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  1. 1
    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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  2. 2
    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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  3. 3
    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol

    Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

    Published 2023
    “…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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  4. 4
    An implementation of brain emotional learning based intelligent controller for AVR system

    An implementation of brain emotional learning based intelligent controller for AVR system by Saat, Shahrizal, Ghazali, Mohd Riduwan, Ahmad, Mohd Ashraf, Mustapha, Nik Mohd Zaitul Akmal, Tumari, Mohd Zaidi Mohd

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. …”
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  5. 5
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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  6. 6
    An implementation of brain emotional learning based intelligent Controller for AVR system

    An implementation of brain emotional learning based intelligent Controller for AVR system by Shahrizal, Saat, Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Nik Mohd Zaitul Akmal, Mustapha, Mohd Zaidi, Mohd Tumari

    Published 2023
    “…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. …”
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  7. 7
    A technical perspective on integrating artificial intelligence to solid‑state welding

    A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Alam, Mohammad Nur‑E, Soudagar, Manzoore Elahi Mohammad

    Published 2024
    “…Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. …”
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  8. 8
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
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  9. 9
    A technical perspective on integrating artificial intelligence to solid‑state welding

    A technical perspective on integrating artificial intelligence to solid‑state welding by Yaknesh, Sambath, Rajamurugu, Natarajan, Babu, Prakash K., Subramaniyan, Saravanakumar, Khan, Sher Afghan, Saleel, C. Ahamed, Nur‑E‑Alam, Mohammad, Soudagar, Manzoore Elahi Mohammad

    Published 2024
    “…Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. …”
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  10. 10
    Industrial implementation of machine learning forecasting algorithms for large-scale Solar Heat for Industrial Process (SHIP) Systems

    Industrial implementation of machine learning forecasting algorithms for large-scale Solar Heat for Industrial Process (SHIP) Systems by Manu, Abdurrahman, Haja Mohideen, Ahmad Jazlan, Akhter, Muhammad Naveed, Ahmad Huzri, Muhammad Danial, Mohd Ibrahim, Azhar, Mohd Zaki, Hasan Firdaus, Sreeram, Victor

    Published 2025
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  11. 11
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  12. 12
    Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi

    Diamond price prediction using random forest algorithm / Nur Amirah Mohd Azmi by Mohd Azmi, Nur Amirah

    Published 2025
    “…Traditional methods struggle to model these complexities effectively, necessitating adoption of advanced algorithms to improve accuracy. …”
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  13. 13
    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region

    Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

    Published 2025
    “…This type of outcome is valuable to the decision-maker to implement a more optimal strategy for reducing the probability of landslides and its associated damages. ? …”
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  14. 14
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…The hierarchical fuzzy clustering method developed here is far better than a similar implementation of the hard k-means method. …”
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  15. 15
    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach

    Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

    Published 2025
    “…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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  16. 16
    Context enrichment framework for sentiment analysis in handling word ambiguity resolution

    Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

    Published 2024
    “…For classification performances, optimization of machine learning parameters and exploration of deep learning approaches can be applied for further enhancement.…”
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  17. 17
    Optimization of turning parameters using genetic algorithm method

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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    Undergraduates Project Papers
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  18. 18
    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis

    Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

    Published 2018
    “…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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  19. 19
    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization

    Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

    Published 2014
    “…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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  20. 20
    Optimization of turning parameters using ant colony optimization

    Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

    Published 2008
    “…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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