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method optimization » motor optimization (Expand Search)
lines based » cities based (Expand Search)
life based » fe based (Expand Search)
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1
On the protection of power system: Transmission line fault analysis based on an optimal machine learning approach
Published 2022“…The design is carried out based on the selection of the optimal model parameters using a search optimization algorithm called GridSearchCV. …”
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Minimizing using BBO and DFO methods
Published 2022“…In order to apply this algorithm to real life problems, two numerical methods need to be developed: A numerical method to solve nonlinear differential equations, and a numerical method to nd the minimum of an objective function (given only numerically) in fi nite dimensional spaces. …”
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masterThesis -
3
Intelligent Rapidly-Exploring Random Tree Star Algorithm
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doctoralThesis -
4
Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems
Published 2020Get full text
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Real-Time Selective Harmonic Mitigation Technique for Power Converters Based on the Exchange Market Algorithm
Published 2020“…The Exchange Market Algorithm (EMA), initially focused on optimizing financial transactions, is considered and executed to achieve the SHM targets. …”
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Enhancement of power system dynamic performance through an on-line self-tuning adaptive SVC controller
Published 2006“…Use of a self-tuning adaptive control algorithm as a supplementary controller for the SVC is presented in this article. …”
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Nested ensemble selection: An effective hybrid feature selection method
Published 2023“…The NES algorithm achieves perfect precision on the synthetic data and near optimal accuracy on the real-life data. …”
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Implementation of trust region methods in optimization. (c1998)
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masterThesis -
10
Simultaneous stabilization of multimachine power systems viagenetic algorithms
Published 1999“…The problem of selecting the parameters of power system stabilizers which simultaneously stabilize this set of plants is converted to a simple optimization problem which is solved by a genetic algorithm with an eigenvalue-based objective function. …”
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Assigning proctors to exams using scatter search. (c2006)
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masterThesis -
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An Enhanced Approach for Solar PV Hosting Capacity Analysis in Distribution Networks
Published 2022“…These algorithms calculate the optimal HC based on six scenarios of annual load and DER generation profiles. …”
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DRL-Based IRS-Assisted Secure Hybrid Visible Light and mmWave Communications
Published 2024“…To address this complexity optimally, we propose a deep reinforcement learning (DRL) approach based on the deep deterministic policy gradient (DDPG) technique. …”
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Mobile Robot Navigation in Dynamic Environments Using an Improved RRT* Approach
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doctoralThesis -
17
Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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Impacts of On-Grid Solar PV on Distribution Networks and Potential Solutions: A Case Study in the Region of Zahle
Published 2025“…The siting and sizing methodology is conducted by considering five different optimization algorithms, namely the single-objective genetic algorithm (SOGA), the combined SOGA and loss sensitivity factor algorithm (SOGA-LSF), the multi-objective genetic algorithm (MOGA), the combined MOGA-LSF and the CAPADD algorithm of OpenDSS. …”
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masterThesis -
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Power system output feedback stabilizer design via geneticalgorithms
Published 1997“…A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. …”
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