Search Results - (( evolution optimization using algorithm ) OR ( using selection methods algorithm ))
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1
Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
Published 2014“…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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2
Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity
Published 2018“…The proposed algorithm is capable of selecting the optimal feature subsets while improving the recognition of acceleration activity using a minimum number of features. …”
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3
A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
Published 2019“…To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
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4
Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…The experiment results show how these algorithms could be used to improve methods for recognizing human activities using wearables technology, such as feature selection, parameter adjustment, and model optimization.…”
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The standard DE algorithm is known as a fixed length optimizer, while our problem demands the need for methods that aren’t tolerated to a fixed individual size, and that was made by altering the mutation and crossover strategies as well as the selection operation. …”
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6
Multiobjective design optimization of a nano-CMOS voltage-controlled oscillator using game theoretic-differential evolution
Published 2015“…The weighted sum scalarization approach was employed in this work in conjunction with three metaheuristic algorithms: particle swarm optimization (PSO), differential evolution (DE) and the improved DE algorithm (GTDE) (which was enhanced using ideas from evolutionary game theory). …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution
Published 2019“…Then, the optimized fractional-slot Permanent Magnet Synchronous Machine (PMSM) performance is validated using the 2-D Finite Element Method (FEM). …”
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9
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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10
Application Of Genetic Algorithms For Robust Parameter Optimization
Published 2010“…Genetic algorithms (GA) are fairly recent in this respect but afford a novel method of parameter optimization. …”
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Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks
Published 2014“…The conventional cell selection in LTE uses S-criterion only, which is inefficient. …”
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12
Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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14
Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…After determine the rates another single objectives algorithm is tested. Hence, the second sub-objective is 2) to evolve RTS controllers using DE and FFNN. …”
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15
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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16
Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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17
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The third method is the hybridization of BPSO and Binary Differential Evolution, namely Binary Particle Swarm Optimization Differential Evolution (BPSODE). …”
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18
Dynamic smart grid communication parameters based cognitive radio network
Published 2023“…A differential evolution algorithm is used to select the optimal transmission parameters for given communication modes based on a fitness function that combines multiple objectives based on appropriate weights. …”
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EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization
Published 2019“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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Omega grey wolf optimizer (ωGWO) for optimization of overcurrent relays coordination with distributed generation
Published 2019“…Comparative studies have been performed in between GWO and the other well-known methods such as Differential Evolution (DE), Particle Swarm Optimizer (PSO) and Biogeographybased Optimizer (BBO), to demonstrate the efficiency of the GWO. …”
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