Search Results - (( global contributing selection algorithm ) OR ( parameter optimization method algorithm ))
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1
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The performance of DE algorithm depends heavily on the selected mutation strategy and its associated control parameters. …”
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Thesis -
2
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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3
Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.]
Published 2024“…To enhance the accuracy of predicting pipeline defect sizes, this study introduces a magnetic leakage detection system, employing Backpropagation (BP) neural networks optimized with genetic algorithms. Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
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4
Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks
Published 2024“…To enhance the accuracy of predicting pipeline defect sizes, this study introduces a magnetic leakage detection system, employing Backpropagation (BP) neural networks optimized with genetic algorithms. Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
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5
Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…The findings showed that incorporating SPM with single-point crossover resulted in lower objective function (OF) values and improved error indices (EI) compared to traditional GA methods. This enhanced the GA's ability to avoid premature convergence and maintained a diverse solution set, leading to more optimal model selection. …”
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management
Published 2009“…After formulating the stochastic model using Mean Absolute Deviation, the problem is then investigated using the Pareto front solution of efficient frontier of the resulting multiobjective optimization problem by using the Weighted Sum Method as well as the ε-constraint method in order to obtain the Pareto Optimal Curve which generates a wide selection of optimization solutions for our problem. …”
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Final Year Project -
8
Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems
Published 2023“…In recent times, some considerations like high reliability and less energy consumption are essential to choosing the optimum CH nodes in clustering-related metaheuristic mechanisms. The selection of proper CHs using metaheuristic algorithms fnds useful in design of energy-efcient WSNs. …”
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9
Hybrid indoor positioning utilizing multipath- assisted fingerprint and geometric estimation for single base station systems
Published 2025“…This study makes a significant contribution by introducing a hybrid method that leverages multipath signals to achieve centimeter-level accuracy in indoor positioning systems.…”
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10
Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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13
Optimization of turning parameters using ant colony optimization
Published 2008“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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Undergraduates Project Papers -
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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Research Reports -
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Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation
Published 2025Subjects:Article -
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Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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17
Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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18
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Article -
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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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