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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…This chapter offers the sea salmon-associated polyp (SALP) swarm algorithm (SSA) and multipurpose SSA (MSSA) as new optimization algorithms for solving optimization problems with single and multiple objectives. …”
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Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm
Published 2023“…<p>This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. …”
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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024“…The teaching–learning-based optimization (TLBO) algorithm is a novel nature-based optimization approach that has attracted a lot of interest from researchers because of its great capacity to handle optimization problems. …”
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Whale optimization algorithm: analysis and full survey
Published 2024“…The survey further discusses the algorithm's performance on a wide range of optimization problems, showcasing its competitiveness and effectiveness. …”
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Holistic Design: Optimizing Mechatronic Systems Using Multi Objective Optimization
Published 2015Get full text
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Metaheuristic Optimization Algorithms for Training Artificial Neural Networks
Published 2012“…The Cuckoo Search (CS) algorithm is a recently developed meta-heuristic optimization algorithm which is suitable for solving optimization problems. …”
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Improved Jaya Synergistic Swarm Optimization Algorithm to Optimize Task Scheduling Problems in Cloud Computing
Published 2024“…In this paper, we propose an enhanced optimization algorithm tailored for task scheduling in cloud environments. …”
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A Survey of cuckoo search algorithm: optimizer and new applications
Published 2024“…The CS algorithm is further validated for solving numerous technological optimization challenges. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link
Published 2023“…<p dir="ltr">CubeSats have been gaining significant interest as a cost-effective solution that can be built with low power requirements for different mission types. …”
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A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems
Published 2025“…Unlike traditional attacks that use fixed or heuristic perturbation parameters, our GA-driven method dynamically evolves perturbation parameters through multi-objective fitness optimization, producing highly adaptive and effective adversarial examples. …”
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Multiobjective Optimal VAR Dispatch Using Strength Pareto Evolutionary Algorithm
Published 2020“…In this paper, strength Pareto evolutionary algorithm (SPEA) for optimal reactive power (VAR) dispatch problem is presented. …”
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Optimal multiobjective design of robust power system stabilizers using genetic algorithms
Published 2003“…Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. …”
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
Published 2011Get full text
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A multiobjective optimization method for the SOC Test Time, TAM, and power optimization using a strength pareto evolutionary algorithm
Published 2017“…This paper presents a multiobjective optimization approach for the SOC test scheduling problem. …”
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A Non-convex Economic Load Dispatch Using Hybrid Salp Swarm Algorithm
Published 2021“…In this paper, the economic load dispatch (ELD) problem with valve point effect is tackled using a hybridization between salp swarm algorithm (SSA) as a population-based algorithm and β-hill climbing optimizer as a single point-based algorithm. …”
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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
Published 2023“…These retransmissions further enhance the delay in LoRa networks. This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …”
