Search Results - (( developing function method algorithm ) OR ( learning estimation learning algorithm ))
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Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm
Published 2023“…Backpropagation; Charging (batteries); Electric vehicles; Estimation; Ions; Knowledge acquisition; Learning algorithms; Lithium-ion batteries; Machine learning; Radial basis function networks; Back-propagation neural networks; Electric vehicle drive cycles; Extreme learning machine; Gravitational search algorithm (GSA); Gravitational search algorithms; Lithium ions; Radial basis function neural networks; State of charge; Battery management systems…”
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2
RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…By taking advantage of localized Gaussian basis function of RBF network, a decomposed version of learning method using finite difference (or derivative free) gradient estimate has been proposed in order to reduce memory requirement for the computation of the weight updates. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
4
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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5
Optimizing high-density aquaculture rotifer Detection using deep learning algorithm
Published 2022“…In this paper, we present the method and performance to detect rotifer Brachionus plicatilis in 1ml sample automatically using deep learning algorithm YOLOv3. …”
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Proceedings -
6
State of charge estimation for lithium-ion battery based on random forests technique with gravitational search algorithm
Published 2023“…Charging (batteries); Decision trees; Electric vehicles; Forestry; Ions; Learning algorithms; Lithium-ion batteries; Radial basis function networks; Gravitational search algorithm (GSA); Gravitational search algorithms; Radial basis function neural networks; Random forests; State of charge; State of charge estimations (SOC); State-of-charge estimation; Sustainable transportation systems; Battery management systems…”
Conference Paper -
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…This research aims to develop a scheme based on a feedforward neural network (FNN) with a vectorized algorithm (FNNVA) for solving FDEs in the Caputo sense (FDEsC) using selected first-order optimization techniques: simple gradient descent (GD), momentum method (MM), and adaptive moment estimation method (Adam). …”
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8
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”
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CMAC spectral subtraction for speech enhancement
Published 2001“…Thus the learning algorithm of CMAC can be integrated with the spectral subtraction method to produce a system that allows the noise estimate to be learned adaptively. …”
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Proceeding Paper -
10
State of Charge Estimation for Lithium-Ion Battery Using Recurrent NARX Neural Network Model Based Lighting Search Algorithm
Published 2023“…Backpropagation; Charging (batteries); Ions; Learning algorithms; Lighting; Lithium-ion batteries; Particle swarm optimization (PSO); Radial basis function networks; Back-propagation neural networks; Electrochemical reactions; NARX neural network; Non-linear autoregressive with exogenous; Radial basis function neural networks; Search Algorithms; State of charge; State-of-charge estimation; Battery management systems…”
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11
An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…Dynamic characterisations of one-dimensional flexible beam and two-dimensional flexible plate structures are presented and simulation algorithms characterising the behaviour of each structure is developed using finite difference methods. …”
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12
Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass
Published 2018“…The PSO algorithm suggested an optimum number of neurons in the hidden layer as 15 and a learning rate of 0.761 these consequently used to construct the ANN model. …”
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A hybrid technique of deep learning neural networks with finite difference method for higher order fractional Volterra-Fredholm integro-differential equations with φ-Caputo operato...
Published 2025“…This technique uses the Adaptive Moment Estimation Method (Adam) as an optimization algorithm with feed-forward deep learning to minimize the error function and training the model using five layers with different activation functions. …”
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14
Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…This learning algorithm represents an automatic generation of membership functions and rules from the data. …”
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15
Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…The aim of this paper is using an ensemble machine learning algorithm to develop a WAG incremental recovery factor predictive model that can be used by reservoir engineers to estimate WAG incremental recovery factor prior kick-off of laboratory experiments and comprehensive technical studies. …”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction
Published 2013“…The development sequence of such method can be divided into two parts: Developing network structure to employ complex fuzzy logic and proposing learning algorithm to train the system. …”
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17
SVM, ANN, and PSF modelling approaches for prediction of iron dust minimum ignition temperature (MIT) based on the synergistic effect of dispersion pressure and concentration
Published 2021“…The cubic kernel function was found suitable for training SVMs. Besides, a feed-forward artificial neural network with the backpropagation algorithm and a polynomial surface fit model have also been developed to predict the MIT. …”
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18
Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network
Published 2017“…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…To summarise, metaheuristic algorithms can give a superior optimization approach than the traditional artificial neural network method, providing the computing time is within an acceptable range. …”
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20
Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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