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  1. 1
    A gauss-newton approach for nonlinear optimal control problem with model-reality differences

    A gauss-newton approach for nonlinear optimal control problem with model-reality differences by Sie, Long Kek, Jiao, Li, Leong, Wah June, Abd Aziz, Mohd Ismail

    Published 2017
    “…Here, the linear model-based optimal control model is considered, so as the optimal control law is constructed. …”
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  2. 2
    Visualization on colour based flow vector of thermal image for movement detection during interactive session

    Visualization on colour based flow vector of thermal image for movement detection during interactive session by Ibrahim, Nabilah, Raman, Mohamad Nurazmi, Mahadi, Lina Farhana, Wan Zakaria, Wan Nurshazwani

    Published 2018
    “…Thus, methods employed in this work are Canny edge detector method, Lucas Kanade and Horn Shunck algorithms, to overcome the major problem when using thresholding method, which is only intensity or pixel magnitude is considered instead of relationships between the pixels. …”
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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
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  4. 4
    Marine Predator Algorithm and Related Variants: A Systematic Review

    Marine Predator Algorithm and Related Variants: A Systematic Review by Philibus, Emmanuel, Mohd Zain, Azlan, Prasetya, Didik Dwi, Bahari, Mahadi, Yusup, Norfadzlan, Abdul Jalil, Rozita, Abdul Majid, Mazlina, A Samah, Azurah

    Published 2025
    “…It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the biological relationship between prey and predators. …”
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  5. 5
    Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques

    Parametric modelling application to a twin rotor system using recursive least squares, genetic, and swarm optimization techniques by Toha, Siti Fauziah, Tokhi, M. O.

    Published 2010
    “…This paper endeavours to establish an empirical relationship between input and observed output data for the identification of a one-degree-of-freedom hovering motion model of a twin rotor multi-input–multi-output system (TRMS). …”
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  6. 6
    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
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  7. 7
    Marine Predator Algorithm and Related Variants: A Systematic Review

    Marine Predator Algorithm and Related Variants: A Systematic Review by Emmanuel, Philibus, Azlan, Mohd Zain, Didik Dwi, Prasetya, Mahadi, Bahari, Norfadzlan, Yusup, Rozita, Abdul Jalil, Mazlina, Abdul Majid, Azurah, A Samah

    Published 2025
    “…It is a population-based metaheuristic optimization algorithm inspired by the general foraging behavior exhibited in the form of Levy and Brownian motion in ocean predators supported by the policy of optimum success rate found in the biological relationship between prey and predators. …”
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  8. 8
    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption

    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

    Published 2015
    “…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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  9. 9
    Gravitational Search Algorithm for Assembly Sequence Planning

    Gravitational Search Algorithm for Assembly Sequence Planning by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Mohd Falfazli, Mat Jusof, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Marizan, Mubin

    Published 2014
    “…In this paper, an approach using Gravitational Search Algorithm (GSA) which is a heuristic optimization algorithm that incorporates the Newton’s law of gravity and the law of motion into analytical studies of systems is proposed to solve the assembly sequence planning problem. …”
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  10. 10
    Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood

    Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood by Dawood, Farhan

    Published 2015
    “…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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  11. 11
    Design and Development of a Vision System Interface for Three Degree of Freedom Agricultural Robot

    Design and Development of a Vision System Interface for Three Degree of Freedom Agricultural Robot by Omrane, Bouketir

    Published 1999
    “…This differential system represents the dynamic model, which describes relationships between robot motion and forces causing that motion. …”
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  12. 12
    QUANTITATIVE SCHLIEREN MEASUREMENT OF 3 DIMENSIONAL TEMPERATURE, CONCENTRATION AND VELOCITY FIELDS IN A GAS FLOW

    QUANTITATIVE SCHLIEREN MEASUREMENT OF 3 DIMENSIONAL TEMPERATURE, CONCENTRATION AND VELOCITY FIELDS IN A GAS FLOW by IFFA, EMISHAW DANDENA IFFA

    Published 2011
    “…The Gladstone-Dale relationship was used to show the direct correlation between the index of refraction and density of the flow. …”
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  13. 13
    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar

    Vibration-based structural damage detection and system identification using wavelet multiresolution analysis / Seyed Alireza Ravanfar by Seyed Alireza, Ravanfar

    Published 2017
    “…Then, the damage severities at the identified locations are assessed using genetic algorithm (GA), through defining a database to reveal the relationships between the energies obtained and damage severities. …”
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  14. 14
    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN)

    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan T., Manan T.S.B., Isa M.H., Ghanim A.A.J., Beddu S., Jusoh H., Iqbal M.S., Ayele G.T., Jami M.S.

    Published 2023
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  15. 15
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…By using the proposed algorithm, the sparse coefficients are learned by exploiting the relationships among different multi-view features and leveraging the knowledge from multiple related tasks. …”
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  16. 16
    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN)

    Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN) by Khan, T., Manan, T.S.B., Isa, M.H., Ghanim, A.A.J., Beddu, S., Jusoh, H., Iqbal, M.S., Ayele, G.T., Jami, M.S.

    Published 2020
    “…The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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  17. 17
    Framework for stream clustering of trajectories based on temporal micro clustering technique

    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…Initiating clustering from scratch in each time-bin and not considering the relationships between the objects from two consecutive time-bins lead to creating redundant micro clusters centralizes in the border area between two adjacent time bins. …”
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  18. 18
    Modelling and simulation of hollow profile aluminium extruded product

    Modelling and simulation of hollow profile aluminium extruded product by Sulaiman, Shamsuddin, Baharudin, B. T. Hang Tuah, Mohd Ariffin, Mohd Khairol Anuar, Magid, Hani Mizhir

    Published 2015
    “…This process is an isothermal process with an extrusion ratio of 3.3. Subsequently, the optimized algorithm for these extrusion parameters was suggested based on the simulation results. …”
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  19. 19
    Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon

    Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon by Lim , Pooi Khoon

    Published 2020
    “…Next, multiple linear regression (MLR) and support vector regression (SVR) models were used to examine the relationship between the Systolic Blood Pressure (SBP) and the Diastolic Blood Pressure (DBP) ratio with ten features extracted from the oscillometric waveform envelope (OWE). …”
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  20. 20
    Modeling of cu(ii) adsorption from an aqueous solution using an artificial neural network (ann)

    Modeling of cu(ii) adsorption from an aqueous solution using an artificial neural network (ann) by Khan, Taimur, Abd Manan, Teh Sabariah, Hasnain Isa, Mohamed, A. J. Ghanim, Abdulnoor, Beddu, Salmia, Jusoh, Hisyam, Iqbal, Muhammad Shahid, Ayele, Gebiaw T, Jami, Mohammed Saedi

    Published 2020
    “…The Fletcher–Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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