Search Results - (( a distribution process algorithm ) OR ( parameter adaptation index algorithm ))*

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    Parameter adaptation for ant colony system in wireless sensor network by Abdul Nasir, Husna Jamal, Ku-Mahamud, Ku Ruhana, Kamioka, Eiji

    Published 2019
    “…Most researches are focused on optimizing the routing process by using predefined parameters within a certain range. …”
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    Article
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    Water quality monitoring using machine learning and IoT: a review by Hasan, Tahsin Fuad, Kabbashi, Nassereldeen Ahmed, Saleh, Tanveer, Alam, Md. Zahangir, Abd Wahab, Mohd Firdaus, Nour, Abdurahman Hamid

    Published 2024
    “…However, with the emergence of machine learning (ML) and Internet of Things (IoT) technologies, the process of water quality monitoring and analysis has become more efficient, accurate, and cost-effective. …”
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    A novel computer-aided multivariate water quality index by Siong, Fong Sim, Teck, Yee Ling, Seng, Lau, Mohd Zuli, Jaafar

    Published 2015
    “…Unlike other conventional indexing methods, the algorithm calculates the index in a multivariate manner. …”
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    A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform by Mahmmod, Basheera M.

    Published 2018
    “…This work contributed in developing a new transform, finding a new speech and noise models, introducing new linear and non-linear estimators with their adaptively smoothing parameter to get good noise reduction. …”
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    Thesis
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    Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring by Ab Halim, Haizum Hanim

    Published 2021
    “…Thus, in this thesis, a new Smart Energy Meter (SEM) with adaptive data transfer algorithm is designed to accommodate the problem. …”
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    Thesis
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    Particle swarm optimization-based model-free adaptive control for time-varying batch processes by Wang, Zhao, A.S., Sadun, N.A., Jalaludin, J., Jalani, S.N.H., Arifin, Mohamed Sunar, N., Muhammad Ashraf, Fauzi

    Published 2024
    “…Further, considering that the adopted model-free adaptive control involves seven control parameters, such as cognitive scaling factor (φ1), social scaling factor (φ2), inertia weight (φ3), learning rate (η), control parameter update rate, exploration rate and learning rate for MFAC obtained by a particle swarm optimization (PSO) algorithm in combination with a criterion function performance index. …”
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