Search Results - (( using function method algorithm ) OR ( parameter adapting learning algorithm ))
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1
The effect of adaptive parameters on the performance of back propagation
Published 2012“…The activation functions are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. …”
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2
Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
Published 2024“…Selected datasets are used to evaluate the performance of the proposed method. …”
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3
Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”
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4
Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…Moreover, the ability of initialization the hidden nodes parameters using density function and recursive algorithm will help WN-OSELM to perform useful generalization facility and modeling accuracy. …”
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5
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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6
Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…Conventionally back-propagation learning algorithm also termed as (BP-MLP) is used. …”
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7
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
8
A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm
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9
Modified anfis architecture with less computational complexities for classification problems
Published 2018“…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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10
A genetically trained adaptive neuro-fuzzy inference system network utilized as a proportional-integral-derivative-like feedback controller for non-linear systems.
Published 2009“…The GA, with real-coding operators, is used to adjust all of the ANFIS parameters, which include the input and output scaling factors, the centres and widths of the input membership functions (MFs), and the consequent parameters. …”
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11
Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction
Published 2013“…The second experiment used proposed method to model a three input nonlinear function. …”
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12
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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13
Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…The ADAM optimizer effectively tackles challenges in continuous parameter optimization by dynamically updating the model's weights and biases, adapting the learning rate for each parameter based on accumulated historical gradient information to achieve more efficient minimization of the loss function during training. …”
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14
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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15
Damage identification using experimental modal analysis and adaptive neuro-fuzzy interface system (ANFIS)
Published 2012“…Using a given input-output data set, ANFIS constructs a Fuzzy Inference System (FIS) whose fuzzy membership function parameters are adjusted using combination of back propagation algorithm with a least square type of method. …”
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16
Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…There have two most uses activation function namely tansig and logsig. …”
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17
SYSTEMATIC DESIGN OF SIMPLY STRUCTURED COMPENSATOR
Published 2005“…This project aims to develop the algorithm for the tuning method that based on Nyquist Stability Criterion and at later stage build a Neural Network Model to predict the tuning parameters for the PID controller. …”
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18
Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…This research proposed an algorithm for improving the current working performance of Back-propagation algorithm by adaptively changing the momentum value and at the same time keeping the ‘gain’ parameter fixed for all nodes in the neural network. …”
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19
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The developed TSK type fuzzy inference engine is called modified adaptive fuzzy inference engine (MAFIE) and its parameters were then adjusted by the hybrid learning algorithm using adaptive neural network architecture towards improved performance which is called MANFIE. …”
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