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  1. 1
    Challenges in developing artificial intelligence based systems using classic Software Development Life Cycle / Noorihan Abdul Rahman

    Challenges in developing artificial intelligence based systems using classic Software Development Life Cycle / Noorihan Abdul Rahman by Abdul Rahman, Noorihan

    Published 2024
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  2. 2
    Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites

    Fuzzy Adaptive Teaching Learning-based Optimization Strategy for the Problem of Generating Mixed Strength T-Way Test Suites by Kamal Z., Zamli, Fakhrud, Din, Salmi, Baharom, Ahmed, Bestoun S.

    Published 2017
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  3. 3
    Fuzzy adaptive teaching learning-based optimization strategy for the problem of generating mixed strength t-way test suites

    Fuzzy adaptive teaching learning-based optimization strategy for the problem of generating mixed strength t-way test suites by Zamli, Kamal Zuhari, Din, Fakhrud, Baharom, Salmi, Ahmed, Bestoun S.

    Published 2017
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  4. 4
    Ontology based approach to Fuzzy student model design

    Ontology based approach to Fuzzy student model design by Muhammad Sani, Salisu, Mohd Aris, Teh Noranis

    Published 2014
    “…An important component of these elearning systems in use today is called the intelligent tutoring system (ITS). …”
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  5. 5
    Teaching and learning via chatbots with immersive and machine learning capabilities

    Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

    Published 2019
    “…These chatbots acquired its intelligence through a hybrid approach that combines pattern-matching technique and machine learning algorithm in order to formulate its responses. …”
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  6. 6
    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih

    Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih by Hashim, Asman

    Published 2001
    “…Artificial Neural Network is one of the branches of Artificial Intelligence which is utilized for the purpose of classification and prediction based on data in hand. …”
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  7. 7
    Design of intelligent control system and its application on fabricated conveyor belt grain dryer

    Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

    Published 2011
    “…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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  8. 8
    Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024)

    Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024) by Ibrahim Brian, Muhammad Shyazzwan

    Published 2025
    “…Based on 48 peer-reviewed empirical studies published between 2019 and 2024, the review explores how AI tools, particularly Natural Language Processing (NLP), Intelligent Tutoring Systems (ITS), and generative AI, support personalized learning, increase engagement, and strengthen skill development among English language learners. …”
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  9. 9
    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network

    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

    Published 2012
    “…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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  10. 10
    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network

    Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network by Ahmad Afif, Mohd Faudzi

    Published 2012
    “…The developed learning system has a 4-layered RNN and it was trained by BPTT method based on teaching signal that was generated by Q-Learning algorithm. …”
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  11. 11
    CSC583 - Artificial Intelligence Algorithms / College of Computing, Informatics and Media

    CSC583 - Artificial Intelligence Algorithms / College of Computing, Informatics and Media by UiTM, College of Computing, Informatics and Media

    Published 2018
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  12. 12
    CSC583: Artificial Intelligence Algorithms / College of Computing, Informatics and Mathematics

    CSC583: Artificial Intelligence Algorithms / College of Computing, Informatics and Mathematics by UiTM, College of Computing, Informatics and Mathematics

    Published 2018
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  13. 13
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
    “…The works related to swarm intelligence algorithms include the development of the algorithm itself, its modification and improvisation as well as its application in solving global optimisation problems. …”
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  14. 14
    Integration of dual intelligent algorithms in shunt active power filter

    Integration of dual intelligent algorithms in shunt active power filter by Abdul Rahman, Nor Farahaida, Mohd Radzi, Mohd Amran, Mariun, Norman, Che Soh, Azura, Abd Rahim, Nasrudin

    Published 2013
    “…This paper presents an integration of dual intelligent algorithms: artificial neural network (ANN) based fundamental component extraction algorithm and fuzzy logic based DC-link voltage self-charging algorithm (fuzzy self-charging algorithm), in a three-phase three-wire shunt active power filter (SAPF). …”
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  15. 15
    Swarm Intelligence Based Protein Conformational Search Algorithm.

    Swarm Intelligence Based Protein Conformational Search Algorithm. by Bahamish, Hesham Awadh Abdallah, Abdullah, Rosni, Salam, Rosalina Abdul

    Published 2007
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  16. 16
    Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications

    Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

    Published 2015
    “…Pertama, algoritma TAC yang diubahsuai, diperkenalkan. The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
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  17. 17
    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun

    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…The system is able to update the information from the database provided that the administrator monitors its activities periodically. This system is achieved using the Genetic Algorithm which is capable of performing information retrieval and learning algorithm. …”
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  18. 18
    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach

    An Intelligent Voltage Controller for a PV Inverter System Using Simulated Annealing Algorithm-Based PI Tuning Approach by Najeeb, Mushtaq, Muhamad, Mansor, Ramdan, Razali, Hamdan, Daniyal, Ali, Mahmood

    Published 2017
    “…This study associates an intelligent voltage controller based PI approach for PV electrical inverter by employing a meta-heuristic optimization algorithmic called a Simulated Annealing (SA) algorithm. …”
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  19. 19
    Potential norms detection in social agent societies

    Potential norms detection in social agent societies by Mahmoud M.A., Mustapha A., Ahmad M.S., Ahmad A., Yusoff M.Z.M., Hamid N.H.A.

    Published 2023
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  20. 20
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Firefly algorithm outperformed the other metaheuristic algorithms used to solve this proposed hybrid artificial intelligence model regarding parameter sensitivity. …”
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