Search Results - (( based optimization modified algorithm ) OR ( parameter optimization strategy algorithm ))
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Methodology for modified whale optimization algorithm for solving appliances scheduling problem
Published 2020“…Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. …”
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Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem
Published 2022“…Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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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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HYBRID SINE COSINE AND FITNESS DEPENDENT OPTIMIZER FOR INCOMPLETE DATASET
Published 2024“…The modifications include a modified pace-updating equation, a random weight factor and global fitness weight strategy, a conversion parameter strategy, and a best solution-updating strategy. …”
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Hybrid evolutionary optimization algorithms: A case study in manufacturing industry
Published 2014“…In this chapter, a new hybrid evolutionary optimization based methodology using a specific non-linear membership function, named as modified S-curve membership function, is proposed. …”
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Spread enhancement for firefly algorithm with application to control mechanism of exoskeleton system
Published 2019“…Firefly algorithm (FA) is a swarm intelligence based algorithm for global optimization and has widely been used in solving problems in many areas. …”
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An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization
Published 2019“…To adaptively switches between the two algorithms, an adaptive switching algorithm based on a Generalized Likelihood Ratio Test (GLRT) is proposed. …”
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Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…The model employs a two-level structure, where the first level uses standard soft constraints as the objective function to evaluate solution quality, while the second level dynamically adapts to faculty-specific preferences. A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment
Published 2017“…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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Design of wavelet neural networks based on symmetry fuzzy C-means for function approximation
Published 2013“…Specifying the number and locations of the translation vectors for wavelet neural networks (WNNs) is of paramount significance as the quality of approximation may be drastically reduced if initialization of WNNs parameters was not done judiciously. In this paper, an enhanced fuzzy C-means algorithm, specifically the modified point symmetry–based fuzzy C-means algorithm (MPSDFCM), was proposed, in order to determine the optimal initial locations for the translation vectors. …”
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Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm
Published 2015“…Developing an exploration algorithm based on spanning tree is the main contribution. …”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…Performance indicators included the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and Parameter Magnitude-based Information Criterion 2 (PMIC2). …”
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Image watermarking optimization algorithms in transform domains and feature regions
Published 2012“…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…The feature evaluation strategy is formulated based on mutual information (MI) to handles both classification and regression supervised learning tasks and the search strategy is a modified greedy forward strategy designed to manage redundancy between features and avoiding features that are irrelevant to the predicting output. …”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis
Published 2025“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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A krill herd behaviour inspired load balancing of tasks in cloud computing
Published 2017“…The speed, task cost, and weight of the tasks were first determined, after which, the Krill herd optimization algorithm was for the load balancing based on the measured parameters. …”
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Structural health monitoring using adaptive wavelet functions / Seyed Hossein Mahdavi
Published 2016“…For this purpose, a wavelet-based GAs strategy is improved by using free-scaled adaptive wavelets to optimally identify unknown structural parameters. …”
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