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  1. 1
    Detection and classification of conflict flows in SDN using machine learning algorithms

    Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

    Published 2021
    “…Moreover, applying machine learning algorithms in the identification and classification of conflicting flows has limitations. …”
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  2. 2
    Q-Learning traffic signal optimization within multiple intersections traffic network

    Q-Learning traffic signal optimization within multiple intersections traffic network by Chin, Yit Kwong, Kow, Wei Yeang, Khong, Wei Leong, Tan, Min Keng, Teo, Kenneth Tze Kin

    Published 2012
    “…Adjacent traffic light intersections will work independently and yet cooperate with each other to a common goal of ensuring the fluency of the traffic flows within traffic network. The experimental results show that the Q-Learning algorithm is able to learn from the dynamic traffic flow and optimized the traffic flow.…”
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  3. 3
    River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network

    River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

    Published 2024
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  4. 4
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  5. 5
    Immune network algorithm in monthly streamflow prediction at Johor river

    Immune network algorithm in monthly streamflow prediction at Johor river by Mat Ali, Nur Izzah, Abdul Malik, Marlinda, Ismail , Amelia Ritahani

    Published 2014
    “…Immune Network Algorithm is part of the three main algorithm in AIS. …”
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  6. 6
    Immune network algorithm in monthly streamflow prediction at Johor river

    Immune network algorithm in monthly streamflow prediction at Johor river by Mat Ali, Nur Izzah, Abdul Malek, Marlinda, Ismail, Amelia Ritahani

    Published 2015
    “…Immune Network Algorithm is part of the three main algorithm in AIS. …”
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  7. 7
    Immune network algorithm in monthly streamflow prediction at Johor river

    Immune network algorithm in monthly streamflow prediction at Johor river by Ali N.I.M., Malek M.A., Ismail A.R.

    Published 2023
    “…Immune Network Algorithm is part of the three main algorithm in AIS. …”
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  8. 8
    Heart Attack Prediction with Deep Learning

    Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

    Published 2023
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  9. 9
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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    Thesis
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  10. 10
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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    Monograph
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  11. 11
    Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network

    Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

    Published 2011
    “…A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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  12. 12
    Microscopic control and optimization of traffic network with Q-Learning algorithm

    Microscopic control and optimization of traffic network with Q-Learning algorithm by Chin, Yit Kwong

    Published 2013
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  13. 13
    Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function

    Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

    Published 2019
    “…The idea is proposed in effort of accessing the functionality of the proposed algorithm to improve the smoothness of traffic flow in a network. …”
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  14. 14
    Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process

    Investigation of cross-entropy-based streamflow forecasting through an efficient interpretable automated search process by Chong K.L., Huang Y.F., Koo C.H., Sherif M., Ahmed A.N., El-Shafie A.

    Published 2024
    “…However, the highly imbalanced flow distribution often hinders the machine learning algorithm's performance. …”
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  15. 15
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. …”
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  16. 16
    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT

    OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

    Published 2023
    “…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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  17. 17
    Comparative analysis of river flow modelling by using supervised learning technique

    Comparative analysis of river flow modelling by using supervised learning technique by Ismail, Shuhaida, Pandiahi, Siraj Mohamad, Shabri, Ani, Mustapha, Aida

    Published 2018
    “…The goal of this research is to investigate the efficiency of three supervised learning algorithms for forecasting monthly river flow of the Indus River in Pakistan, spread over 550 square miles or 1800 square kilometres. …”
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  18. 18
    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources

    Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

    Published 2021
    “…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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  19. 19
    Back Propagation Algorithm-Based Intelligent Model for Botnet Detection

    Back Propagation Algorithm-Based Intelligent Model for Botnet Detection by Nik Quosthoni, Sunaidi, Ahmed, Abdulghani Ali

    Published 2018
    “…The focus of this study is a proposed back propagation algorithm in for training the sensor leveraging the machine learning techniques, which will keep an eye on attributes of the identified or recognized traffic flow. …”
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  20. 20
    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus

    Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus by Kumar, A., Ridha, S., Ilyas, S.U., Dzulkarnain, I., Pratama, A.

    Published 2022
    “…The algorithms also explain the effect of geometric and rheological parameters on the fluid flow attributes. …”
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