Search Results - (( parameter optimization based algorithm ) OR ( initial solving system algorithm ))
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1
Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization
Published 2022“…Global optimization method based on an enhanced scatter search (ESS) algorithm is a suitable choice to address this issue. …”
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Artificial neural networks based optimization techniques: A review
Published 2023“…The entire set of such techniques is classified as algorithms based on a population where the initial population is randomly created. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Afterward, a genetic algorithm-based optimization framework was designed to improve the interpretability and accuracy of the proposed fuzzy-tabu controller by optimizing the parameters of the FLC and also some of the planner’s parameters in order to improve the quality of the generated paths and runtimes of the planner and also to decrease the variation of the results in different runs of the planner. …”
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Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff
Published 2011“…The main goal of this research is to compare the performances between Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. …”
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5
Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column
Published 2005“…Based on this formulation, a Mass Transfer of A Single Drop (MTASD) Algorithm was designed, followed by a more realistic Mass Transfer of Multiple Drops (MTMD) Algorithm which was later refined to become another algorithm named the Mass Transfer Steady State (MTSS) Algorithm. …”
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6
Renewable sources-based automatic load frequency control of interconnected systems using chaotic atom search optimization
Published 2022“…This paper proposes an improved form of chaotic based atom search optimization (IASO) algorithm by adapting one-dimensional (1D) chaotic map (tent, sine and logistic) to improve the search ability by intensifying the exploration and exploitation phase. …”
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7
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…While the main aim of this thesis is to present a new computational methodfor solving discrete-valued optimal control problems, the initial focus is on solvingpurely discrete optimization problems. …”
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8
Solving an application of university course timetabling problem by using genetic algorithm
Published 2022“…Among the approaches, genetic algorithm (GA), constructed based on Darwin's theory of evolution, becomes the renowned approach to solve various types of timetabling problems. …”
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Optimization of process parameters for rapid adsorption of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite using wavelet neural network
Published 2016“…In this study, a wavelet neural network (WNN) based on the incremental backpropagation (IBP) algorithm was used in conjunction with an experimental design. …”
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Design of single- and multi-loop self-adaptive PID controller using heuristic based recurrent neural network for ALFC of hybrid power system
Published 2022“…Then, these dynamics are solved using hybrid particle swarm optimization-gravitational search algorithm (PSO-GSA) to obtain the initial solution. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The design of the APFLC is initially started with the designation of Basic FLC with two input and single output system. …”
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12
An advanced scheme based on Artificial Intelligence technique for solving nonlinear Riccati systems
Published 2024“…This work aims to implement a feedforward ANN with two hidden layers to solve nonlinear systems based on the fractional Riccati differential equation (FRDE). …”
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Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations
Published 2024“…Finally, ANNs employing a combination of power series methods in the GCFFD are developed to approximate solutions of higher-order linear FFDEs with both constant and variable coefficients. Initially, the algorithm utilized a truncated series. …”
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14
Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Then, design of experiments is used to examine the sensitivity of the parameters of each solving algorithm using Taguchi method. …”
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15
Optimization of slosh suppression system through data-driven state feedback controller
Published 2024“…The general view of the data-driven control framework is to obtain the optimal solution of the controller’s parameter by only using the recorded input and output data system without any mathematical model system. …”
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16
A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…Obviously, selecting four muscles to attain a full joint moment and motion is not sufficient, therefore we introduced the net joint moment obtained from the inverse dynamics to optimize the predicted joint moment. Initial estimate of the model is obtained from literature review while the Levenderg-Marquardt (LM) method is applied to solve the nonlinear least squares optimization problem. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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18
On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems
Published 2019“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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