Search Results - (( between learning algorithm ) OR ( between three algorithm ))
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Development of learning algorithm of passive joint for 3R under-actuated robot / Mohd Amiruddin Fikri Yaakob
Published 2015“…Two different techniques were tested using three rotations (3R) under-actuated robot manipulator. …”
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Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
Published 2019“…We believed that the survey can facilitate synergy between the nature inspired algorithms and deep learning research communities. …”
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Proceeding Paper -
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Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023)
Published 2025“…The synergy between deep learning and meta-heuristic algorithms presents a promising avenue for tackling the complexities of energy-related modeling and forecasting tasks. …”
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Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
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Comparison of Gradient Boosting Decision Tree Algorithms for CPU Performance
Published 2021“…This paper aims to compare the performance of CPU implementation of the top three gradient boosting algorithms. We start by explaining how the three algorithms work and the hyperparameters similarities between them. …”
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Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…The use of information gain in the ID3 algorithm as the attribute selection criteria is not to assess the relationship between classification and the dataset’s attributes. …”
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Waste management using machine learning and deep learning algorithms
Published 2020“…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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Application of deep learning algorithms in lung sound classification: A systematic review since 2015
Published 2025“…The article systematically explored the application of deep learning for lung sound classification in three popular scientific databases – PubMed, ScienceDirect and IEEE Xplore, for articles published between 2015 and 2024. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Exploring nexus of social media algorithms, content creators, and gender bias: a systematic literature review
Published 2024“…An analysis of 18 quantitative and mixed-method studies from the Web of Science and Scopus databases, spanning 2019 to 2023, uncovers three main research trajectories: algorithms' influence on gender bias, their role in shaping content, and the interactions between algorithms, gender bias, and content creators. …”
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Classification of diabetic patients with imbalanced class distribution by using a Cost-Sensitive forest algorithm / Ummi Asyiqin Che Muhammad and Muhammad Hasbullah Mohd Razali
Published 2023“…Although many machine learning algorithms have been developed by researchers, the class imbalanced distribution still makes it challenging for classifiers to properly learn and differentiate between the minority and majority classes. …”
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Book Section -
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Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
Published 2016“…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. …”
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Student Project -
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Comparative analysis on the deployment of machine learning algorithms in the distributed brillouin optical time domain analysis (BOTDA) fiber sensor
Published 2023“…It was found that all of the ML algorithms have significantly reduced the signal processing time to be between 3.5 and 655 times faster than the conventional Lorentzian curve fitting (LCF) method. …”
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms
Published 2022“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms
Published 2022“…The machine learning models employed automated features selection with hybrid two metaheuristics algorithms namely particle swarm optimization (PSO) and genetic algorithm (GA). …”
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…In one-side incomplete information problem, comparison between MGT algorithm and smart random trade-offs (SRT) algorithm indicates that MGT outperforms SRT. …”
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Enhanced Model Compression for Lipreading Recognition based on Knowledge Distillation Algorithm
Published 2025“…Three compression algorithms are used to fit and learn the transformation between different features, so that portable mobile terminals with limited hardware resources can carry the model. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia
Published 2015“…Then, a multi criteria with two-threshold algorithm is proposed to prioritize the selection between the LTE and WiMAX as target technologies. …”
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