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  1. 1
    Neighbour-based on-demand routing algorithms for mobile ad hoc networks

    Neighbour-based on-demand routing algorithms for mobile ad hoc networks by Ejmaa, Ali Mohamed E.

    Published 2017
    “…All the three proposed algorithms are evaluated using discrete event simulation, in particular Network Simulator tool (NS2), and compared with the latest routing algorithm (NCPR ) and fundamental algorithm (AODV) using five performance metrics. …”
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    Thesis
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  2. 2
    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS

    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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  3. 3
    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation

    Machine learning methods for herschel-bulkley fluids in annulus: Pressure drop predictions and algorithm performance evaluation by Kumar, A., Ridha, S., Ganet, T., Vasant, P., Ilyas, S.U.

    Published 2020
    “…The impact of each input parameter affecting the pressure drop is quantified using the RF algorithm. © 2020 by the authors.…”
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  4. 4
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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  5. 5
    Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm

    Performance Enhancement of Routing Protocols in Mobile Wireless Ad-Hoc Networks Using Fuzzy Reasoning Algorithm by Natsheh, Essam Fathi

    Published 2006
    “…Finally, in the last method fuzzy reasoning is used for network congestion estimation and estimating time to start dropping incoming packets. …”
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  6. 6
    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study

    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

    Published 2010
    “…This study aims to develop a universal artificial neural network model for estimating pressure drop at pipelines under multiphase flow conditions. …”
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  7. 7
    Performance study of large block forward error correction with random early detection queue policy

    Performance study of large block forward error correction with random early detection queue policy by Almomani, Omar, Ghazali, Osman, Hassan, Suhaidi

    Published 2009
    “…FEC is a technique that uses redundant packet to reconstruct the dropped packet, while RED is an active queue management algorithm. …”
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  8. 8
    Affine projection algorithm for speech enhancement using controlled projection order

    Affine projection algorithm for speech enhancement using controlled projection order by Noor, Ali O. Abid

    Published 2020
    “…The MSE of the proposed VPAPA method drops to -65 dB in steady state compared to -20 dB using NLMS and just below -30 dB using standard APA with projection order of 8, while the powerful RLS reaches around -60dB under the same environment. …”
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  9. 9
    A study on the application of discrete curvature feature extraction and optimization algorithms to battery health estimation

    A study on the application of discrete curvature feature extraction and optimization algorithms to battery health estimation by Goh, Hui Hwang, An, Zhen, Zhang, Dongdong, Dai, Wei, Kurniawan, Tonni Agustiono, Goh, Kai Chen

    Published 2024
    “…The error evaluation metrics used are mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE). …”
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  10. 10
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  11. 11
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
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  12. 12
    A study on the application of discrete curvature feature extraction and optimization algorithms to battery health estimation

    A study on the application of discrete curvature feature extraction and optimization algorithms to battery health estimation by Hui Hwang Goh, Hui Hwang Goh, Zhen An, Zhen An, Dongdong Zhang, Dongdong Zhang, Wei Dai, Wei Dai, Tonni Agustiono Kurniawan, Tonni Agustiono Kurniawan, Kai Chen Goh, Kai Chen Goh

    Published 2024
    “…The error evaluation metrics used are mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE). …”
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  13. 13
    A comparative study and simulation of object tracking algorithms

    A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

    Published 2020
    “…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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  14. 14
    Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm

    Optimal Charging Strategy for Plug-in Hybrid Electric Vehicle Using Evolutionary Algorithm by Mohd Redzuan, Ahmad, Ismail, Musirin, M. M., Othman

    Published 2014
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  15. 15
    A scene invariant convolutional neural network for visual crowd counting using fast-lane and sample selective methods

    A scene invariant convolutional neural network for visual crowd counting using fast-lane and sample selective methods by Teoh, Shen Khang

    Published 2023
    “…Existing research usually follow the training-testing protocol within a single dataset and the accuracy drops when conducting cross-dataset evaluation. Density map prediction methodology is widely used but it has drawbacks in ground truth generation and the use of Euclidean distance results in low quality density map. …”
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    Final Year Project / Dissertation / Thesis
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  16. 16
    Algorithm of the effect of g-jittren on free convection adjacent to a stretching sheet

    Algorithm of the effect of g-jittren on free convection adjacent to a stretching sheet by Shafie, Sharidan

    Published 2009
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    Monograph
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  17. 17
    Evaluation of Formation Damage from Transient Pressure Analysis: Unsteady State Skin Factor

    Evaluation of Formation Damage from Transient Pressure Analysis: Unsteady State Skin Factor by El-Khatib, Noaman A.F.

    Published 2011
    “…The developed model and the correlation charts can be used to evaluate the formation damage from well test analysis around the well by estimating both the skin permability and the depth of invasion in the damaged zone. …”
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  18. 18
    Electronic Tongue: Study on the Freshness of Milk

    Electronic Tongue: Study on the Freshness of Milk by Jaafar, Mohamad Nazrin

    Published 2012
    “…After the experiment has been done, the data obtained was used in Matlab for classification purpose. By using the Neural Network algorithm, we are actually able to find the threshold line which actually separates the fresh and spoilt milk into two different regions. …”
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    Final Year Project
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  19. 19
    Artificial intelligent power prediction for efficient resource management of WCDMA mobile network

    Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

    Published 2023
    “…This artificial intelligent call admission control (CAC) was validated using a dynamic WCDMA mobile network simulator. A few comparative results in downlink have shown that our integrated support vector regression assists genetic algorithm (SVRaGA) is capable of predicting next interval power consumption at Node B with low prediction error and improving the quality of service (QoS) by reducing dropped calls. � 2008 IEICE.…”
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  20. 20
    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method

    Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

    Published 2024
    thesis::doctoral thesis
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