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Statistical modeling of the electromechanical behaviour of BI-2223 composite wires
Published 2024text::Final Year Project -
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Multiobjective optimization using particle swarm optimization with non-Gaussian random generators
Published 2016“…The two non-Gaussian distributions are the Weibull and Gamma distributions. …”
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Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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Performance Improvement of Multiobjective Optimal Power Flow-Based Renewable Energy Sources Using Intelligent Algorithm
Published 2022“…Weibull and lognormal probability distribution functions (PDFs) are respectively adopted to describe uncertainties in wind speed and solar irradiance. …”
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A novel computer-aided multivariate water quality index
Published 2015“…Unlike other conventional indexing methods, the algorithm calculates the index in a multivariate manner. …”
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Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…Thus, in this thesis, a new Smart Energy Meter (SEM) with adaptive data transfer algorithm is designed to accommodate the problem. …”
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Particle swarm optimization-based model-free adaptive control for time-varying batch processes
Published 2024“…Further, considering that the adopted model-free adaptive control involves seven control parameters, such as cognitive scaling factor (φ1), social scaling factor (φ2), inertia weight (φ3), learning rate (η), control parameter update rate, exploration rate and learning rate for MFAC obtained by a particle swarm optimization (PSO) algorithm in combination with a criterion function performance index. …”
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Adaptive Neuro-Controller for three axes attitude control of innovative satellite
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