Search Results - (( based learning algorithm ) OR ( pattern ((research algorithm) OR (bees algorithm)) ))
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Artificial neural networks based optimization techniques: A review
Published 2023“…In this paper, we present an extensive review of artificial neural networks (ANNs) based optimization algorithm techniques with some of the famous optimization techniques, e.g., genetic algorithm (GA), particle swarm optimization (PSO), artificial bee colony (ABC), and backtracking search algorithm (BSA) and some modern developed techniques, e.g., the lightning search algorithm (LSA) and whale optimization algorithm (WOA), and many more. …”
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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…The Artificial Neural Networks Training (ANNT) process is an optimization problem of the weight set which has inspired researchers for a long time. By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Monograph -
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach
Published 2009“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition
Published 2016“…This research is mainly focused on creating a new algorithm based on classification technique to calculate food calorie intake in real-time. …”
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Conference or Workshop Item -
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Book Section -
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Web usage mining for UUM learning care using association rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Firstly is by enhancing the learning algorithm of a neural-fuzzy network; and secondly by devising an ensemble model to combine the predictions from multiple neural-fuzzy networks using an agent-based framework. …”
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Grid base classifier in comparison to nonparametric methods in multiclass classification
Published 2010“…The two algorithms were compared, and the proposed algorithm was found to be able to both learn and classify quickly. …”
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The development of an automated pattern recognition based on neural network / Irni Hamiza Hamzah, Mohammad Nizam Ibrahim and Linda Mohd Kasim
Published 2006“…The selected neural network architecture is the Multilayer Perceptron (MLP) network, which is trained with three different types of learning algorithms, namely the Levenberg Marquardt (LM), Bayesian Regression (BR) and Gradient Descent (GDX). …”
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Research Reports -
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EEG-based emotion recognition using machine learning algorithms
Published 2024“…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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Final Year Project / Dissertation / Thesis -
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Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. …”
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Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…In this research, a vision system algorithm has been developed to identify and locate base of young corn trees based upon robot vision technology, pattern recognition techniques, and knowledge-based decision theory. …”
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Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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Analyzing enrolment patterns: Stacked ensemble statistical learning-based approach to educational decision making
Published 2023“…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel stacked ensemble machine learning algorithm based on these determinants, following the CRISP-DM data science methodology. …”
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