Search Results - (( evolution optimization approach algorithm ) OR ( control optimization based algorithm ))
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1
Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution
Published 2014“…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
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2
Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica...
Published 2021“…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. …”
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3
Optimization of an extended H-infinity controller for unmanned helicopter control using multiobjective differential evolution (MODE)
Published 2015“…Then apply the MODE-based algorithm to optimize the weighting function of the control problem formulation for optimal performance. …”
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4
Control of an inverted pendulum using MODE-based optimized LQR controller
Published 2013“…Hence, a Multiobjective differential evolution algorithm is proposed to design an LQR controller with optimal compromise between the conflicting control objectives. …”
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5
Resource allocation in coordinated multipoint long term evolution-advanced networks
Published 2015“…ORA is formulated based on Lagrangian method and optimized using Particle Swarm Optimization (PSO). …”
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6
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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7
OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM
Published 2011“…Many tuning methods for PID controller have been developed, and one of them is based on natural evolution, the genetic algorithm (GA). …”
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8
A novel clustering based genetic algorithm for route optimization
Published 2016“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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Harmonic Elimination Pulse Width Modulation Using Differential Evolution Technique For Three Phase Voltage Source Inverter
Published 2018“…Differential Evolution (DE) has been gaining popularity among researchers as an effective yet simple evolutionary algorithm to solve the optimization problems. …”
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11
Differential evolution with improved sub-route reversal repair mechanism for multiobjective urban transit routing problem
Published 2018“…A population-based metaheuristic, namely, Differential Evolution (DE) algorithm is then proposed to handle the multiobjective UTRP with the aim of devising an efficient transit route network that optimizes both passengers' and operators' costs. …”
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A coevolutionary multiobjective evolutionary algorithm for game artificial intelligence
Published 2013“…The Pareto Archived Evolution Strategy (PAES) algorithm is used to generate a Pareto optimal set of ANNs that optimize the conflicting objectives of maximizing game scores and minimizing neural network complexity. …”
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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach
Published 2018“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”
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Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability
Published 2016“…A new approach of unified power flow controller (UPFC) optimal placement in the power system network based on dynamic analysis of voltage stability is presented in this paper. …”
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15
Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy
Published 2024“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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16
Grey wolf optimization and differential evolution-based maximum power point tracking controller for photovoltaic systems under partial shading conditions
Published 2022“…To track the global maximum peak power (GMPP) instead of local maxima peak power (LMPP), the combination of gray wolf optimization (GWO) and differential evolution (DE) algorithm is hybridized (GWO-DE) in this work. …”
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Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach
Published 2023“…GP is a meta-heuristic search and optimization technique based on natural evolution. The control and optimization parameters in this study are tuned. …”
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Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The second scheme is cell selection based on multiple criteria decision making (MCDM) approach. …”
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Artificial Neural Controller Synthesis in Autonomous Mobile Cognition
Published 2009“…This paper describes a new approach in using multi-objective evolutionary algorithms in evolving the neural network that acts as a controller for the phototaxis and radio frequency localization behaviors of a virtual Khepera robot simulated in a 3D, physics-based environment. …”
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Automatic generation of Swarm Robotic behaviors using multi-objective evolution
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Working Paper
