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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Investigating the Performance of Deep Reinforcement Learning-Based MPPT Algorithm under Partial Shading Condition by Yew W.H., Fat Chau C., Mahmood Zuhdi A.W., Syakirah Wan Abdullah W., Yew W.K., Amin N.

“…Recently, more robust algorithms based on deep reinforcement learning (DRL) have been proposed. …”

Implementation of machine learning algorithm in preventing network congestion by Noorazimah binti Ali Sabri

Object based segmentation and analysis using deep learning algorithm for cats and dogs images by N.Rajandhiran, Shreevishal

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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…The experiments were performed on the prominent intrusion machine-learning datasets (KDDCUP’99 and CICIDS 2017), where significant enhancements were observed with the suggested NTLBO algorithm as compared to the classical TeachingLearning-Based Optimization algorithm (TLBO), NTLBO presented better results than TLBO and many existing works. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

“…Furthermore, the proposed techniques based on the Q-Learning algorithm do not consider context-based actions. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

“…We utilized the enhanced Q-Learning algorithm to compare actions, including context-based actions, to effectively achieve higher code coverage. …”
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Assessing rainfall prediction models: Exploring the advantages of machine learning and remote sensing approaches by Latif S.D., Alyaa Binti Hazrin N., Hoon Koo C., Lin Ng J., Chaplot B., Feng Huang Y., El-Shafie A., Najah Ahmed A.

“…Statistical models and machine learning algorithms automatically learn and improve based on data. …”

An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…Maladaptive e-Learning systems cannot impart quality content for each student as the users observe the information based on their exclusive learning traits. …”

Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning by Rahman, R.A., Masrom, S., Zakaria, N.B., Nurdin, E., Abd Rahman, A.S.

“…Furthermore, the most outperformed algorithm has been presented by the linear based machine learning, which produced the best accuracy in the shortest total time completion. …”
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Classification of Unhealthy Chicken based on Chromaticity of the Comb by Bakar M.A.A.A., Ker P.J., Tang S.G.H., Lee H.J., Zainal B.S.

Machine learning modeling for radiofrequency electromagnetic fields (RF-EMF) signals from mmWave 5G signals by Al-Jumaily, Abdulmajeed, Sali, Aduwati, Riyadh, Mohammed, Wali, Sangin Qahtan, Li, Lu, Osman, Anwar Faizd

“…As a result, it can be observed that the Exact-RBFNN algorithm is the best algorithm to predict the RF-EMF because it shows good agreement with the measured value. …”
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Multi-Agent Reinforcement Learning For Swarm Robots Formation by Bujang, Christina

“…The reinforcement learning algorithm offers one of the most general frameworks in learning subjects to address some of the control issues in a multi-agent system. …”
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Machine learning-based leukemia classification using gene expression for accurate diagnosis by Mahmoud, Amena, Talpur, Kazim Raza, Saini, Shilpa, Talpur, Bandeh Ali, Shah, Asadullah, Zaki, John

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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…Each observation was independently assessed for errors. Ten machine learning (ML) algorithms were applied with features derived from systematic reviews, incident reports, and expert consensus. …”
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Enhanced Model Compression for Lipreading Recognition based on Knowledge Distillation Algorithm by Qianru, Lu, Kuryati, Kipli, Tengku Mohd Afendi, Zulcaffle, Yuan, Liu, Xiangju, Liu, Bo, Wang

“…Therefore, three knowledge distillation compression algorithms are proposed in this paper: Three different knowledge distillation compression algorithms, an offline model compression algorithm based on multi-feature transfer (MTOF), an online model compression algorithm based on adversarial learning (ALON), and an online model compression algorithm based on consistent regularization(CRON) to complete the compression of the Chinese character sequence output by the model. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich by Bathich, Ammar

“…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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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking by Dira, Yasir Sabah

“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

“…Based on observations made from stochastic dynamical systems, we consider the issue of parameter learning, and a related state estimation problem. …”
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