Search Results - (( parameter evaluation method algorithm ) OR ( using function machine algorithm ))
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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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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates
Published 2024“…The proposed algorithm is used to train the neural networks with di"erent hidden layer sizes and di"erent neurons. …”
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Enhancement of new smooth support vector machines for classification problems
Published 2011“…To obtain optimal accuracy results, Uniform Design method is used to select parameter. The performance of the method is evaluated using 10-fold cross validation accuracy, confusion matrix, sensitivity and specificity. …”
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5
RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…The proposed methods are tested using well known nonlinear benchmark problems and also evaluated for system with irregular sample time or known as lost packets. …”
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6
Handgrip strength evaluation using neuro fuzzy approach
Published 2010“…The expert rules define the membership function for the fuzzy system. The fuzzy model based on the membership function, fed in by the neural network will intelligently classify the data. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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Rainfall forecasting model using machine learning methods: Case study Terengganu, Malaysia
Published 2023Article -
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Prediction Of Petroleum Reservoir Properties Using Nonlinear Feature Selection And Ensembles Of Computational Intelligence Techniques
Published 2015“…Common metrics were used to evaluate the performance of the proposed models. …”
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Intelligent approach for processmodelling and optimization on electrical dischargemachining of polycrystalline diamond
Published 2020“…Subsequently, moth search algorithm (MSA) was used to determine the optimal machining parameters, such that the MRR was maximized and EWR was minimized. …”
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Intelligent approach for process modelling and optimization on electrical discharge machining of polycrystalline diamond
Published 2018“…Subsequently, moth search algorithm (MSA) was used to determine the optimal machining parameters, such that the MRR was maximized and EWR was minimized. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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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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17
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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18
Analysis On QOS Parameters To Predict Http Response
Published 2017“…Therefore, the real live world web service label data uses to evaluate the focus parameters using classification machine learning algorithms to process the data. …”
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Thesis -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The neural network methods use a number of heuristics to find appropriate parametric values. …”
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