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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…A two-step enhanced non-dominated sorting HHMO (2SENDSHHMO) algorithm has been proposed to solve this problem. …”
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A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Even though Cuckoo Search has been proven to be able to solve global optimization in various areas, the algorithm leads to a slow convergence rate when the step size is large. …”
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Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm
Published 2025“…The intent is to formulate an algorithm capable of adapting to fluctuations in excitation frequencies and the structural modal parameters. …”
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Design of QFT-based self-tuning deadbeat controller
Published 2013“…QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. …”
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Design of QFT-based self-tuning deadbeat controller
Published 2013“…QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. …”
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Development of hybrid artificial intelligent based handover decision algorithm
Published 2017“…The performance of the newly developed k � step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. …”
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An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz
Published 2017“…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system
Published 2023“…Undertaking a couple of modifications to the conventional marine predators algorithm (MPA), random average marine predators algorithm (RAMPA) with tunable adaptive coefficient to control the step size (CF) has been proposed in this paper as an enhanced alternative towards fine-tuning data-driven multiple-node hormone regulation neuroendocrine-PID (MnHR-NEPID) controller parameters for the multi-input–multi-output (MIMO) gantry crane system. …”
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Sensorless Adaptive Fuzzy Logic Control Of Permanent Magnet Synchronous Motor
Published 2008“…The main features of the proposed controller are; quick recovery of motor’s speed from load disturbances and insensitivity to parameter variation over a wide speed range. The proposed controller is a hybrid model reference adaptive speed controller (HMRASC) which mainly consists of two functional blocks. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Full search (FS), three step search (TSS), new three step search (NTSS), diamond search (DS) and hexagon based search (HS) are the most well known block-matching algorithm. …”
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Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman
Published 2014“…The last part is the development of a metal artifact correction (MAC) algorithm and evaluation of the proposed algorithm in artifacts reduction in CT images. …”
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Optimal Tuning of Fractional Order Sliding Mode Controller for PMSM Speed Using Neural Network with Reinforcement Learning
Published 2024“…To determine the optimal parameters of the FOSMC for control speed in a PMSM drive, a neural network algorithm with reinforcement learning (RLNNA) is proposed. …”
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Dynamic control and performance of dual active bridge converter based particle swarm optimization
Published 2022“…A 200 kW DAB system with single-phase shift (SPS) modulation is tested for direct and indirect online tuning phase-shift angle, ϕ using PSO algorithm. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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Simultaneous Adaptation Of Multiple Genetic Algorithm Parameters Using Fuzzy Logic Controllers
Published 2010“…This study aims at designing an online adaptive method to control multiple parameters of the Genetic Algorithm. …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit
Published 2024“…Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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Exploring dynamic self-adaptive populations in differential evolution
Published 2006“…In this paper, we present a first attempt at self-adapting the population size parameter in addition to self-adapting crossover and mutation rates. …”
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