Search Results - (( using optimization method algorithm ) OR ( variable evaluation system algorithm ))
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Harmony search-based robust optimal controller with prior defined structure
Published 2013“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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Optimization of biochemical systems production using combination of newton method and particle swarm optimization
Published 2019“…In the proposed method, the Newton method was used to deal with nonlinear equations system, while the PSO algorithm was utilized to fine-tune the variables in nonlinear equations system. …”
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Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication
Published 2021“…By using the optimization min-sum belief propagation approach, a low complexity min-sum (MS) based decoding algorithm called Variable Global Optimization Min-Sum (VGOMS) has been developed. …”
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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A Hybrid of Optimization Method for Multi-Objective Constraint Optimization of Biochemical System Production
Published 2015“…Then, Genetic Algorithm (GA) in SPEA and CCA were used to represent the variables in non-linear equations system into multiple sub-chromosomes. …”
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Fuzzy based BSA optimization for maximum power point tracking controller performance evaluation
Published 2023Conference Paper -
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm
Published 2025“…The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. …”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…Models were tested with both complete and missing output data to evaluate the robustness of the IAOA-based method. The proposed based method identified linear and nonlinear subsystem variables in a continuous-time Hammerstein model leveraging input and output data, validated through two practical experiments: a Twin Rotor System and an Electromechanical Positioning System. …”
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Single and Multiple variables control using Tree Physiology Optimization
Published 2017“…The proposed algorithm is also compared with deterministic gradient-free algorithm: Nelder-Mead simplex (NMS) and another metaheuristic algorithm: Particle Swarm Optimization (PSO). …”
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Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method
Published 2017“…The effectiveness of the proposed method is evaluated using two benchmark biochemical systems, and the experimental results show that the proposed method performs well compared to other works.…”
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Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer
Published 2024“…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH
Published 2021“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability
Published 2016“…Furthermore, to verify the suitability of the explored locations, a comparative study has been conducted after placing UPFC in the present locations and other locations obtained using optimization techniques like particle swarm optimization (PSO), differential evolution (DE), genetic algorithm (GA), and bacteria foraging algorithm (BFA). …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Thus, this thesis precisely developed and evaluated IFS_BACS (Binary Ant Colony System) hybrid method. …”
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Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…At last, PRPLS is implemented in photovoltaic system, specifically in the maximum power point tracking (MPPT) algorithm. …”
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Development of a two-level trade credit model with shortage for deteriorating products using hybrid metaheuristic algorithm
Published 2015“…In order to evaluate the solutions of the hybrid algorithm, the models are also solved by a global optimization solver,Branch-And-Reduce Optimization Navigator (BARON). …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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