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  1. 1
    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling

    Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    Conference Paper
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  2. 2
    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks

    Backhaul load and performance optimality of partial joint processing schemes in LTE-A networks by Kousha, Mohammad

    Published 2014
    “…However, the problem of performance degradation caused by InterCell-Interference (ICI) also raised for cell-edge users. …”
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  3. 3
    Quality of service and scheduling performance optimization in LTE networks / Abubakar Auwal Idris

    Quality of service and scheduling performance optimization in LTE networks / Abubakar Auwal Idris by Abubakar Auwal , Idris

    Published 2017
    “…The future work will consider to simulate multi cell scenario and the system complexity evaluation. …”
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  4. 4
    Handover Decision-Making Algorithm for 5G Heterogeneous Networks

    Handover Decision-Making Algorithm for 5G Heterogeneous Networks by Mark Irwin Goh, Abbas Ibrahim Mbulwa, Hoe, Tung Yew, Aroland Kiring, Chung, Seng Kheau, Ali Farzamnia, Ali Chekima, Manas Kumar Haldar

    Published 2023
    “…The TOPSIS evaluates the network quality and chooses the best network based on user preference. …”
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  5. 5
    Performance evaluation of relay deployment in long term evolution advanced (LTE-A) network / Aminah Najihah Jaafar

    Performance evaluation of relay deployment in long term evolution advanced (LTE-A) network / Aminah Najihah Jaafar by Hasanudin, Siti Farhana

    Published 2014
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  6. 6
    Performance evaluation of LTE scheduling techniques for heterogeneous traffic and different mobility scenarios

    Performance evaluation of LTE scheduling techniques for heterogeneous traffic and different mobility scenarios by Sukeran, Lukmanhakim, Habaebi, Mohamed Hadi, Zyou, Al-Hareth, Ahmed, Musse Mohamud, Hameed, Shihab A, Azman, Amelia Wong, Islam, Md Rafiqul

    Published 2015
    “…In this paper five scheduling algorithms were investigated and their performance was evaluated in terms of Fairness Index, Peak Throughput, Average Throughput and Edge Cell User Throughput. …”
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  7. 7
    Performance evaluation of LTE scheduling techniques for heterogeneous traffic and different mobility scenarios

    Performance evaluation of LTE scheduling techniques for heterogeneous traffic and different mobility scenarios by Sukeran, Lukmanhakim, Habaebi, Mohamed Hadi, Zyoud, Al-Hareth, Musse, Mohamud Ahmed, Hameed, Shihab A., Azman, Amelia Wong, Islam, Md. Rafiqul

    Published 2014
    “…In this paper five scheduling algorithms were investigated and their performance was evaluated in terms of Fairness Index, Peak Throughput, Average Throughput and Edge Cell User Throughput. …”
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    Proceeding Paper
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  8. 8
    Performance evaluation of relay deployment in Long Term Evolution Advanced (LTE-A) network / Aminah Najihah Jaafar

    Performance evaluation of relay deployment in Long Term Evolution Advanced (LTE-A) network / Aminah Najihah Jaafar by Jaafar, Aminah Najihah

    Published 2016
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  9. 9
    A new dynamic code assignment algorithm for joint CDMA and SDMA system

    A new dynamic code assignment algorithm for joint CDMA and SDMA system by Odeh, Nidhal A. S., Khatun, Sabira, Ismail, Alyani, Mohd Ali, Borhanuddin

    Published 2008
    “…The probability of blocking is calculated to evaluate the system performance for different number of users and available codes. …”
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  10. 10
    An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab

    An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

    Published 2020
    “…Firstly, intra-severity classification intended to identify the level of severity of the dysarthric speakers. …”
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  11. 11
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  12. 12
    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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  13. 13
    Efficient radio resource management through coordinated multipoint transmission and carrier aggregation for LTE-advanced / Muhammad Hasibur Rashid Chayon

    Efficient radio resource management through coordinated multipoint transmission and carrier aggregation for LTE-advanced / Muhammad Hasibur Rashid Chayon by Muhammad Hasibur, Rashid Chayon

    Published 2018
    “…The cell-center user gets multiple CCs from the same attached eNodeB (eNB). …”
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  14. 14
    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction

    Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

    Published 2024
    “…In addition, level of care dataset reveals the highest accuracy of 97.15% for MLP and Bagging algorithms and the lowest accuracy of 91.66% for stacking algorithm. …”
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  15. 15
    Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri

    Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri by Masri, Nor Khirda

    Published 2017
    “…The principle of ICLONALG is to select the best cells to be cloned and mutated by calculating similarity measurements of the most competent cells. …”
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  16. 16
    A Predictive Classification Model For Running Injury

    A Predictive Classification Model For Running Injury by Ganesan, Devesh Raj

    Published 2022
    “…The J48, SMO, Random Forest, and Simple Logistic algorithms were used for 10-fold cross validation mode classification benchmarked on the ZeroR baseline algorithm. …”
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    Monograph
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  17. 17
    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms

    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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  18. 18
    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad

    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…This reserarch adapted a methodology of computer vision and algorithms that exploit image segmentation, feature extraction and fuzzy classification to guide the research activities. …”
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  19. 19
    Power line faults classification by neural network train by Ant Colony Optimization

    Power line faults classification by neural network train by Ant Colony Optimization by Nasirudin, Mohd Syafiq

    Published 2017
    “…In This paper it will show the performance for Neural Network and the performance train with Ant Colony Optimization for case of classification. Ant Colony Optimization is a meta-heuristic way to deal with take care of troublesome streamlining issues. …”
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  20. 20
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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