Search Results - (( parameter optimization system algorithm ) OR ( using evolutionary based algorithm ))
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…To address the optimization problem, the Evolutionary Mating Algorithm (EMA) is proposed. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…Firstly, an improved EM (IEM) algorithm is presented to estimate the five parameters of the single PV-module system. …”
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Implementation of PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator
Published 2018“…This signifies that, the PSO algorithm is very effective in optimizing the PID parameters.…”
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Decentralized Intelligent PID based controller tuned by Evolutionary Algorithm for Double Link Flexible Robotic Manipulator with Experimental Validation
Published 2018“…The controllers are incorporated with optimization algorithm that is PSO to find out the parameters of the PID controllers. …”
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Optimizing deep neuro-fuzzy classifier with a novel evolutionary arithmetic optimization algorithm
Published 2022“…Therefore, this study aims on improving the model's accuracy by proposing Arithmetic Optimization Algorithm. The outcomes using the Arithmetic Optimization Algorithm for feature selection have not only reduced the burden of implementing a huge dataset, but the Arithmetic Optimization-based deep neuro-fuzzy system has outperformed with 95.14 accuracy compared to the standard method with 94.52. …”
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Implementation and analysis of BBO algorithm for better damping of rotor oscillations of a synchronous machine
Published 2023Conference Paper -
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Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine
Published 2009“…This adds up to more nonlinearity of the system. In this paper the result of an attempt to develop a substitute nonlinear model based on multilayer neural network (MLNN) and evolutionary algorithm (EA) for a single-shaft gas turbine having IGVs and VSVs is presented. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…Based on the results, the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms. …”
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Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polyn...
Published 2016“…Hence, this research involves development of an adaptive mutation algorithm based multi-objective for Optimal Reactive Power Dispatch (ORPD) in a power system in order to minimize the total loss and the improved voltage stability simultaneously. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin
Published 2014“…This paper presents a Multi-Layer Feedforward Neural Network (MLFNN) for predicting the AC power output from a grid-connected photovoltaic (GCPV) system. In the proposed MLFNN, Firefly Algorithm (FA) was employed as the optimizer and search tools of the MLFNN training parameters. …”
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Multi-objective pareto ant colony system based algorithm for generator maintenance scheduling
Published 2022“…The proposed models and algorithm can be used to solve the multi-objective GMS problem while the new parameters’ values can be used to obtain optimal or near optimal maintenance scheduling of generators. …”
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Metaheuristic approach for optimizing neural networks parameters in battery state of charge estimation
Published 2023“…EMA is the recent evolutionary algorithm based on mating theory and environmental factor will be used in this paper to optimize the weights and biases of FNN on a common Li-ion battery, multiple data measurements, drive cycles and training repetitions. …”
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