Search Results - (( variable training based algorithm ) OR ( changes optimization based algorithm ))
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…In preprocessing of optimization, modeFrontier Response Surface Method (RSM) is able to model the behavior of engine performances corresponding to the change of design variables.…”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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Fault Detection Relevant, Neural Network and Evolutionary Algorithm based Model for a Single-shaft Industrial Gas Turbine
Published 2009“…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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Design of Optimal Pitch Controller for Wind Turbines Based on Back-Propagation Neural Network
Published 2024“…The model is simulated in MATLAB 2019b, real-time data are observed, and the control effect is compared with that of a Takagi–Sugeno optimal controller, firefly algorithm optimal controller and fuzzy controller. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail
Published 2015“…An intelligent predictive model will replace the lengthy procedures by predicting the properties using known fiberboard characteristics. Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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Flash floods prediction using real time data: an implementation of ANN-PSO with less false alarm
Published 2019“…Approaches for the early prediction of flash floods and hurricanes may be categorized as (a) Modeling of the system (bathymetry), (b) Sensors and gauges-based measurement, (c) Radar-based images, (d) Satellite images and data, and (e) AI-based prediction. …”
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Proceeding Paper -
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…A comparison between one variable at a time, Taguchi method and artificial neural network shows that both Taguchi and ANN can reduce the amount of enzyme, amount of molecular sieve, reaction time and molar ratio in solvent based and solvent free system. …”
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Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics
Published 2021“…The statistical analysis presented in this study incorporated one of the best regression models algorithms based on machine learning approach to study the adsorption variation with shale fabric this study. …”
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A hybrid chromaticity-morphological machine learning model to overcome the limit of detecting newcastle disease in experimentally infected chicken within 36 h
Published 2025“…These findings highlight the importance of extracting chromaticity features in predicting infected chicken, especially at the early phase of infection. Based on the HCMML models result, SVM with Polynomial kernel achieved a test accuracy of 82·39 % with 79·00 % validation accuracy at 36 h post-infection after feature optimization and > 95·00 % test accuracy after 96 h post-infection. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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Optimized PID controller of DC-DC buck converter based on archimedes optimization algorithm
Published 2023“…The proposed PID controller, optimized using AOA, is contrasted with PID controllers tuned via alternative algorithms including the hybrid Nelder-Mead method (AEONM), artificial ecosystem-based optimization (AEO), differential evolution (DE), and particle swarm optimizer (PSO). …”
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Adaptable algorithms for performance optimization of dynamic batch manufacturing processes
Published 2018“…Central to precision manufacturing is artificial intelligence as this thesis presents the performance characteristics of tuning-based, rule-based, learning-based and evolutionary-based algorithms. …”
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AN ENSEMBLE APPROACH OF METAHEURISTIC ALGORITHMS WITH PARABOLIC APPROXIMATION TO OPTIMIZE WELL PLACEMENT PROBLEM
Published 2021“…However, the ensemble algorithm often changes search strategies and adds an algorithm based on their success, which makes it more reliable on multimodal optimization problems. …”
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Exponentially adaptive sine-cosine algorithm for global optimization
Published 2019“…Sine-Cosine algorithm (SCA) is an optimization algorithm formulated based on mathematical Sine and Cosine terms. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks
Published 2015“…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Optimal operation of hydropower reservoirs under climate change
Published 2024“…The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. …”
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