Search Results - (( based optimization learning algorithm ) OR ( evolution optimization problem algorithm ))
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1
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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2
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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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Metaheuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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4
Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations
Published 2014“…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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5
An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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6
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…However, WOA suffers from the same problem faced by many other optimization algorithms and tend to fall in local optima. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…Meta-heuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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8
Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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9
Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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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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11
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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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…The focus of this research is to explore the hybridization of nature-inspired computation methods for optimization of neural network-based cognition in video games, in this case the combination of a neural network with an evolutionary algorithm. …”
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An adaptive HMM based approach for improving e-Learning methods
Published 2023“…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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The exploration of hybrid metaheuristics-based approaches: A bibliometric analysis
Published 2025“…The rapid evolution of computational intelligence has driven significant interest in hybrid metaheuristics, which combine multiple optimization algorithms to solve complicated problems more efficiently. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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18
Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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19
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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20
Artificial intelligence (AI) and its application in architecture design: a thematic review
Published 2025“…The analysis identified six primary themes: 1) Architecture and Science, which includes research on complex systems, genetic algorithms, and machine learning;2) Architecture and Construction Management, including the development of frameworks that support decision making; architecture and interior design, which includes work on space-planning optimization and furniture and occupant arrangement;3) Architecture Interior Design; 4) Architecture and Urban; which encompasses attempts to develop tools to help design new cities; architectural engineering, where building performance analysis was the most-common AI application; 5) Architectural Engineering; and 6) Design Education and Training, in which AI appears most promising for advancing problem-based learning. …”
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