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1
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…The newly proposed algorithm was tested using a set of standard benchmark functions with different searching space and global optima placement. …”
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2
Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays
Published 2023“…Animals; Antenna arrays; Antennas; Beam forming networks; Beamforming; Behavioral research; Bioinformatics; Evolutionary algorithms; Global optimization; Problem solving; Swarm intelligence; Bio-inspired algorithms; Co-operative behaviors; Global optimization problems; Meta heuristics; Optimization algorithms; Optimization techniques; Real-parameter optimization; Swarm algorithms; Optimization…”
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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4
A new HMCR parameter of harmony search for better exploration
Published 2016“…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
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5
A new HMCR parameter of harmony search for better exploration
Published 2015“…As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. …”
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6
A multiobjective simulated Kalman filter optimization algorithm
Published 2018“…This paper presents a new multiobjective type optimization algorithm known as a Multiobjective Optimization Simulated Kalman Filter (MOSKF). …”
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7
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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8
A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems
Published 2021“…This paper presents a new hybrid identification algorithm called the Average Multi-Verse Optimizer and Sine Cosine Algorithm for identifying the continuous-time Hammerstein system. …”
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9
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…This paper proposes a new SGD algorithm with modified stepsize that employs function scaling strategy. …”
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10
Design of low order quantitative feedback theory and H-infinity-based controllers using particle swarm optimisation for a pneumatic actuator system
Published 2010“…On the other hand, the design of conventional control with structured and unstructured uncertainties is also presented. The PSO algorithm is used to minimize the infinity norm of the transfer function of the nominal closed loop system to obtain the optimal parameters of the weighting functions. …”
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11
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…In particular, the search capacity of the MVO algorithm has been improved using the sine and cosine functions of the Sine Cosine Algorithm (SCA) that will be able to balance the processes of exploration and exploitation. …”
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12
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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13
Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method
Published 2024“…The OCRC is established by manipulating the current known as plus setting (PS) and time delay known as time multiplier setting (TMS) parameters. The optimized value of the TMS and PS will be selected using the algorithms to ensure the minimize result of the objective function. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane
Published 2021“…The efficiency of the proposed HMVOSCA algorithm is evaluated using the convergence curve, parameter estimation error, bode plot, function plot, and Wilcoxon's test method. …”
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15
Fractional chaos maps with flower pollination algorithm for chaotic systems� parameters identification
Published 2023“…Chaotic systems; DC motors; Heuristic algorithms; Optimization; Benchmark functions; Chaotic behaviors; Convergence speed; Evaluation function; Meta-heuristic optimizations; Non-parametric statistical tests; Optimization problems; Parameters identification; Parameter estimation…”
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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17
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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18
Optimal power flow using the Jaya algorithm
Published 2016“…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…Specifically, in electromagnetic field, bidirectional scattering distribution function of a diffraction grating is computed using MEEP simulation and requires numerous numbers of parameters. …”
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20
Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia
Published 2024“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. …”
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