Search Results - (( intelligence based data algorithm ) OR ( intelligence big data algorithm ))*

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    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

    Published 2019
    “…The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. …”
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    Article
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    Software agent as an effective tool for managing the Internet of thing data complexity by Mustafa, M.B., Yusoof, M.A.M.

    Published 2017
    “…In the agent-based approach to middleware, the agent’s property such as autonomous, mobile and intelligent are suitable as e-assistance tool for big data management. …”
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    Conference or Workshop Item
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    Novel rule base development from IED-resident big data for protective relay analysis expert system by Othman, Mohammad Lutfi, Aris, Ishak, Ananthapadmanabha, Thammaiah

    Published 2016
    “…Thus, the objective of this chapter is to study the design of an Expert System called ProtectiveRelay Analysis System (PRAY), which is imbedded with a rule base construction module. This module is to provide the facility of intelligently maintaining the knowledge base of PRAY through the prior discovery of relay operations (association) rules from a novel integrated data mining approach of Rough-Set-Genetic-Algorithm-based rule discovery and Rule Quality Measure. …”
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    Book Section
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    Computational intelligence approaches for classification of medical data: State-of-the-art, future challenges and research directions by Kalantari, Ali, Kamsin, Amirrudin, Shamshirband, Shahaboddin, Gani, Abdullah, Alinejad-Rokny, Hamid, Chronopoulos, Anthony T.

    Published 2018
    “…The explosive growth of data in volume, velocity and diversity that are produced by medical applications has contributed to abundance of big data. …”
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    Article
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    Efficient transmission based on genetic evolutionary algorithm by Jin Fan, Kit Guan Lim, Helen Sin Ee Chuo, Min Keng Tan, Ali Farzamnia, Kenneth Tze Kin Teo

    Published 2022
    “…Today’s society has grappled with the age of big data. Widespread use of informatization technology has promoted the development of artificial intelligence and communication technologies, which can play an important role in communication networks. …”
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    Proceedings
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    DATA ANALYTICS FOR HOSPITAL OPERATIONS by EL SAFTY, ABDULRAHMAN EHAB

    Published 2015
    “…Throughout the years, research has been concluded to develop methods of interpreting and analyzing this data. Biomedical statistical researchers have experimented algorithms to achieve findings and associations within the aspects of the data given. …”
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    Final Year Project
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    Development and Integration of Metocean Data Interoperability for Intelligent Operations and Automation Using Machine Learning: A Review by Danyaro, K.U., Hussain, H.H., Abdullahi, M., Liew, M.S., Shawn, L.E., Abubakar, M.Y.

    Published 2022
    “…This slows down provisioning, while the monitoring element of the Metocean data path is partial. In this paper, we demonstrate the capabilities of ML for the development of Metocean data integration interoperability based on intelligent operations and automation. …”
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    Article
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    Classification of EEG Spectrogram Using ANN for IQ Application by Mahfuzah, Mustafa, Norizam, Sulaiman

    Published 2013
    “…This texture feature produced big matrix data, thus Principal Component Analysis (PCA) is used to reduce the big matrix. …”
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    Conference or Workshop Item
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    GA optimization-based BRB AI reasoning algorithm for determining the factors affecting customer churn for operators by Kun, Liu, Alli, Hassan, Abd Rahman, Khairul Aidil Azlin

    Published 2024
    “…In the era of big data, numerous predictive models are based on more redundant features, which increases the complexity of the algorithms and the difficulty of analyzing customer churn. …”
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    Article
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