Search Results - (( using optimization learning algorithm ) OR ( using evolutionary process algorithm ))
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Towards Software Product Lines Optimization Using Evolutionary Algorithms
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement
Published 2025“…SGA is used in the process of solving optimization test problems by neural networks. …”
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Optimized processing of satellite signal via evolutionary search algorithm
Published 2000“…Using a different initial point, all of them produced the correct results …”
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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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Conference or Workshop Item -
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Metaheuristic algorithms for feature selection (2014–2024)
Published 2025“…Over the last decade (2014–2024), numerous approaches have been explored, each with its own optimization strengths and constraints. Swarm intelligence and evolutionary algorithms—including genetic algorithms, particle swarm optimization, and the zebra optimization algorithm—have operated effectively in this area. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Thesis -
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
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Operating a reservoir system based on the shark machine learning algorithm
Published 2018“…In the current study, the shark machine learning algorithm (SMLA) is proposed to develop an optimal rule for operating the reservoir. …”
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Article -
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Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…The IHS-GWO is evaluated using two standard benchmarking sets and two real-world optimization problems. …”
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Thesis -
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
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An evolutionary based features construction methods for data summarization approach
Published 2015“…A data summarization approach is proposed due to its capability to learn data stored in multiple tables. In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). …”
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Research Report -
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Advances in metaheuristics: Applications in engineering systems
Published 2016“…With this book, readers can learn to solve real-world engineering optimization problems effectively using the appropriate techniques from emerging fields including evolutionary and swarm intelligence, mathematical programming, and multi-objective optimization. …”
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Book -
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Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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Multi-Objective Multi-Exemplar Particle Swarm Optimization Algorithm with Local Awareness
Published 2024“…Multi-Objective Optimization (MOO) algorithms play a crucial role in this process by enabling them to navigate these trade-offs effectively. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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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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Evolutionary-based feature construction with substitution for data summarization using DARA
Published 2012“…This is performed in order to exploit all possible interactions among attributes which involves an application of genetic algorithm to find a relevant set of features. The constructed features will be used to generate relevant patterns that characterize non-target records associated to the target record as an input representation for data summarization process. …”
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