Search Results - (( evolution evaluation study algorithm ) OR ( program implementation drops algorithm ))
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Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm
Published 2013“…A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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A comprehensive comparison of evolutionary optimization limited by number of evaluations against time constraints
Published 2016“…Practically allevolutionary optimization studies have focused exclusively on the use of number of fitness evaluations as the constraining factor when comparing different evolutionary algorithms (EAs). …”
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Hybrid differential evolution-particle swarm optimization algorithm for multi objective urban transit network design problem with homogeneous buses
Published 2019“…The computational results of the proposed hybrid algorithm improve over the benchmark obtained in most of the previous studies. …”
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Experimental implementation controlled SPWM inverter based harmony search algorithm
Published 2023Article -
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On fractional and semi-soft handover in long term evolution(LTE) networks
Published 2011“…In this paper a hybrid HO algorithms called semi-soft handover (SSHO) and fractional soft handover (FSHO) in long term evolution (LTE) system are studied. …”
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…The Genetic Algorithm is an area in the field of Artificial Intelligence that is founded on the principles of biological evolution. …”
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A time-critical investigation of parameter tuning in differential evolution for non-linear global optimization
Published 2016“…In a previous study, Differential Evolution (DE) has been found as one of the best performing algorithms under time constraints. …”
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Effects of Authentication of Users in Mobile Internet Protocol Version 6
Published 2004“…Comparisons are done between systems implementing authentication and those that do not. The results show that the average delay is not much affected by the implementation of the program. …”
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Evolution of RF-signal cognition for wheeled mobile robots using pareto multi-objective optimization
Published 2009“…The elitist Pareto-frontier Differential Evolution (PDE) algorithm is used to generate the Pareto optimal set of ANNs that could optimize two objectives in a single run; (1) maximize the mobile robot homing behavior whilst (2) minimize the hidden neurons involved in the feed-forward ANN. …”
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An enhanced metaheuristic approach to solve quadratic assignment problem using hybrid technique
Published 2021“…The objectives of this study are to employ the best crossover operator in the Discrete Differential Evolution (DDE) algorithm. …”
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Performance analysis of uplink scheduling algorithms in the urban and rural environments in LTE / Shafinaz Ismail, Darmawaty Mohd Ali and Norsuzlia Ya'acob
Published 2018“…Long Term Evolution (LTE) is the evolution of an existing 3G mobile network towards a higher capacity, a lower latency and a more efficient core network and radio access. …”
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Empirical Evaluation of Mutation Step Size in Automated Evolution of Non-Target-Based 3D Printable Objects
Published 2015“…The focus of this study is to explore the mutation step size in hoping to create more diverse populations in the evolution of the generated 3D printable objects. …”
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A competitive co-evolutionary approach for the nurse scheduling problem
Published 2026“…This study proposes a competitive co-evolutionary algorithm for the NSP that introduces adaptive adversarial evaluation, where candidate schedules are assessed under dynamic competitive pressure to expose structural weaknesses and guide evolution more effectively. …”
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