Search Results - (( parameter evaluation system algorithm ) OR ( changes optimization based algorithm ))
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Efficiency and accuracy of scheduling algorithms for final year project evaluation management system
Published 2023“…This research paper conducts a comparative analysis of three algorithms: genetic algorithm, hill climbing algorithm, and particle swarm optimization algorithm, with a focus on evaluating their performance in scheduling presentations. …”
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Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control
Published 2014“…The robustness of the proposed algorithm is further investigated by evaluating the response of the system under simultaneous step load perturbation (SLP), changing load demand and collectively varying system parameters in the range of ±50%. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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Evaluation of genetic algorithm based solar tracking system for photovoltaic panels
Published 2008“…Literature suggested that the PV panels could produce maximum power if the panels have angle of inclination zero degree to the sun position. This work evaluate the best combination of GA parameters to optimize a solar tracking system for PV panels in terms of azimuth angle and tilt angle. …”
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Multi leader particle swarm optimization for optimal placement and sizing of multiple distributed generation for a micro grid
Published 2023“…In addition, the solutions have been evaluated based on pre-defined performance metrics and the outcomes of the optimization framework were compared with the other existing optimization techniques to evaluate the potency and the productivity of the developed MLPSO algorithm. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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Recent methodology based Harris Hawks optimizer for designing load frequency control incorporated in multi-interconnected renewable energy plants
Published 2023“…This paper proposes a reliable approach-based Harris Hawks Optimizer (HHO) to evaluate the optimal parameters of the Proportional�Integral (PI) controller simulating load frequency control (LFC) incorporated in a multi-interconnected system with renewable energy sources (RESs). …”
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Dynamic control and performance of dual active bridge converter based particle swarm optimization
Published 2022“…While in indirect tuning method, the optimal values of PI parameters are functioning to well-tuned the desired ϕ in the DAB system, where both values of KP and KI have been optimized using the PSO algorithm. …”
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Prediction of photovoltaic system output using hybrid Cuckoo Search Least Square Support Vector Machine / Muhammad Aidil Adha Aziz
Published 2019“…Therefore, Cuckoo Search Algorithm (CS) is hybrid with LS-SVM in order to optimize the RBF parameters for a better prediction performance. …”
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Simultaneous controllers for stabilizing the frequency changes in deregulated power system using moth flame optimization
Published 2022“…The performance of MFO-based 2DOF PID-FOPDN is evaluated against Cuckoo search (CS), Bat algorithm (BA), and Teaching learning-based optimization (TLBO) approaches in different contract scenarios of deregulated system. …”
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Advancing voltage control in DC microgrids: a comparative study with IGWO-based H∞ control
Published 2024“…The H∞ controller's weighted parameters are precisely determined using the IGWO algorithm to enhance system stability. …”
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Adaptive manet OLSR routing protocol for optimal route selection in high dynamic network
Published 2020“…The statistical framework based on QoS requirements is introduced for optimal solutions. …”
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Optimal PI controller based PSO optimization for PV inverter using SPWM techniques
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The computational complexity and mathematical formulation solutions are some limitations in optimizing the relay characteristic changes with changes in the system reactive power penetration for effective fault detection and isolations. …”
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Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios
Published 2015“…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. …”
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Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network
Published 2024“…The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. …”
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Online auto-tuned proportional-integral controller using particle swarm optimization for dual active bridge DC-DC converter
Published 2021“…APSO-PI is an auto-tuned PI using the PSO algorithm where the optimal values of Kp and Kiwere tuned at the initial control process only. …”
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…The synthetic reaction was optimized by Taguchi method based on orthogonal array to evaluate the effect of each parameters and interactive effects of reaction parameters including temperature, time, amount of enzyme, amount of molecular sieve, amount of solvent, and molar ratio of substrates (xylitol: fatty acid). …”
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Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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