Search Results - (( parameter adaptation machine algorithm ) OR ( parameter optimization method algorithm ))
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BBO algorithm-based tuning of PID controller for speed control of synchronous machine
Published 2023Article -
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Nature-inspired parameter controllers for ACO-based reactive search
Published 2015“…This study proposes machine learning strategies to control the parameter adaptation in ant colony optimization algorithm, the prominent swarm intelligence metaheuristic.The sensitivity to parameters’ selection is one of the main limitations within the swarm intelligence algorithms when solving combinatorial problems.These parameters are often tuned manually by algorithm experts to a set that seems to work well for the problem under study, a standard set from the literature or using off-line parameter tuning procedures. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
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Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm
Published 2025“…The research aims to optimize key TMD parameters (mass ratio, damping ratio, and frequency ratio) using the dynamic CS algorithm. …”
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Sensitivity analysis of drill wear and optimization using Adaptive Neuro fuzzy –genetic algorithm technique toward sustainable machining
Published 2018“…Effects of spindle rotational speed, feed rate and diameter of drill on tool wear were determined through Adaptive Neuro Fuzzy Inference System (ANFIS). Next, genetic algorithm (GA) was used to identify the optimal drilling parameter for different diameters of drill. …”
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Single Machine Connected Infinite Bus system tuning coordination control using biogeography-based optimization algorithm
Published 2023“…The BBO algorithm is demonstrated to tune the control parameter values of coordinated damping controller. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Minimization of tool path length of drilling process using particle swarm optimization (PSO)
Published 2020“…In various publications and articles, scientists and researchers adapted several methods of artificial intelligence (AI) or hybrid optimization method for tool path artificial immune system (AIS), genetic algorithms (GA), Artificial Neural networks (ANN) Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) (Narooei and Ramli, 2014). …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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Assessment of ANN-based auto-reclosing scheme developed on single machine-infinite bus model with IEEE 14-bus system model data
Published 2009“…The results show the efficacy of the developed adaptive automatic reclosing method.…”
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Power system stabilizer optimization using BBO algorithm for a better damping of rotor oscillations owing to small disturbances
Published 2023“…We introduce here a latest biogeography-based optimization (BBO) algorithm to adjust PSS parameters for different operating conditions in order to improve the stability margin and the system damping. …”
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Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems
Published 2009“…In addition, Taguchi's methodology is employed in optimizing the parameters of each algorithm used for training, and in deciding the number of hidden neurons of the neural network. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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A comparative study of the Z-N, adaptation law and PSO methods of tuning the PID controller of a synchronous machine
Published 2023“…A proportional–integral–derivative (PID)-based power system stabilizer (PSS) was designed to damp low-frequency oscillations in power systems under different operating conditions. The parameters of the PID controller were tuned using a particle swarm optimization (PSO) algorithm. …”
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Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The framework addresses a gap in predictive analytics by combining computational techniques, consumer behavior theories, and demographic data to better understand and forecast purchasing trends. The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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