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61
Metaheuristic algorithm for testing web 2.0 applications. (c2012)
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masterThesis -
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A Stochastic Newton-Raphson Method with Noisy Function Measurements
Published 2016“…The development of the proposed optimal algorithm is based on minimizing a stochastic performance index. …”
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A fuzzy basis function network for generator excitation control
Published 1997“…A fuzzy basis function network (FBFN) based power system stabilizer (PSS) is presented in this paper. …”
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65
Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem
Published 2023“…In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. …”
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66
Wild Blueberry Harvesting Losses Predicted with Selective Machine Learning Algorithms
Published 2022“…For the purpose of predicting ground loss as a function of fruit zone, plant height, fruit production, slope, leaf loss, and blower damage, three ML models i.e., support vector regression (SVR), linear regression (LR), and random forest (RF)—were used. …”
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Accuracy of an internationally validated genetic-guided warfarin dosing algorithm compared to a clinical algorithm in an Arab population
Published 2024“…To compare the accuracy of a clinical warfarin dosing (CWD) versus genetic warfarin dosing algorithms (GWD) during warfarin initiation. …”
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70
An efficient failure-resilient mutual exclusion algorithm for distributed systems leveraging a novel zero-message overlay structure
Published 2024“…<p>In this paper, we provide a novel failure-resilient token-based mutual exclusion (ME) algorithm for distributed systems. …”
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71
A Quasi-Oppositional Method for Output Tracking Control by Swarm-Based MPID Controller on AC/HVDC Interconnected Systems With Virtual Inertia Emulation
Published 2021“…<p>This paper presents a comprehensive evaluation of the effect of quasi oppositional - based learning method utilization in output tracking control through a swarm-based multivariable Proportional-Integral-Derivative (SMPID) controller, which is tuned by a novel performance index based on the step response characteristics in multi-input multi-output (MIMO) system. …”
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A deterministic heuristic algorithm for optimal multiprocessor scheduling. (c1995)
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masterThesis -
74
Optimal multiobjective design of robust power system stabilizers using genetic algorithms
Published 2003“…The problem of robustly selecting the parameters of the power system stabilizers is converted to an optimization problem which is solved by a genetic algorithm with the eigenvalue-based multiobjective function. …”
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75
New Fast Arctangent Approximation Algorithm for Generic Real-Time Embedded Applications
Published 2019“…The new algorithm exploits the pseudo-linear region around the tangent function zero point to estimate a reduced input arctangent through a modified rational approximation before referring this estimate to its original value using miniature LUTs. …”
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Radial basis function networks for contingency analysis of bulkpower systems
Published 1999“…The performance of the RBFN is compared with a standard AC load flow algorithm…”
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77
New fault models and efficient BIST algorithms for dual-portmemories
Published 1997“…The testability problem of dual-port memories is investigated. A functional model is defined, and architectural modifications to enhance the testability of such chips are described. …”
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78
Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization
Published 2022“…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…This paper introduces a novel multi-trial vector-based sine cosine algorithm (MTV-SCA) for the identification of seven unknown parameters of PEMFCs. …”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…Grasshopper optimization algorithm (GOA) is a fresh population based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature, which has good convergence ability towards optima. …”