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  1. 1
    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool

    Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

    Published 2019
    “…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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  2. 2
    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control

    A novel softsign fractional-order controller optimized by an intelligent nature-inspired algorithm for magnetic levitation control by Ahmad, Mohd Ashraf, Izci, Davut, Ekinci, Serdar, Mohd Tumari, Mohd Zaidi

    Published 2025
    “…The performance of the proposed approach was extensively benchmarked against four modern metaheuristic algorithms (greater cane rat algorithm, catch fish optimization algorithm, RIME algorithm and artificial hummingbird algorithm) under identical conditions. …”
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  3. 3
    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Temitope T., Dele-Afolabi, Masoud, Ahmadipour, Mohamed Ariff, Azmah Hanim, A.A., Oyekanmi, M.N.M., Ansari, Sikiru, Surajudeen, Kumar, Niraj

    Published 2024
    “…The presence of MWCNTs in the Sn-5Sb solder alloy significantly prevented IMC formation at the interface and enhanced the shear strength, according to empirical observations, which were supported by the excellent properties of MWCNTs. An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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  4. 4
    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer

    Performance assessment of Sn-based lead-free solder composite joints based on extreme learning machine model tuned by Aquila optimizer by Dele-Afolabi T.T., Ahmadipour M., Azmah Hanim M.A., Oyekanmi A.A., Ansari M.N.M., Sikiru S., Kumar N.

    Published 2025
    “…The presence of MWCNTs in the Sn-5Sb solder alloy significantly prevented IMC formation at the interface and enhanced the shear strength, according to empirical observations, which were supported by the excellent properties of MWCNTs. An extreme learning machine (ELM) prediction approach refined by Aquila optimizer (AO), a new cutting-edge metaheuristic optimization algorithm was utilized to develop a prediction model for the performance assessment of the developed solder composites. …”
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  5. 5
    Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review

    Ozone Concentration Forecasting Based on Artificial Intelligence Techniques: A Systematic Review by Yafouz A., Ahmed A.N., Zaini N., El-Shafie A.

    Published 2023
    Review
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  6. 6
    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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  7. 7
    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer

    Optimisation of support vector machine hyperparameters using enhanced artificial bee colony variant to diagnose breast cancer by Ravindran, Nadarajan

    Published 2023
    “…The combination of these two aspects can assist to balance and enhance the exploration and exploitation capability. Before using the JAABC5ROC as an optimizer for the SVM, a total of 10 benchmark function were used to determine its performance assessment 5 common benchmarks which are (Shows Rosenbrok, Sphere, Step and RS Schwefel Ridges and RS Zekhelip) and 5 CEC2017 benchmarks which are (Shifted and Rotated Zakharov Function, Hybrid Function 01, Composite Function 08, Composite Function 09 and Composite Function 10). …”
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  8. 8
    Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network

    Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network by Langroodi, Naz Chaibakhsh

    Published 2010
    “…Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of seven hidden nodes with hyperbolic tangent sigmoid transfer function. …”
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  9. 9
    Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics

    Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

    Published 2021
    “…The statistical analysis presented in this study incorporated one of the best regression models algorithms based on machine learning approach to study the adsorption variation with shale fabric this study. …”
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  10. 10
    Analysis of photovoltaic panels performance and power output forecasting based on optimized deep learning technique / Muhammad Naveed Akhter

    Analysis of photovoltaic panels performance and power output forecasting based on optimized deep learning technique / Muhammad Naveed Akhter by Muhammad Naveed, Akhter

    Published 2021
    “…Moreover, Salp Swarm Algorithm (SSA) is used to tune the hyperparameters of the developed deep learning method on an annual basis over four years to enhance its forecasting accuracy and is compared with RNN-LSTM, GA-RNN-LSTM, and PSO-RNN-LSTM. …”
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  11. 11
    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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  12. 12
    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing

    On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

    Published 2015
    “…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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  13. 13
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  14. 14
    Finite impulse response optimizers for solving optimization problems

    Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

    Published 2019
    “…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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  15. 15
    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting

    LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

    Published 2015
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  16. 16
    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri

    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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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
    Optimization of milling parameters using ant colony optimization

    Optimization of milling parameters using ant colony optimization by Mohd Saupi, Mohd Sauki

    Published 2008
    “…The simulation based on ACO algorithm are successful develop and the optimization of parameters values is to maximize the production rate is obtain from the simulation.…”
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  19. 19
    Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm

    Improvement of horizontal streak on disparity map thru parameter optimization for stereo vision algorithm by Gan, Melvin Yeou Wei, Hamzah, Rostam Affendi, Nik Anwar, Nik Syahrim, Herman, Adi Irwan, Jamil Alsayaydeh, Jamil Abedalrahim

    Published 2024
    “…Then, the research continues to optimize the proposed local based SVDM algorithm through parameters optimization in obtaining the final disparity map. …”
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  20. 20
    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study

    Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

    Published 2023
    “…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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