Search Results - (( using evolution method algorithm ) OR ( problem implementation using algorithm ))
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A New Hybrid Approach Based On Discrete Differential Evolution Algorithm To Enhancement Solutions Of Quadratic Assignment Problem
Published 2020“…Even though the use of several mathematical formulations is employed for FLP, Quadratic Assignment Problem (QAP) is one of the most commonly used. …”
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2
Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity
Published 2018“…Consequently, this paper proposes a ranking self-adaptive differential evolution (rsaDE) feature selection algorithm. 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
Sub-route reversal repair mechanism and differential evolution for urban transit network design problem
Published 2017“…From the literature of UTNDP, the most widely used metaheuristic is the genetic algorithm, at the expense of other population-based metaheuristics. …”
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Thesis -
4
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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5
Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES)
Published 2022“…The natural evolution optimization algorithm which is genetic algorithm can be improve by combining the nature meta-heuristic algorithms which is bald eagle search to improve the makespan of genetic algorithm using cloudsim that need to be implement on the eclipse platform. …”
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Academic Exercise -
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Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This will involve the explanation of the use of evolution algorithms combined with the music programming to be able to create creative digital music.…”
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Final Year Project / Dissertation / Thesis -
7
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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8
An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin
Published 2013“…Genetic Algorithms (GA) which is based on biological evolution is one of the metaheuristics that has been successfully applied to JSSP. …”
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11
A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation
Published 2019“…First, three different optimization algorithms, namely particle swarm optimization, differential evolution, and whale optimization algorithm, have been applied. …”
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POISSON EQUATION FOR ELECTROSTATIC FIELD USING THE FINITE DIFFERENCE METHOD
Published 2019“…This problem will be solved via matrix and successive over relation to get a good solution for the implementation result.…”
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Final Year Project Report / IMRAD -
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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14
Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
Published 2012“…Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN. …”
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A modified group authentication scheme for machine type communication in LTE/LTE-a networks
Published 2018“…Meeting the necessities of control usage of devices and mass implement transmission is a key issue in the implementation of MTC in the Long Term Evolution/Long Term Evolution Advanced systems. …”
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A novel high performance routing technique for cross-referencing DMFBs
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Working Paper -
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A hybrid optimization technique for solving economic emission load dispatch problems
Published 2023text::Final Year Project -
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Restoration of old malay jawi manuscripts using mumford-shah and bertalmio inpainting models / Nurul Nabilah Zainal, Nur Fatini Mohammad Yuri and Abdul Kadir Jumaat
Published 2022“…This indicates that the Mumford-Shah inpainting model is more effective than Bertalmio inpainting model. The algorithms used in this study can be upgraded to a software framework for commercial use and can be implemented for other kinds of digitized data.…”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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