Search Results - (( parameter evaluation method algorithm ) OR ( based difference learning algorithm ))
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…In other words, in order to get a good result, the BPNN learning algorithm needs to be executed several times with different topology structures and parameter values in order to determine the best set of parameter values used in the BPNN. …”
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Thesis -
2
Autism Spectrum Disorder Classification Using Deep Learning
Published 2021“…In the future, different types of deep learning algorithms need to be applied, and different datasets can be tested with different hyper-parameters to produce more accurate ASD classifications.…”
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Article -
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. …”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market
Published 2024“…By setting the ML algorithms and their parameter along with using Walk-Forward Analysis (WFA) method, the algorithm design of trading signal was evaluated based on two groups of evaluation indicators, namely directional and performance. …”
thesis::master thesis -
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…However, different clustering algorithms have different parameters that need to be specified. …”
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Book Chapter -
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Information Theoretic-based Feature Selection for Machine Learning
Published 2018“…Moreover, the third test used ten natural domain datasets obtained from UCI Repository, in about fifteen different experiments, using three to four different Machine Learning Algorithms for performance evaluation. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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Conference or Workshop Item -
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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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Malaysian Daily Stock Prediction Analysis Using Supervised Learning Algorithms
Published 2024Article -
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…In this paper, a new method is designed to effectively determine the parameters of proton exchange membrane fuel cells (PEMFCs), i.e., ?…”
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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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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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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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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission
Published 2023“…Three different ensemble learning methods namely, XGboost, LightGBM, and CatBoost were chosen to predict damages and AE parameters. …”
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Article -
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The NPO was tested and evaluated based on sixty unconstrained benchmark test functions. …”
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Thesis -
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