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Spiral-sooty tern optimization algorithm for dynamic modelling of a twin rotor system
Published 2022“…A spiral model is incorporated into the Sooty-Tern Optimization Algorithm (STOA) structure. …”
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Perovskite lattice constant prediction framework using optimized artificial neural network and fuzzy logic models by metaheuristic algorithms
Published 2023“…The identification of optimized parameters for the ANN and fuzzy logic models is accomplished using innovative metaheuristic algorithms such as, Particle Swarm Optimization (PSO), Invasive Weed Optimization (IWO) and Imperialist Competitive Algorithm (ICA). …”
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A New Optimization Algorithm based on Copulation Behavior of Simine Jackals
Published 2011“…This work introduces a new meta-heuristic algorithm, termed as Simine Jackal algorithm, designed to solve optimization problems. …”
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Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction
Published 2025“…Genetic algorithms for hyperparameter optimization significantly contributed, with the GA + LSTM + ADAGRAD model achieving 88% and 87% accuracy in the 7th and 9th models for BBB course data. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…Drawing from an extensive review of existing predictive models and cardiovascular health risk factors, this research proposes an enhanced ADAM optimization algorithm, integrated with advanced data processing and feature selection methodologies, to identify and refine key predictors for improved model performance. …”
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New bio-inspired barnacle optimizers based least-square support vector machine for time-series prediction of pandemic outbreaks
Published 2024“…These findings underscore the efficacy of GBO and its competitive edge in achieving accurate time-series predictions when compared to a diverse set of algorithms. The groundbreaking outcome of this research lies in the transformative impact of enhanced BMO variants, along with the innovative new bio-inspired GBO algorithm and GBO-LSSVM models. …”
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…As technology continues to advance, the demand for effective methodologies to design, analyse, and synthesize complex system models becomes vital. In response to this imperative, researchers have increasingly turned to optimization-based approaches, with the Sine Cosine Algorithm (SCA) emerging as a prominent solution. …”
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Using Spiral Dynamic Algorithm for Maximizing Power Production of Wind Farm
Published 2017“…This paper presents a preliminary study of a model-free approach based on spiral dynamic algorithm (SDA) for maximizing wind farms power production. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…Therefore, this study explores how to model reconfigurable manufacturing activities in an optimization perspective and how to develop and select appropriate non-conventional optimization techniques for reconfigurable process planning.In this study, a new approach to modeling Manufacturing Process Planning Optimization (MPPO) was developed by extending the concept of manufacturing optimization through a decoupled optimization method. …”
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An integrated model to email spam classification using an enhanced grasshopper optimization algorithm to train a multilayer perceptron neural network
Published 2021“…This study introduces an email detection model that is designed based on use of an improved version of the grasshopper optimization algorithm to train a Multilayer Perceptron in classifying emails as ham and spam. …”
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Long-term optimal planning of distributed generations and battery energy storage systems towards high integration of green energy considering uncertainty and demand response progra...
Published 2025“…Scenario reduction through the Backward Reduction Algorithm (BRA) manages computational complexity. To solve the proposed model, a hybrid approach combining Non-Dominated Sorting Genetic Algorithm II (NSGAII) and Multi-Objective Particle Swarm Optimization (MOPSO) is employed. …”
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Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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Energy-efficient base station transmission design for green 5G massive MIMO and hybrid networks
Published 2021“…Then, a new corresponding iterative EE optimization algorithm is proposed based on the BSTPA model to further improve the system’s EE. …”
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A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA)
Published 2024“…The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). …”
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Innovation of marketing supply chain management model based on SICAS modeling
Published 2024“…A collaborative optimization model of the supply chain based on virtual inventory management is constructed to ensure the normal operation of the whole supply chain by deploying flexible inventory in the hands of customers, and the constructed model is solved by using an evolutionary algorithm based on indexes and an optimal solution sorting method based on regret theory. …”
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Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif
Published 2024“…This approach integrates a conditional variational autoencoder (CVAE) to effectively balance the dataset and a stack predictor (SPFHD) that utilizes tree-based ensemble learning algorithms. The base models' predictions are integrated using a support vector machine, significantly enhancing detection accuracy. …”
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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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