Search Results - (( global optimization method algorithm ) OR ( parameter simulation based algorithm ))
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Improved opposition-based particle swarm optimization algorithm for global optimization
Published 2021“…PSO also becomes trapped into local optima similarly to other nature-inspired algorithms. The literature depicts that in order to solve pre-mature convergence for PSO algorithms, researchers have adopted various parameters such as population initialization and inertia weight that can provide excellent results with respect to real world problems. …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Modelling of multi-robot system for search and rescue
Published 2023“…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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Design of PSO-based Fuzzy Logic Controller for single Axis Magnetic Levitation System.
Published 2011“…PSO algorithm is applied to search globally optimal parameters of FLCs. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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Thesis -
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Notably, the SPSA and GSPSA based methods only produced the optimal design parameter at the final iteration while it may keep a better design parameter during the tuning process if it has a memory feature. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…While the automatic method focus on optimization which is normally computer based. …”
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Final Year Project -
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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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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…As these methods are global optimizers, there is less possibility that they will fall in a local minima and are suitable for the selection of the parameters of the antecedent part. …”
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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 simulation results show the effectiveness of the ARDE method over other conventional techniques, transcending the limits of the existing state-of-the-art algorithms in estimating the parameters of robot. …”
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Efficiency improvement of a standalone photovoltaic system using fuzzy-based maximum power point tracking algorithm
Published 2016“…MPPT algorithms can be categorized into classical methods and artificial intelligence-based methods. …”
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Power Stabilization Of A Stand-Alone Solar System Using Perturb and Observe MPPT Algorithm
Published 2010“…This paper presents the method of power stabilization of a stand-alone solar system using perturb and observe (P&O) maximum power point algorithm. The PV module is modeled based on the parameters obtained from a commercial PV data sheet. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The proposed algorithm simulates the behavior of the nomads when they are searching for life sources (water or grazing fields). …”
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Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks / Wang Jie ... [et al.]
Published 2024“…To enhance the accuracy of predicting pipeline defect sizes, this study introduces a magnetic leakage detection system, employing Backpropagation (BP) neural networks optimized with genetic algorithms. Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
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Defect recognition method for magnetic leakage detection in oil and gas steel pipes based on improved neural networks
Published 2024“…To enhance the accuracy of predicting pipeline defect sizes, this study introduces a magnetic leakage detection system, employing Backpropagation (BP) neural networks optimized with genetic algorithms. Traditional BP networks face challenges, including parameter determination and slow convergence, addressed through genetic algorithms' global search capabilities. …”
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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination
Published 2022“…In this work, a new improved arithmetic optimization method based on the adaption of Newton–Raphson and Levenberg–Marquardt damping parameter (IAOANRaLMp) is presented to globally extract the parameter of the single- and double-diode PV models. …”
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Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks
Published 2017“…A search method with numerous advantages over conventional algorithms, has been designed to solve the optimization problems with an enhanced global optimality and convergence speed. …”
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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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Parameter extraction of solar photovoltaic modules using penalty-based differential evolution
Published 2012“…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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