Search Results - (( sequence optimization modified algorithm ) OR ( evolution classification based algorithm ))
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Operation sequencing using modified particle swarm optimization
Published 2007“…In this paper, modified particle swarm optimization (MPSO) has been used to generate a feasible operation sequence for a real world manufacturing problem. …”
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BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. …”
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Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain
Published 2020“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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Optimization of job scheduling in a machine shop using genetic algorithm
Published 2002“…A modified version of GA known as string GA has been used to get the near optimal cycle time for permutation analysis. …”
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Optimization of job scheduling in a machine shop using genetic algorithm
Published 2002“…A modified version of GA known as string GA has been used to get the near optimal cycle time for permutation analysis. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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The development of integrated planning and scheduling framework for dynamic and reactive environment of complex manufacturing problem
Published 2008“…Then, in Chapter 4, a modified particle swarm optimization (MPSO) has been used to generate a feasible operation sequence for a real world manufacturing problem. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…These fine-tuning techniques continue to be the object of ongoing research. Differential evolution (DE) is a simple yet powerful population-based metaheuristic. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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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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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…Hence, VLSI floorplanning is important in IC design. Floorplanning optimization consists of representation and optimization algorithm. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…The spectral features were performed by employing the relative spectral powers of delta (δRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The differential evolution-based channel selection algorithm (DEFS_Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. …”
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Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…A test suite of twelve benchmark test functions and three global optimization problems: Team Formation Optimization (TFO), Low Autocorrelation Binary Sequence (LABS), and Modified Condition/ Decision coverage (MC/DC) test case generation problem were solved using the proposed algorithm. …”
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Email spam classification based on deep learning methods: A review
Published 2025“…Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. …”
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