Search Results - (( text generation method algorithm ) OR ( parameter optimization method algorithm ))
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1
Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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2
Machining optimization using Firefly Algorithm / Farhan Md Jasni
Published 2020“…For this project, we will verify the Firefly Algorithm (FA) into finding total profit rate by optimizing the machining parameter of milling operation and compare the effectiveness of FA with other non¬conventional method. …”
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3
Optimizing Central Pattern Generators (CPG) Controller For One Legged Hopping Robot By Using Genetic Algorithm (GA)
Published 2018“…Therefore,a computational stochastic optimization method; GA is designed to optimize the CPG controller parameters. …”
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4
A modified technique in RFID networking planning and optimization
Published 2015“…To reduce the complexity of the optimization process, this research focuses on developing a method to determine the optimum setting for PSO parameters. …”
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5
Optimal Location And Sizing Of Distrubuted Generator Using PSO And GA Algorithms In Power Systems
Published 2019“…Some existing algorithms need to be improved while others, need to add a new parameter for improving the performance of optimization methods and making it more effective and efficient. …”
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6
Optimal location and size of distributed generation to reduce power losses and improve voltage profiles using differential evolution optimization method
Published 2016“…Some existing algorithms need to be improved while others, need to add a new parameter for improving the performance of optimization methods and making it more effective and efficient. …”
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7
Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…Friedman test using GRG metric shows significant better performance (p-values<0.05) for PACS algorithm compared to benchmark algorithms. The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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8
Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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9
The convergence properties of a new hybrid conjugate gradient parameter for unconstrained optimization models
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10
Optimization machining parameters in pocket milling using genetic algorithm and mastercam
Published 2023“…Genetic Algorithm (GA) has been implemented to obtain the optimum parameters. …”
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11
Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…The obtained results of the proposed algorithm are compared to simulated results of the original Particle Swarm Optimization (PSO) method and the present state-of-the-art optimization techniques. …”
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12
Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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13
Power generation allocation in smart grid using Dwarf Mongoose Optimization / Mohamad Irfan Shamani
Published 2025“…Dwarf Mongoose Optimization (DMO) is a new metaheuristic algorithm that published in 2022 by Jeffrey O. …”
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14
Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…Extensive experimentation with genetic algorithm parameters has yielded promising results, notably a parameter set (population size = 12, generation size = 30, mutation rate = 0.2) demonstrating robust performance, achieving optimal timetables with swift convergence and minimal conflicts. …”
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15
Optimal Power Flow of power systems using Harris Hawks Optimization and Salp Swarm Algorithm
Published 2021“…The obtained results showed the decent improvement comparing to other swarm-based techniques like Whale Optimization Algorithm (WOA), Math Flame (MF), and Glowworm Optimization Algorithm (GOA) in terms of convergence performance and quality. …”
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16
Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…The results showed that the Firefly Algorithm (FA) performs much better for the optimal allocation and sizing of DG compared to the other metaheuristic techniques, particularly based on convergence characteristics and standard deviation. …”
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17
Breaking A Playfair Cipher Using Single and Multipoints Crossover Based on Heuristic Algorithms
Published 2023Conference Paper -
18
Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…Meanwhile, the proposed QOJaya algorithm produces better results than the basic Jaya method in terms of solution optimality and convergence speed. …”
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19
Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…There are two main problems that affect classification performance in software defect prediction: noisy attributes and imbalanced class distribution of datasets, and difficulty of selecting optimal parameters of the classifiers. In this study, a software defect prediction framework that combines metaheuristic optimization methods for feature selection and parameter optimization, with meta learning methods for solving imbalanced class problem on datasets, which aims to improve the accuracy of classification models has been proposed. …”
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20
Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…Finally, the algorithm is able to reduce SLL to -25.23 dB. The third method develops a new algorithm named Division Algorithm (DA) to solve the optimization problems. …”
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