Search Results - intelligence _ ((proposed algorithm) OR (cloud algorithm))

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    Two objectives big data task scheduling using swarm intelligence in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke, Islam, Shayla, Zarir, Abdullah Ahmad

    Published 2016
    “…In this direction, this paper first gives review of some previous scheduling algorithms used in cloud. Then, it proposes a type of swarm intelligence called Particle Swarm Optimization (PSO) algorithm to diminish cost though meeting deadlines. …”
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    Article
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    Tag clouds algorithm with the inclusion of personality traits by Ahmad Affandi, Supli

    Published 2015
    “…Furthermore, the algorithm to generate tag cloud visualization based on personality traits has not been explored. …”
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    Thesis
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    Modeling approach of cloud 4D printing service composition optimization based on non-dominated sorting genetic algorithm III by Liu, Jiajia, Zainudin, Edi Syams, As'arry, Azizan, Ismail, Mohd Idris Shah

    Published 2024
    “…We propose a comprehensive multiobjective optimization model for cloud-based 4D printing service portfolios, incorporating the intricate complexities of 4D printing services and assessing the efficacy of the Non-Dominated Sorting Genetic Algorithm III (NSGA III) in optimizing these service portfolios to meet dynamic demands. …”
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    Article
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    User authentication in public cloud computing through adoption of electronic personal synthesis behavior by Mohanaad Talal Shakir

    Published 2023
    “…Moreover, the learning process of the proposed algorithm for behavior recognition designed as a matching factor with a password during the authentication process. …”
    text::Thesis
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    Tag cloud algorithm with the inclusion of personality traits by Supli, Ahmad Affandi, Shiratuddin, Norshuhada, Ab. Aziz, Azizi

    Published 2014
    “…Therefore, the main objective of this study is to make tag cloud algorithm with the inclusion of personality traits by adjusting two prominent visual features (color and shape) as an integration of layout.In addition, the utilization of RBS (rule bas e system) approach as artificial intelligent method is also taken into account to make knowledge base that stores the relationship between the proper personality elements and particular layout.This paper also discusses findings from satisfaction evaluation of prototyping, which comprises three dimensions facet: overall layout, color, and shape .The findings showed that the majority mean value for each dimension is categorized in agree scale (6-point), which indicates that respondents are satisfied with the tag cloud layout display generated by proposed algorithm.The findings suggest interface designers to be careful in selecting the appropriate tag clouds layout to be displayed for users with varying personality differences.…”
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    Article
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    Task scheduling in cloud computing using Harris-Hawk Optimization by Iza A. A. Bahar, Azali Saudi, Abdul Kadir, Syed Nasirin Syed Zainol Abidin, Tamrin Amboala, Esmadi Abu Bin Abu, Abdullah B. Mohd. Tahir, Suddin Lada

    Published 2024
    “…In this study, the proposed HHO algorithm is simulated and compared with other well-known swarm intelligence algorithms, including Bat Algorithm (BA), Grey Wolf Optimization (GWO), and Particle Swarm Optimization (PSO). …”
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    Proceedings
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    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

    Published 2022
    “…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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    Final Year Project / Dissertation / Thesis
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    Latency Analysis of Cloud Infrastructure for Time-Critical IoT Use Cases by Kartinah, Zen, Saju, Mohanan, Seleviawati, Tarmizi, Noralifah, Annuar

    Published 2022
    “…Latency in real-time processing is influenced by many factors such as artificial intelligence (AI) computing algorithm, device processing capabilities, the frameworks, and also the distance from the cloud infrastructure. …”
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    Proceeding
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