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Optimizing boarding school schedule using graph colouring : case study of Sekolah Menengah Sultan Abdul Halim / Nur Farhana Mohd Asri
Published 2021“…Both algorithms were supported by C++ software. Besides, this study applies the concept of comparison between Vertex and Edge Coloring approach. …”
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Student Project -
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Optimizing boarding school schedule using graph coloring: case study of Sekolah Menengah Sultan Abdul Halim / Nur Farhana Mohd Asri
Published 2022“…Both algorithms were supported by C++ software. Besides, this study applies the concept of comparison between Vertex and Edge Coloring approach. …”
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Research Reports -
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Quantifying usability prioritization using K-means clustering algorithm on hybrid metric features for MAR learning
Published 2023“…Augmented reality; Learning algorithms; Machine learning; Usability engineering; Between clusters; Mobile augmented reality; Prioritization; Prioritization techniques; Unsupervised machine learning; Usability; K-means clustering…”
Conference Paper -
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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“…A prototype was fabricated to demonstrate the manipulator. 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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Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…This work proposed the implementation of modified Artificial Bee Colony with Firefly algorithm for training the FLNN network to overcome the drawback of BP-learning algorithm. …”
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Thesis -
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An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms
Published 2022“…The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. …”
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Evaluating the performance of machine learning techniques in the classification of Wisconsin Breast Cancer
Published 2018“…Numerous research works have tried to apply the algorithms of machine learning for classifying breast cancer and it was proven by many researchers that machine learning algorithms act preferable in the diagnosing process. …”
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…This work investigates the suitability and effectiveness of machine learning algorithms such as Multinomial Naive Bayes, KNN, Logistic Regression, Decision Tree for predicting levels of arousal intensity among the programmers and LSTM deep learning algorithm to classify the programmers according to their performance. …”
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Enhancing understanding of programming concepts through physical games
Published 2017“…We regularly discussed and improved on how the steps of the games should be executed especially regarding the sorting algorithm. We also tested the lesson games in our community initiate programmes with the aborigines of Suku Kaum Temuan (28 children and teenagers between 7 to 18 years) and a local community in Subang Bestari, Shah Alam through a computational thinking game competition (32 children and teenagers between 6 to 15 years) supported by the local "Persatuan Penduduk". …”
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Conference or Workshop Item -
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich
Published 2019“…The main objective of this work is to propose and implement an efficient handover decision procedure based on users’ profiles using Q-learning technique in a LTE-A macrocell-femtocell networks. …”
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Thesis -
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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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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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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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Applications of deep learning algorithms for supervisory control and data acquisition intrusion detection system
Published 2022“…For each algorithm, prior works have been identified, examined, and described based on their conceptual similarities. …”
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Integrating finance dictionary in lexicon-based approach with machine learning algorithm to analyse the impact of OPEC news sentiment on financial market / Wu Ling
Published 2020“…The findings of this research show that applying financial sentiment dictionary to train the supervised machine learning algorithm can enhance the performance of machine learning classifier. …”
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Thesis -
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Interpretation of machine learning model using medical record visual analytics
Published 2021“…This paper studied on the effectiveness of visual analytics techniques to identify the appropriate technique to be instantiated to the machine learning algorithm to further elaborate the results obtained by demonstrating transparency, interpreta- bility and explainability of the machine learning algorithm. …”
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Proceeding Paper -
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Multiobjective deep reinforcement learning for recommendation systems
Published 2022“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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Article -
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Multi-objective deep reinforcement learning for recommendation systems
Published 2022“…These limitations have prompted this work to propose deep reinforcement learning (DRL) approaches for MO optimization in RSs. …”
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