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  1. 1

    Improved chemotaxis differential evolution optimization algorithm by Yıldız, Y. Emre, Altun, Oğuz, Topal, A. Osman

    Published 2015
    “…The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). …”
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    Conference or Workshop Item
  2. 2

    An FPGA implementation of exp-bet scheduling algorithm in LTE networks / Yusmardiah Yusuf by Yusuf, Yusmardiah

    Published 2017
    “…It is performed by the scheduling algorithm implemented in the Long Term Evolution (LTE) base station, Evolved Node B. …”
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    Thesis
  3. 3

    Enhanced Quality of Service of Cell-Edge User by Extending Modified Largest Weighted Delay First Algorithm in LTE Networks by Chayon, H.R., Dimyati, K., Ramiah, H., Reza, A.W.

    Published 2017
    “…It includes the distance of the user from attached eNB, received Signal to Interference plus Noise Ratio (SINR) and error probability into the original algorithm. The simulated results are compared with other well-known algorithms and the comparison shows that the proposed algorithm enhances overall 56.23% of cell-edge user throughput and significantly improves the average user throughput, fairness index, and spectral efficiency.…”
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    Article
  4. 4

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq

    Published 2024
    “…The paper presents a method for autotuning attitude PID for a quadplane UAV using differential evolution (DE), X-Plane simulation, and neural network (NN)-based system identification. …”
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    Article
  5. 5

    Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm by Pairan, Mohammad Fahmi, Shamsudin, Syariful Syafiq, Yaakub, Mohd Fauzi

    Published 2024
    “…The paper presents a method for autotuning attitude PID for a quadplane UAV using differential evolution (DE), X-Plane simulation, and neural network (NN)-based system identification. …”
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    Article
  6. 6

    The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robo... by Moloody, Abbas, As’arry, Azizan, Hong, Tang Sai, Raja Kamil, ., Zolfagharian, Ali

    Published 2025
    “…Simulation results illustrate the effectiveness of the proposed MDEOA strategy which is significantly and quite satisfactory about 25 to 30 (%) better than comparing to the other algorithms in improvement stabilization and vibration control of CSLRFM.…”
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    Article
  7. 7

    Fair scheduling algorithm in LTE-advanced networks by Al-Shibly, Mohammed Abuljawad M, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Chebil, Jalel, Zyoud, Alhareth, Alfaqawi, Mohammed I M

    Published 2015
    “…The novel algorithm is implemented in a PS module for LTE-Advanced via system level simulations. …”
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    Article
  8. 8

    HARQ aware scheduling algorithm for the downlink LTE system by Mohd. Ramli, Huda Adibah, Sandrasegaran, Kumbesan, Basukala, Riyaj, Afrin, Toyoba Sohana

    Published 2011
    “…Simulation results show that this algorithm outperforms modified-largest weighted delay first (M-LWDF) algorithm by minimizing the number of lost packets, maintaining a low queuing delay and maximizing effective user throughput.…”
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    Proceeding Paper
  9. 9

    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

    Published 2015
    “…Based on simulation results, it is concluded that the proposed energy-efficient scheduling has led the eNodeB to transmit with low power through modified MCS. …”
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    Thesis
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    Accurate numerical treatment on a stochastic SIR epidemic model with optimal control strategy by Ghosh, Indranil, Rashid, Muhammad Mahbubur, Ghosh, Pallabi, Mawa, Shukranul, Roy, Rupal, Ahsan, Md Manjurul, Gupta, Kishor Datta

    Published 2022
    “…We furnish numerical and graphical simulation combined with explicit series solutions of the proposed model using the New Iterative Method (NIM) and Modified New Iterative Method (MNIM). …”
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    Article
  12. 12

    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

    Published 2019
    “…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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    Thesis
  13. 13

    Group formation using genetic algorithm by Che Ani, Zhamri, Husin, Mohd Zabidin, Yasin, Azman

    Published 2009
    “…However, due to lack of programming skills especially in Java programming language and the inability to have meetings frequently among the group members,most of the students’ software project cannot be delivered successfully.To solve this problem, systematic group formation is one of the initial factors that should be considered to ensure that every group consists of quality individuals who are good in Java programming and also to ensure that every group member in a group are staying closer to each other.In this research, we propose a method for group formation using Genetic Algorithms, where the members for each group will be generated based on the students’ programming skill and location of residential colleges.…”
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    Monograph
  14. 14

    Design And Development Of Modified-Proportional Fair Scheduler For LTE/LTE-Advanced by Mohd Khairy, Ismail, Azmi, Awang Md Isa, Mohd Nor, Husain, Muhammad Syahrir, Johal, Mohd Riduan, Ahmad

    Published 2016
    “…Simulation results show that the Modified-PF scheduler provides the best performance in terms of throughput and spectral efficiency with comparale fairness as compared to RR and PF schedulers. …”
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    Article
  15. 15

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. Estimated location is reported as physical location and symbolic location. …”
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    Thesis
  16. 16

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

    Published 2017
    “…The developed algorithm is simulated in LTE-Sim simulator released 5 in terms of three QoS metrics (1) Packet Loss Ratio (2) Delay (3) Throughput. …”
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    Thesis
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    A novel LTE scheduling algorithm for green technology in smart grid by Hindia, M.N., Reza, A.W., Noordin, K.A., Chayon, M.H.R.

    Published 2015
    “…In terms of fairness, the proposed algorithm shows 3, 7 and 9 better performance compared to exponential rule (EXP-Rule), modified-largest weighted delay first (M-LWDF) and exponential/PF (EXP/PF), respectively.…”
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    Article
  20. 20

    An experimental study on the mechatronics design and implementation of an intelligent active vibration control system for a CSLRFM by Moloody, Abbas, As’arry, Azizan, Sai Hong, Tang, Kamil, Raja, Md. Zain, Mohd Zarhamdy, Bahiuddin, Irfan

    Published 2025
    “…RFMs offer benefits such as lighter weight and faster response but present challenges in motion and vibration control under disturbances. To address this, a Modified Differential Evolution Optimization Algorithm (MDEOA) tunes a PID controller to improve vibration suppression. …”
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    Article