the long term optimal investment strategies of the hybrid wind-thermal investor are determined based on the dynamic programming algorithm by considering the long term states of demand growth and fuel price uncertainties. …”
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Thesis
