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1
Kinetic parameters estimation of the Escherichia coli (E. coli) model by Garra Rufa-inspired Optimization Algorithm (GRO)
Published 2024“…So, Garra Rufa-inspired Optimization (GRO) Algorithm is applied to the primary metabolic network of E. coli as a model to estimate small-scale kinetic parameters and increase the kinetic accuracy. …”
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2
Modified archive update mechanism of multi-objective particle swarm optimization in fuzzy classification and clustering
Published 2022“…However, the PSO algorithm produces a group of non-dominated solutions which makes the choice of a “suitable” Pareto optimal or non-dominated solution more difficult. …”
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Thesis -
3
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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4
Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm
Published 2022“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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5
Multifunctional optimized group method data handling for software effort estimation
Published 2022“…Group Method of Data Handling (GMDH) algorithms have been widely used for modelling and identifying complex systems and potentially applied in software effort estimation. …”
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6
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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7
DEVELOPMENT OF PREDICTIVE MODELS FOR INFINITE DILUTIONACTIVITY COEFFICIENTOF ALCOHOLIN IONIC LIQUIDSUSING GROUP CONTRIBUTION METHOD
Published 2020“…In this work, two van’tHoff models consist of two (Model I) and three parameters (Model II) are used to calculate the value of IDAC using multiple linear regression (MLR) method and optimized by generalized reduced gradient (GRG) non-linear algorithm in order to obtain a similar value from both experimental and predicted data points…”
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8
DEVELOPMENT OF COMPOSITIONAL MODEL FOR PREDICTING VISCOSITY OF CRUDE OILS USING POLYNOMIAL NEURAL NETWORKS (PNN) INDUCED BY GROUP METHOD OF DATA HANDLING (GMDH)
Published 2011“…GMDH is an inductive algorithm for computer-based mathematical modeling using neural network with active neurons that optimizes model coefficients for predetermine mathematical equation and selects the optimal model complexity. …”
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9
Identifying high influence parameters using Genetic Algorithm (GA) chromosomes for water consumption
Published 2021“…This work utilized Genetic Algorithm (GA) to optimize the coefficient of micro-components of water consumption (CMWC) values to determine high influential household routine parameters. …”
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10
Radiation dose, cancer risk and diagnostic performance of computed tomography pulmonary angiography examination
Published 2021“…Hence, this study aims to evaluate the radiation dose, cancer risk and image diagnostic performance of CTPA examination regarding primary and secondary optimization such as iterative reconstruction (IR) algorithm, tube potential and pitch factor selection. …”
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11
Development of Fluid Properties Correlation For Malaysian Crude
Published 2013“…This project will be used MATLAB software and Microsoft Excel through the method of Group Method of Data Handling (GMDH) . …”
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Final Year Project -
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SEARCH GROUP ALGORITHM FOR MULTI-OBJECTIVE OPTIMIZATION IN ENERGY APPLICATIONS
Published 2020“…This study proposed a new multi-objective version of the Search Group Algorithm (SGA) called the Multi-Objective Search Group Algorithm (MOSGA), aiming for the multi-objective optimization in energy applications. …”
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13
Optimization of k-Nearest Neighbour to categorize Indonesian’s news articles
Published 2021“…There are several filter-based feature selection methods; some are Chi-Square, Information Gain, Genetic Algorithm, and Particle Swarm Optimization (PSO). …”
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14
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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15
Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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16
Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD)
Published 2020“…However, MOPSO algorithm produces a group of non-dominated solutions which make the selection of an “appropriate” Pareto optimal or non-dominated solution more difficult. …”
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Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks
Published 2023“…In addition, it also concluded that metaheuristic optimization algorithm and weighted least square method are more suitable to conquer anisotropic factor. …”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification
Published 2007“…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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Improvement and application of particle swarm optimization algorithm
Published 2025“…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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