Search Results - feed-forward ((((evolution algorithm) OR (evolutionary algorithm))) OR (selection algorithm))
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
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Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…The proposed EC methods are Genetic Algorithm (GA), Differential Evolution (DE), Evolutionary Programming (EP), and Pareto-based Differential Evolution (PDE). …”
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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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Evolution strategies for evolving artificial neural networks in an arcade game
Published 2010“…The aim of this paper is to use a simple but powerful evolutionary algorithm called Evolution Strategies (ES) to evolve the connection weights and biases of feed-forward artificial neural networks (ANN) and to examine its learning ability through computational experiments in a non-deterministic and dynamic environment, which is the well-known arcade game called Ms. …”
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Forecasting solar power generation using evolutionary mating algorithm-deep neural networks
Published 2024“…This paper proposes an integration of recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) in optimizing the weights and biases of deep neural networks (DNN) for forecasting the solar power generation. …”
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Self-evaluation of RTS Troop's performance
Published 2015“…This paper demonstrates the research results obtained from a comparison of Evolutionary Programming (EP) and hybrid Differential Evolution (DE) and Feed Forward Neural Network (FFNN) algorithms in the Real Time Strategy (RTS) computer game, namely Warcraft III. …”
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Optimisation of neural network with simultaneous feature selection and network prunning using evolutionary algorithm
Published 2015“…Most advances on the Evolutionary Algorithm optimisation of Neural Network are on recurrent neural network using the NEAT optimisation method. …”
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Artificial Neural Controller Synthesis in Autonomous Mobile Cognition
Published 2009“…The Pareto-frontier Differential Evolution (PDE) algorithm is utilized to generate the Pareto optimal sets through a 3-layer feed-forward artificial neural network that optimize the conflicting objectives of robot behavior and network complexity, where the two different types of robot behaviors are phototaxis and RF-localization, respectively. …”
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
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Artificial Neural Controller Synthesis in Autonomous Mobile Cognition
Published 2009“…The Pareto-frontier Differential Evolution (PDE) algorithm is utilized to generate the Pareto optimal sets through a 3-layer feed-forward artificial neural network that optimize the conflicting objectives of robot behavior and network complexity, where the two different types of robot behaviors are phototaxis and RF-localization, respectively. …”
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Automatic generation of multi-objective neural game controllers using Pareto-based differential evolution
Published 2010“…For this research, three Evolutionary Algorithm (EA) (Genetic Algorithm (GA), Differential Evolution (DE), and POE) is use to evolve a Feed-Forward Artifitial Neural Networks (FFANN) to playa custom made map in Warcraft III and the outcome is compared amng them. …”
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Automating commercial video game development using computational intelligence
Published 2011“…Pac-man. The resulting algorithm is referred to as an Evolution Strategies Neural Network or ESNet. …”
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Automatic generation of Swarm Robotic behaviors using multi-objective evolution
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…ANN can be categorized into three main types: single layer, recurrent network and multilayer feed-forward network. In multilayer feed-forward ANN, the actual performance is highly dependent on the selection of architecture and training parameters. …”
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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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Evolutionary Multiobjective optimization for automatic generation Of Neural game controller
Published 2013“…This research presents the result of implementing evolutionary algorithms towards computational intelligence in Tower Defense game (TD game). …”
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…First, the best set of structures for feed forward neural network were found by multi objective parallel genetic algorithm. …”
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A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction
Published 2025“…The PSO adopts a unique random number selection strategy, incorporating the K-Nearest Neighbor (KNN) algorithm to reduce prediction errors. …”
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