Search Results - (( pattern classification parallel algorithm ) OR ( program validation learning algorithm ))
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EMG motion pattern classification through design and optimization of neural network
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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Proceeding Paper -
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EMG motion pattern classification through design and optimization of Neural Network
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Working Paper -
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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Article -
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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Thesis -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Thesis -
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Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors
Published 2016“…In recent years, finger vein recognition has emerged as a promising biometric technology due to the fact that each person in this world has unique finger vein pattern. Over the past few years, various finger vein recognition algorithms and techniques have been proposed by researchers and scholars. …”
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Case Slicing Technique for Feature Selection
Published 2004“…The classification accuracy obtained from the CST method is compared to other selected classification methods such as Value Difference Metric (VDM), Pre-Category Feature Importance (PCF), Cross-Category Feature Importance (CCF), Instance-Based Algorithm (IB4), Decision Tree Algorithms such as Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5), Rough Set methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) and Neural Network methods such as the Multilayer method.…”
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Thesis -
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A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…The results obtained from the resulting rollout policy with CPLEX execution during rollout are also presented to validate the reduced model and the matheuristic algorithm. …”
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System identification using Extended Kalman Filter
Published 2017“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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Student Project -
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Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN)
Published 2011“…ANNs are particularly useful for complex pattern recognition and classification tasks. The capability of learning from examples, the ability to reproduce arbitrary non-linear functions of input, and the highly parallel and regular structure of ANNs make them especially suitable for pattern recognition tasks. …”
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Proceeding Paper -
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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Thesis -
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…This is believed to be due to the different approaches of both classifiers in capturing data pattern for classification. In terms of computational time, compared to GS-tuned models and the respective HS hybrids, the proposed hybrid MHS-SVM and MHS-RF have reported time improvement of more than 50%, while the parallel computation have saved up approximately 80% of the computational time. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Predicting Student Performance in Object Oriented Programming Using Decision Tree : A Case at Kolej Poly-Tech Mara, Kuantan
Published 2013“…Using 10-fold cross validation for each algorithm, it was found that decision tree was the best algorithm with 83.6944% correctness. …”
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Conference or Workshop Item -
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Current applications of machine learning in dentistry
Published 2022“…The process is similar to a human expert that can learn by repeated training (Hung et al., 2019). The quality of the output depends on the quality of data used to train and validate the algorithm (Rowe, 2019). …”
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Book Chapter -
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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Thesis -
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Construction Noise Prediction Using Stochastic Deep Learning
Published 2022“…The programming algorithm of stochastic modelling was executed in MATLAB, whereas the deep learning model was established by using Python 3.6 programming language in Spyder. …”
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Final Year Project / Dissertation / Thesis
