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  1. 1
    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin

    Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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  2. 2
    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin

    Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

    Published 2014
    “…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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  3. 3
    Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions

    Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions by Abbas O.K., Abdullah F., Radzi N.A.M., Salman A.D., Abdulkadir S.J.

    Published 2025
    “…Thus, developing an effective routing algorithm to optimize network functionality is a big concern. …”
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  4. 4
    Multi-objective optimization for integrated task scheduling and load balancing in fog computing for IoT applications

    Multi-objective optimization for integrated task scheduling and load balancing in fog computing for IoT applications by Rafique, Majid

    Published 2025
    “…By using a task scheduling and offloading method, the FOCS algorithm arranges data according to size and sends it to the appropriate fog nodes. …”
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  5. 5
    Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm

    Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

    Published 2023
    “…In reducing the learning complexity, a genetic algorithm was implemented to optimize the logical rule throughout the learning phase in performing a 2-satisfiability-based reverse analysis method, implemented during the learning phase as this method was compared. …”
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  6. 6
    Edge assisted crime prediction and evaluation framework for machine learning algorithms

    Edge assisted crime prediction and evaluation framework for machine learning algorithms by Adhikary, Apurba, Murad, Saydul Akbar, Munir, Md Shirajum, Choong Seon, Hong Seong

    Published 2022
    “…To anticipate occurrences, ML methods such as Decision Trees, Neural Networks, K-Nearest Neighbors, and Impact Learning are being utilized, and their performance is compared based on the data processing and modification used. …”
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  7. 7
    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks

    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

    Published 2015
    “…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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  8. 8
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  9. 9
    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying

    Intelligent image noise types recognition and denoising system using deep learning / Khaw Hui Ying by Khaw , Hui Ying

    Published 2019
    “…To classify image noise type, the CNN trained with Backpropagation (BP) algorithm and Stochastic Gradient Descent (SGD) optimization technique are implemented. …”
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  10. 10
    Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli

    Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli by Rosli, Mohamed Syazwan Asyraf

    Published 2022
    “…Meanwhile, the Adam optimizer with a detailed learning rate and momentum fine-tuning provides sufficient convergence rate and assisting YOLOv5s achieve better performance of mAP which is 0.6% higher than SGD implementation and 13.72% better than original author for The Brackish Dataset implementation. …”
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  11. 11
    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…The use of SSL framework also reduces the need for labeled data during training and significantly decreases training time. …”
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  12. 12
    Implementation of Biological Sprouting Algorithm for NoC Fault Tolerance

    Implementation of Biological Sprouting Algorithm for NoC Fault Tolerance by Sethi, Muhammad Athar Javed, Hussin, Fawnizu Azmadi, Hamid, Nor Hisham

    Published 2013
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  13. 13
    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
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  14. 14
    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre

    A study of fluctuations and confidence of implementation in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2018
    “…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
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  15. 15
    A study of fluctuations in genetic algorithm optimized network in data centre

    A study of fluctuations in genetic algorithm optimized network in data centre by Nurika, O., Hassan, M.F., Zakaria, N., Jung, L.T.

    Published 2017
    “…Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. …”
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  16. 16
    Traffic management algorithms for LEO satellite networks

    Traffic management algorithms for LEO satellite networks by Huyop @ Ayop, Fahrul Hakim

    Published 2016
    “…In order to evaluate the proposed algorithm, a series of experiments to implement Discrete Event Simulation (DES) of a LEO satellite network by using ns-2 and C/C++ are conducted. …”
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  17. 17
    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm

    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm by Zeni, Saltihie

    Published 2012
    “…This document is a study about LEACH algorithm where the implementation was done using OMNeT++ network simulator to study the performance of this algorithm in term of network lifetime. …”
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  18. 18
    A semi-synchronous label propagation algorithm with constraints for community detection in complex networks

    A semi-synchronous label propagation algorithm with constraints for community detection in complex networks by Chin, J.H., Ratnavelu, K.

    Published 2017
    “…The performance of the proposed algorithm is evaluated on various benchmark and real-world networks. …”
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  19. 19
    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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  20. 20
    Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm

    Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

    Published 2024
    “…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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