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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
Published 2015“…Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Efficient beamforming and spectral efficiency maximization in a joint transmission LTE-A system
Published 2016“…Moreover, addressing the lack-of-diversity issue in Basic Particle Swarm Optimization Algorithm (BPSOA) is a primary concern of this work. …”
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Tasks Distribution In Driver Scheduling Using Dynamic Set Of Bandwidth In Harmony Search Algorithm With 2-Opt
Published 2021“…The existing techniques (HS and its variants) have issues in terms of searching strategy (exploration and exploitation), slow convergence rate and high computation time for solving the scheduling problems maximally or near to optimal one. …”
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Exploring dynamic self-adaptive populations in differential evolution
Published 2006“…In this paper, we present a first attempt at self-adapting the population size parameter in addition to self-adapting crossover and mutation rates. …”
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…,e results show that the rate of convergence of the Adam algorithm is significantly enhanced by using the AdamSE algorithm. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
Published 2024“…The process of training neural networks heavily involves solving optimization problems. Most optimization algorithms use a !…”
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Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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Proceedings -
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…These results show that,for all the arrays (2D and 3D) except 3D pole - dipole data, resilient propagation is the most efficient algorithm for training the DC resistivity data. In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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An algorithm for the selection of planting lining technique towards optimizing land area: an algorithm for planting lining technique selection
Published 2012“…The three techniques with different planting lining direction lead to different number of trees, therefore the technique promotes the highest number of tree is optimal technique. …”
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…The Emperor Penguin Optimizer (EPO) is a recently developed population-based metaheuristic algorithm that simulates the huddling behaviour of emperor penguins. …”
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An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem
Published 2022“…To alleviate these problems, an adaptive mechanism can be introduced in EPO. This paper proposes a fuzzy adaptive variant of EPO, namely Fuzzy Adaptive Emperor Penguin Optimizer (FAEPO), to solve this problem. …”
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Particle swarm optimization (PSO) for CNC route problem
Published 2002“…The algorithm used in this project is the Global Best (gbest) algorithm where it is a basic algorithm of Particle Swarm Optimization which applicable the shortest time and path of CNC machine to complete the process of drilling. …”
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Undergraduates Project Papers -
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Attack path selection optimization with adaptive genetic algorithms
Published 2016“…We describe our approach for implementing an optimized security assessment using Genetic Algorithm (GA). …”
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Attack path selection optimization with adaptive genetic algorithms
Published 2016“…We describe our approach for implementing an optimized security assessment using Genetic Algorithm (GA). …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…Particle swarm optimization (PSO) is a population-based metaheuristic optimization algorithm that solves a problem through iterative operations. …”
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