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  1. 1
    A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption

    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
    “…This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. …”
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  2. 2
    A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption

    A theoretical framework for big data analytics based on computational intelligent algorithms with the potential to reduce energy consumption by Haruna, Chiroma, Abdullahi, Usman Ali, Targio Hashem, Ibrahim Abaker, Saadi, Younes, Al-Dabbagh, Rawaa Dawoud, Ahmad, Muhammad Murtala, Emmanuel Dada, Gbenga, Danjuma, Sani, Maitama, Jaafar Zubairu, Abubakar, Adamu, Abdulhamid, Shafi’i Muhammad

    Published 2019
    “…This work highlights that big data analytics using computational intelligent algorithms generates a very high amount of energy, especially during the training phase. …”
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  3. 3
    Swarm intelligence optimization algorithms: a review

    Swarm intelligence optimization algorithms: a review by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad

    Published 2018
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  4. 4
    Two objectives big data task scheduling using swarm intelligence in cloud computing

    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
    “…On the other hand, scheduling algorithms; starting from traditional to Hyper-heuristic; are widely used in computing systems such as cloud computing to monitor the use of resources. …”
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  5. 5
    Advanced computational geometry for proximity queries of convex polyhedras

    Advanced computational geometry for proximity queries of convex polyhedras by Sundaraj, Kenneth, Retnasamay, V.

    Published 2009
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  6. 6
    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm

    Optimal location and size estimation of distributed generators by employing grouping particle swarm optimization and grouping genetic algorithm by Mohammed, Zahraa Abdulkareem

    Published 2017
    “…This work is aimed to decrease the total real and reactive power losses while enhancing the voltage profile of the distribution network with less computation time by proposing two new artificial intelligence algorithms, i.e. grouping particle swarm optimization algorithm and grouping genetic algorithm. …”
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  7. 7
    Development of an intelligent prediction tool for rice yield based on machine learning techniques

    Development of an intelligent prediction tool for rice yield based on machine learning techniques by Md. Sap, Mohd. Noor, Awan, A. M.

    Published 2006
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  8. 8
    E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm

    E2IDS: an enhanced intelligent intrusion detection system based on decision tree algorithm by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik

    Published 2022
    “…This work presents an enhanced intelligent intrusion detection model (E2IDS) to detect state of the art known cyberattacks. …”
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  9. 9
    Bats echolocation-inspired algorithms for global optimisation problems

    Bats echolocation-inspired algorithms for global optimisation problems by Nafrizuan, Mat Yahya

    Published 2016
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  10. 10
    Intelligent energy allocation strategy for PHEV charging station using gravitational search algorithm

    Intelligent energy allocation strategy for PHEV charging station using gravitational search algorithm by Rahman, Imran, Vasant, Pandian, Mahinder Singh, Balbir Singh, Abdullah-Al-Wadud, M.

    Published 2014
    “…Most of these works require formulation of mathematical models which extensively use computational intelligence-based optimization techniques to solve many technical problems. …”
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  11. 11
    An intelligent system based on kernel methods for crop yield prediction

    An intelligent system based on kernel methods for crop yield prediction by Majid Awan, A., Md. Sap, Mohd. Noor

    Published 2006
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  12. 12
    A hybrid intelligent algorithm for solving the bilevel programming models

    A hybrid intelligent algorithm for solving the bilevel programming models by Shamsul Bahar, Yaakob, Prof. Madya, Watada, Junzo

    Published 2011
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  13. 13
    Server scanning worm detection by using intelligent failure connection algorithm

    Server scanning worm detection by using intelligent failure connection algorithm by M. Rasheed, Mohammad, Ghazali, Osman, Md. Norwawi, Norita

    Published 2010
    “…The aim of this study is to propose Server Worm Register (SWD) to register the number of computers that are infected by the worm. Our proposal decreases the false alarm in Intelligent Failure Connection Algorithm (IFCA). …”
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  14. 14
    Automating commercial video game development using computational intelligence

    Automating commercial video game development using computational intelligence by Tse, Guan Tan, Teo, Jason Tze Wi, Patricia Anthony

    Published 2011
    “…Pac-man. The resulting algorithm is referred to as an Evolution Strategies Neural Network or ESNet. …”
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  15. 15
    Handbook of Research on Artificial Intelligence Techniques and Algorithms

    Handbook of Research on Artificial Intelligence Techniques and Algorithms by Vasant, P.

    Published 2014
    “…The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. …”
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  16. 16
    Intelligent classification algorithms in enhancing the performance of support vector machine

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2019
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  17. 17
    Development of Artificial Intelligent Techniques for Manipulator Position Control

    Development of Artificial Intelligent Techniques for Manipulator Position Control by Bani Hashim, Ahmad Yusairi

    Published 2002
    “…This work combines three methods in artificial intelligence: fuzzy rules, neural networks, and genetic algorithm to form the soft computing plant uniquely planned for a six degree-of-freedom serial manipulator. …”
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  18. 18
    Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm

    Optimization of user comfort index for ambient intelligence using dynamic inertia weight artificial bees colony optimization algorithm by Farah Nur Arina, Baharudin, Nor Azlina, Ab. Aziz, Mohamad Razwan, Abdul Malek, Zuwairie, Ibrahim

    Published 2021
    “…Ambient intelligence (AmI) aims to bring intelligence to human daily lives and making the environment more sensitive and comfortable by applying computational intelligence, sensors and sensors networks. …”
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  19. 19
    An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms

    An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

    Published 2022
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  20. 20
    Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm

    Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

    Published 2010
    “…The growth of intelligent intrusion and diverse attack techniques in network systems stimulate computer scientists and mathematical researchers to challenge the dangers of intelligent attacks. …”
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