Search Results - (( parameter identification using algorithm ) OR ( using function learning algorithm ))
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…It represents an interconnection among neuron which consists of several adjustable parameters which are tuned using a set of learning examples to obtain the desired function represent the actual system. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…In particular, the search capacity of the MVO algorithm has been improved using the sine and cosine functions of the Sine Cosine Algorithm (SCA) that will be able to balance the processes of exploration and exploitation. …”
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A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems
Published 2017“…The proposed algorithm benefits from the combination of extreme learning machine (ELM) and non-dominated sorting genetic algorithm (NSGAII) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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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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Damage identification using experimental modal analysis and adaptive neuro-fuzzy interface system (ANFIS)
Published 2012“…The adaptive neuro-fuzzy inference system (ANFIS) is a process for mapping from a given input to a single output using the fuzzy logic and neuro-adaptive learning algorithms. …”
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Conference or Workshop Item -
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Handgrip strength evaluation using neuro fuzzy approach
Published 2010“…Handgrip assessment is a useful method to monitor patient rehabilitation. The neurofuzzy analysis provides system identification and interpretability of fuzzy models and learning capability of neural networks. …”
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Fault classification in smart distribution network using support vector machine
Published 2023“…Gaussian radial basis function (RBF) kernel function has been used for training of SVM to accomplish the most optimized classifier. …”
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Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN. …”
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Development of damage identification scheme using de-noised modal frequency response function data with artificial neural network / Mohamad Izzudin Hussein Shah
Published 2018“…Multilayer Perceptron (MLP) with backpropagation learning algorithm ANN is used in this study. Moreover, this study needs to minimize the number of samples used by reducing number of sensors and frequency range used without affecting the performance accuracy. …”
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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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An optimized ensemble for predicting reservoir rock properties in petroleum industry
Published 2013“…A lot of researches have been done to predict the reservoir parameters using well log data through applying various methods. …”
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Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.]
Published 2014“…Back-propagation training algorithm and sigmoid transfer function were used to optimise the parameters in the training network. …”
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Book Section -
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An effective source number enumeration approach based on SEMD
Published 2022“…In signal processing, empirical mode decomposition (EMD) first decomposes the received single-channel signal into several intrinsic mode functions (IMFs) and a residual, and then uses machine learning methods for source number enumeration. …”
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Detection of sweetness level for fruits (watermelon) with machine learning
Published 2020“…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. …”
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New techniques incorporating computational intelligence based for voltage stability evaluation and improvement in power system / Nur Fadilah Ab. Aziz
Published 2014“…Another new hybrid algorithm that used Evolutionary Programming (EP) termed as Evolutionary Support Vector Machine (ESVM) was also developed for comparative study. …”
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