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  1. 1
    Development of a novel component carrier selection algorithm in long term evolution-advanced (LTE-A) with carrier aggregation

    Development of a novel component carrier selection algorithm in long term evolution-advanced (LTE-A) with carrier aggregation by Al Katsha, Mhd Zaher, Mohd. Ramli, Huda Adibah

    Published 2017
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  2. 2
    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution

    Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution by Ganesan, T., Elamvazuthi, I., Shaari, K.Z.K., Vasant, P.

    Published 2014
    “…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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  3. 3
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2018
    “…This thesis proposed an efficient algorithm, namely, the Quality of Service (QoS) and Energy Efficient Aware (QEEA). …”
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  4. 4
    Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applications

    Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica... by Stonier, A.A., Chinnaraj, G., Kannan, R., Mani, G.

    Published 2021
    “…Harmonics are used to estimate the quality of output voltage and measuring the improvement of the power quality. …”
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  5. 5
    Resource allocation in coordinated multipoint long term evolution-advanced networks

    Resource allocation in coordinated multipoint long term evolution-advanced networks by Katiran, Norshidah

    Published 2015
    “…The resource allocation algorithm is developed through three phases, namely Low-Complexity Resource Allocation (LRA), Optimized Resource Allocation (ORA) and Cross-Layer Design of ORA (CLD-ORA). …”
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  6. 6
    Efficient radio resource management algorithms for downlink long term evolution networks

    Efficient radio resource management algorithms for downlink long term evolution networks by Mamman, Maharazu

    Published 2018
    “…Hence, the major problem is developing a scheduling algorithm which creates a trade-off between the system performances. …”
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  7. 7
    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff

    Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

    Published 2017
    “…This thesis proposed an efficient algorithm, namely, the Quality of Service (QoS) and Energy Efficient Aware (QEEA). …”
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  8. 8
    On fractional and semi-soft handover in long term evolution(LTE) networks

    On fractional and semi-soft handover in long term evolution(LTE) networks by Hussein, Yaseein Soubhi, Mohd Ali, Borhanuddin, Varahram, Pooria

    Published 2011
    “…In this paper a hybrid HO algorithms called semi-soft handover (SSHO) and fractional soft handover (FSHO) in long term evolution (LTE) system are studied. …”
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  9. 9
    A study on channel and delay-based scheduling algorithms for live video streaming in the fifth generation long term evolution-advanced

    A study on channel and delay-based scheduling algorithms for live video streaming in the fifth generation long term evolution-advanced by Abdul Latiff, Liza, Mohd Ramli, Huda Adibah, Asnawi, Ani Liza, Abdul Wahab, Nur Haliza

    Published 2022
    “…These algorithms were developed for use in the legacy wireless networks and minor changes were made to enable these algorithms to perform packet scheduling in the downlink 5G LTE-A. …”
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  10. 10
    Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity

    Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

    Published 2018
    “…Consequently, this paper proposes a ranking self-adaptive differential evolution (rsaDE) feature selection algorithm. The proposed algorithm is capable of selecting the optimal feature subsets while improving the recognition of acceleration activity using a minimum number of features. …”
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  11. 11
    Evolution of transformer health index in the form of mathematical equation

    Evolution of transformer health index in the form of mathematical equation by Azmi, Akma, Jasni, Jasronita, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin

    Published 2017
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  12. 12
    Enhanced handover mechanism in long term evolution (LTE) networks

    Enhanced handover mechanism in long term evolution (LTE) networks by Hussein, Yaseein Soubhi, Mohd Ali, Borhanuddin, Varahram, Pooria, Sali, Aduwati

    Published 2011
    “…To address these challenges intensive researches are being carried out to define algorithms that can handle the HO decisions based on user equipment (UE) requirements and quality of service (QoS) expectations. …”
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  13. 13
    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems

    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
    “…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. Since the developed downlink scheduler and the partial feedback scheme affect the QoS, self-configured versions of both algorithms are developed to provide QoS provisioning. …”
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  14. 14
    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network

    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network by Usman, I. H., Nordin, N. K., Omizegba, E. E., Sali, A., Rasid, M. F. A., Hashim, F.

    Published 2021
    “…This implied that the network operating under the proposed TVWS algorithm presented low radio link decoding errors when compared with the validation algorithms MIF and CONV. …”
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  15. 15
    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decision-making

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…VL-WIDE was also integrated with the solution selection model based on the Analytical Hierarchical Process (AHP) that considers decision-maker preference for the optimized objectives. Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. …”
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  16. 16
    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 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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  17. 17
    Parameter extraction of solar photovoltaic modules using penalty-based differential evolution

    Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

    Published 2012
    “…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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  18. 18
    Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation

    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
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  19. 19
    Seed disperser ant algorithm for optimization / Chang Wen Liang

    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The Seed Disperser Ant Algorithm (SDAA) is developed based on the evolution or expansion process of Seed Disperser Ant (Aphaenogaster senilis) colony. …”
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  20. 20
    Proposed algorithm for scheduling in computational grid using backfilling and optimization techniques

    Proposed algorithm for scheduling in computational grid using backfilling and optimization techniques by Dakkak, Omar, Awang Nor, Shahrudin, Che Mohamed Arif, Ahmad Suki

    Published 2016
    “…In recent years, the fast evolution in the industry of computer hardware such as the processors, has led the application developers to design advanced software's that require massive computational power.Thus, grid computing has emerged in order to handle the computational power demands requested by the applications.Quality of service (QoS) in grid is highly required in order to provide a high service level to the users of Grid.Several interactions events are involved in determining the QoS level in grid such as; allocating the resources for the jobs, monitoring the performance of the selected resources and the computing capability of the available resources. …”
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