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  1. 1

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…Future work should be focusing on data collection of the E-Nose sensors and the improvement of the learning algorithm robustness towards environmental noise during data acquisition, such as evaporation and contamination of odor samples.…”
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    Thesis
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    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  4. 4

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
  5. 5

    Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof by Yusof, Yusman

    Published 2019
    “…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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    Evaluation of optimal MLP structure for heart disease diagnosis / Salbiah Ab Hamid by Ab Hamid, Salbiah

    Published 2010
    “…The weight of each value in hidden layers will be considered during the learning process. LM algorithm is used to minimize the error during training and testing process. …”
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    A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

    Published 2016
    “…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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    Article
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    Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

    Published 2018
    “…The availability of nowadays clinical data of Dengue disease can be used to train machine learning algorithm in order to automaticaly detect the present of Dengue disease of the patients. …”
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    Article
  11. 11

    Machine learning: tasks, modern day applications and challenges by Aljuaid, Lamyaa Zaed, Koh, Tieng Wei, Sharif, Khaironi Yatim

    Published 2019
    “…Machine learning algorithms learned from available data. Further, this learning laid the foundation to develop AI for the various systems around us. …”
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    Article
  12. 12

    Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

    Published 2017
    “…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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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 by 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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  14. 14

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
    Review
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    Evaluation of rehearsal effects of multimedia content based on EEG using machine learning algorithms by Mazher, M., Aziz, A.A., Malik, A.S.

    Published 2017
    “…Three frequency based features are used to discriminate the three learning states mentioned as L1, L2 and L3 using machine learning algorithms. …”
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    Article
  17. 17

    Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

    Published 2022
    “…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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    A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification by Wong, S.Y., Yap, K.S., Yap, H.J., Tan, S.C.

    Published 2015
    “…The idea of developing FAM-OELM is motivated by the ELM concept proposed by Huang et al., for being an efficient learning algorithm that provides better generalization performance at a much faster learning speed. …”
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    Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

    Published 2017
    “…Therefore, the aim of this study is to minimize the computation time during RFS by improving the standard rsync algorithm. …”
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    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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