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could algorithm » mould algorithm (Expand Search), carlo algorithm (Expand Search), colony algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
could algorithm » mould algorithm (Expand Search), carlo algorithm (Expand Search), colony algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
element » elements (Expand Search)
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…The mathematical design and methodology of the complete PV system were detailed in our prior research, titled "Dynamic and Adaptive Maximum Power Point Tracking Using Sequential Monte Carlo Algorithm for Photovoltaic System" by Odat et al. (2023) [1]. …”
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Holistic Design: Optimizing Mechatronic Systems Using Multi Objective Optimization
Published 2015Get full text
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ADAPTIVE ALGORITHMS FOR CHANNEL ESTIMATION: USING A PRIORI INFORMATION FOR OPTIMUM DESIGN
Published 2008Get full text
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Optimal multiobjective design of robust power system stabilizers using genetic algorithms
Published 2003“…Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. The overall cost function has been developed using fuzzy logic. …”
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Topology design of switched enterprise networks using a fuzzy simulated evolution algorithm
Published 2020“…In this paper, we present an approach based on Simulated Evolution algorithm for the design of SEN topology. The overall cost function has been developed using fuzzy logic. …”
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An incremental approach for test synthesis and scheduling using genetic algorithms. (c2002)
Published 2002Get full text
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Design of an innovative and self-adaptive-smart algorithm to investigate the structural integrity of a rail track using Rayleigh waves emitted and sensed by a fully non-contact laser transduction system
Published 2020“…A library of possible mother wavelets was designed based on the experimental data. As the inci dent wave for each sensing point varies because of the physical condition of the rail surface and the laser excitation, the algorithm automatically picks the mother wavelet from the library that generates the lar gest absolute cross-correlation with the incident wave. …”
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The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…Recent advances in algorithm design have shown a growing interest in seeking exact solutions to many hard problems. …”
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A modified ant colony algorithm for evolutionary design of digital circuits
Published 2003“…It is shown that the designed circuits using the proposed algorithm outperform those of the existing techniques.…”
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Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
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Thyristor controlled phase shifter based stabilizer design usingsimulated annealing algorithm
Published 1999“…This paper presents a thyristor controlled phase shifter (TCPS) based stabilizer design using the simulated annealing (SA) algorithm. …”
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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter
Published 2013Get full text
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”