Search Results - (( evolution optimization learning algorithm ) OR ( problem implementation bees algorithm ))
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…Hybrid genetic algorithms are the combination of learning algorithms(Back propagation), usually working as evaluation functions, and genetic algorithms. …”
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Application of Bee Colony Optimization (BCO) in NP-Hard Problems
Published 2011“…P-Median problem will be used as the main case study in implementing one of the Bee-Inspired algorithms to prove, illustrate example and show the characteristics of the selected concept…”
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Final Year Project -
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Differential evolution for neural networks learning enhancement
Published 2008“…To overcome this problem, Differential Evolution (DE) has been used to determine optimal value for ANN parameters such as learning rate and momentum rate and also for weight optimization. …”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
Published 2023“…The Artificial Bee Colony (ABC) algorithm has gained widespread attention and has been applied in various fields due to its ability to achieve excellent global optimization results and ease of implementation. …”
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Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin
Published 2022“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation
Published 2019“…The Bees Algorithm is a population-based optimisation algorithm inspired by the food foraging behaviour of honey bees. …”
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An improved bees algorithm local search mechanism for numerical dataset
Published 2015“…Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. …”
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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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A true annealing approach to the marriage in honey-bees optimization algorithm
Published 2003“…The modified algorithm is tested using a group of randomly generated hard 3-SAT problems to compare its behavior and efficiency against previous implementations. …”
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Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin
Published 2021“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Student Project -
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Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Recently, an attractive bio-inspired method—namely the Artificial Bee Colony (ABC)—has shown outstanding performance with some typical computational algorithms in different complex problems. …”
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Dual optimization approach in discrete Hopfield neural network
Published 2024“…Therefore, this research contributes to the improvement of the learning and retrieval phases by integrating the Hybrid Differential Evolution Algorithm and Swarm Mutation respectively. …”
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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development
Published 2025“…This review uniquely focuses on harnessing the synergy between ML and computational modeling (CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction (HER) catalysts and various hydrogen production processes (HPPs). …”
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Minimizing power loss using modified artificial bee colony algorithm / Nur Azlin Ashiqin Mohd Amin ...[et al.]
Published 2021“…In this paper, the Modified Artificial Bee Colony (MABC) algorithm is implemented to solve the power system's optimal reactive power flow problem. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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