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1
Finite impulse response optimizers for solving optimization problems
Published 2019“…Optimization problems are frequently found in various fields. The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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2
Finite impulse response optimizers for solving optimization problems
Published 2019“…Optimization problems are frequently found in various fields. The classification of estimation-based metaheuristic algorithms has been introduced for solving optimization problems. …”
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3
Analysis of multicomponent transient signals using music superresolution technique
Published 2008“…The problem of estimating the parameters of transient signals consisting of real decay constants has for long been a subject of study by many researchers. …”
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4
Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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5
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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6
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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7
Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nurulhuda Zainuddin and Khairiyah Md Shahid
Published 2012“…Multilayer perceptrons (MLPs) is one of the topology used for processing ANN, while backpropagation algorithm is one of the most popular methods in training MLPs. …”
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Research Reports -
8
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In order to improve recognition of high interclass similarity activities, One-Versus- All (OVA) binarization strategy is introduced by transforming original multi-class classification problems into a series of two-class classification problems. …”
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9
Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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10
Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…In these extended IFS method, feature selection method was defined and presented as a 0-1 Knapsack Problem (MKP). …”
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11
Robust techniques for linear regression with multicollinearity and outliers
Published 2016“…However, no research is focused on the parameter estimation method to remedy the problem of multicollinearity which is due to multiple HLPs. …”
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12
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…The modification comprises of two main modelling problems: high-dimensionality and missing data. These problems were extensively studied within the scope of classification (binary and multi-class) and regression (linear and survival). …”
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13
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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14
An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Article -
15
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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16
The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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17
Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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18
Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm
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An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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