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1
A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
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2
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Two major difficulties in clustering ensemble include diversity of clustering and consensus functions. Genetic algorithms are well known methods with high ability to resolve optimization problems including clustering. …”
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3
Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering
Published 2024“…Particularly, swmcan addresses multi-view data noise using the l1-norm and optimizes the objective function through a novel iterative reweighted method. …”
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4
Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms can be used successfully in many applications requiring the optimization of a certain multi-dimensional function. …”
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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
RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…This thesis proposes derivative free learning, using finite difference, methods for fixed size RBF network in comparison to gradient based learning for the application of system identification. …”
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7
An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…The GD method not performed well in large scale applications and when higher learning performances are required. …”
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8
The effect of adaptive parameters on the performance of back propagation
Published 2012“…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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9
E-history Malaysian secondary school textbook using TF-IDF algorithm and text visualization / Nur Hafizah Mohd Ridzuan
Published 2020“…History is one of the school subjects in Malaysian schools and known as a compulsory subject that is required to pass the SPM examination. One of the main learning methods in Malaysian education is by using textbooks as it is a universal formal school learning material and a dominant resource of learning. …”
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10
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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11
Interpretation of machine learning model using medical record visual analytics
Published 2021“…The state of the art of medical application that being implemented are mostly based on common machine learning model. …”
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12
Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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13
Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification
Published 2024“…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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14
An approach to improve functional link neural network training using modified artificial bee colony for classification task
Published 2013“…The standard method for tuning the weight in FLNN is using a Backpropagation (BP) learning algorithm. …”
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15
Interpretation of machine learning model using medical record visual analytics
Published 2022“…The state of the art of medical application that being implemented are mostly based on common machine learning model. …”
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16
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
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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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18
Deep learning convolutional neural network algorithms for the early detection and diagnosis of dental caries on periapical radiographs: a systematic review
Published 2021“…Identifying caries with a deep convolutional neural network-based detector enables the operator to distinguish changes in the location and morphological features of dental caries lesions. Deep learning algorithms have broader and more profound layers and are continually being developed, remarkably enhancing their precision in detecting and segmenting objects. …”
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19
Deep Reinforcement Learning For Control
Published 2021“…In essence, the method is to use a reward-based learning environment to watch how the agent makes decisions. …”
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20
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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