Search Results - (( using computer learning algorithm ) OR ( a simulation optimization algorithm ))
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…The second proposed algorithm uses SA to optimize the terms selection while constructing a rule. …”
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Pressure vessel design simulation using hybrid harmony search algorithm
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the simulation result, by using these sensors information the AUTOWiSARD algorithm can successfully differentiate and classify states without supervision, while the Q-learning algorithm is able to produce and optimized states-actions policy. …”
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Revolutionizing crowd safety: A breakthrough hybrid whale-bat chaotic algorithm (WOABCM) for optimized evacuation simulations
Published 2024“…The Whale-Bat Chaotic Algorithm (WOABCM) is a revolutionary tool for optimizing pathfinding navigation in crowd evacuation scenarios. …”
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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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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…The simulation results of the MLP trained with improved algorithms were compared with that when trained with the standard BP, ABC, Global ABC and Particle Swarm Optimization algorithm. …”
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Enhancing simulated kalman filter algorithm using current optimum opposition-based learning
Published 2019“…Simulated Kalman filter (SKF) is a new population-based optimization algorithm inspired by estimation capability of Kalman filter. …”
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Fog-cloud scheduling simulator for reinforcement learning algorithms
Published 2023“…This study presents a developed simulator that captures all mentioned realistic scenarios by providing the feature of integrability with the reinforcement learning (RL) algorithm. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different�state-of-the-art algorithms. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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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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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…This paper presents a simulation study focused on optimizing user comfort and energy consumption in smart buildings. …”
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…This thesis presents a new approach to optimize the performance of a dual beam optical scanning system in terms of its scanning combinations and speed, using Genetic Algorithm (GA). …”
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Hybrid Henry Gas-Harris Hawks comprehensive-opposition algorithm for task scheduling in cloud computing
Published 2025“…Users can use online data computing services and computational resources from a distance in cloud computing environments. …”
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Memory efficient BFGS neural-network learning algorithms using MLP-network: a survey
Published 2004“…This paper surveys various implementation of a memory efficient second order (Broyden, Fletcher, Goldfard and Shanno) BFGS training algorithms which includes novel optimal memory (OM) BFGS neural network training algorithm, proposed by the present authors, which optimises performance in relation to available memory. …”
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An oppositional learning prediction operator for simulated kalman filter
Published 2018“…Simulated Kalman filter (SKF) is a recent metaheuristic optimization algorithm established in 2015. …”
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System identification using Extended Kalman Filter
Published 2017“…The EKF algorithm performance was compared with Recursive Least Square (RLS) estimation algorithm as a comparison algorithm performance. …”
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