Search Results - (( data relational learning algorithm ) OR ( parameter optimization method algorithm ))
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
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3
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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4
Optimization of ANFIS with GA and PSO estimating α ratio in driven piles
Published 2020“…This study aimed to optimize Adaptive Neuro-Fuzzy Inferences System (ANFIS) with two optimization algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for the calculation friction capacity ratio (α) in driven shafts. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. …”
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…The WNMPC is developed by a proposed algorithm named adaptive updating rule (AUR) used with gradient descent optimization method to minimize a constrained cost function over the prediction and control horizons and to offer a robust control performances. …”
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Affect classification using genetic-optimized ensembles of fuzzy ARTMAPs
Published 2015“…Speciation was implemented using subset selection of classification data attributes, as well as using an island model genetic algorithms method. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
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An optimized ensemble for predicting reservoir rock properties in petroleum industry
Published 2013“…In the present thesis, we proposed a new method named optimized ensembleto improve the prediction of these reservoirs parameters from well log data with the aid of available core data. …”
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11
Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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Enhancing reservoir simulation models with genetic algorithm optimized neural networks across diverse climatic zones / Saad Mawlood Saab
Published 2025“…The research improved the predictive models by integrating them with the Genetic Algorithm (GA). The optimizer algorithm (i.e., GA) determines the optimal input variables and internal parameters in the prediction models. …”
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Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.]
Published 2023“…The algorithm is trained, tested, and verified with the experiment data. …”
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Wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning
Published 2023“…In this aspect, this study develops a new wearables-assisted smart health monitoring for sleep quality prediction using optimal deep learning (WSHMSQP-ODL) model. The presented WSHMSQP-ODL technique initially enables the wearables to gather sleep-activity-related data. …”
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15
Modeling of road geometry and traffic accidents by hierarchical object-based and deep learning methods using laser scanning data
Published 2018“…Experimental results regarding road geometry extraction indicated that the proposed methods could achieve relatively high accuracy (~ 85% - User’s Accuracy) of road detection from airborne laser scanning data. …”
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Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…Nowadays there are many related efforts in detecting spliced images, but most of them are either feature-specific or complicated algorithms. …”
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Experimental and AI-driven enhancements in gas-phase photocatalytic CO2 conversion over synthesized highly ordered anodic TiO2 nanotubes
Published 2025“…The highest prediction achieved for the photoconversion of CO2 was 71.32 %, while experimental validation confirmed an effectiveness of 70.60 % under optimized conditions. The SHapley Additive exPlanations (SHAP) method and normalized importance showed that the parameters related to photocatalysts were the most influential features in enhancing the gas-phase CO2 photoconversion compared to parameters related to photocatalytic settings. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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19
Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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