Search Results - (( weight distribution rate algorithm ) OR ( (parameter OR parameters) estimation poe algorithm ))

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  1. 1

    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
    “…The technique allocates available network resources based on application's priority, whereas the algorithm makes scheduling decision based on dynamic weighting factors of multi-criteria to satisfy the demands (delay, past average throughput and instantaneous transmission rate) of quality of service. …”
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    Article
  2. 2

    A novel scheduling algorithm based on game theory and multicriteria decision making in LTE network by Hindia, M.N., Reza, A.W., Noordin, K.A.

    Published 2015
    “…On the first level, bankruptcy and shapely value algorithm fairly distribute the resources among smart grid applications. …”
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    Article
  3. 3

    Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements by Ramadhan, Mazen Farid Ebrahim

    Published 2022
    “…Second, to propose a minimum-weight-based multi-objective algorithm (MOS-MWO), which is based on Particle Swarm Optimization (PSO) technique and a novel minimum weight optimization approach, that improves user’s QoS satisfaction. …”
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    Thesis
  4. 4

    Utility-based non-cooperative power control game in wireless environment / Yousef Ali Mohammed Al-Gumaei by Yousef Ali, Mohammed Al-Gumaei

    Published 2017
    “…Moreover, these algorithms have a relatively fast convergence rate and guarantee that all users can achieve their required QoS.…”
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    Thesis
  5. 5

    Energy-efficient communications in wireless powered cognitive radio networks based on game theory / Fadhil Mukhlif Aswad Al-Obaidy by Fadhil Mukhlif , Aswad Al-Obaidy

    Published 2020
    “…Furthermore, the convergence rate of these algorithms is relatively fast which can help in guaranteeing that all users achieve their required QoS. …”
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    Thesis
  6. 6

    Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

    Published 2016
    “…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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    Article
  7. 7

    Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

    Published 2016
    “…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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    Article
  8. 8

    Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

    Published 2016
    “…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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    Article
  9. 9

    Multiobjective optimization using particle swarm optimization with non-Gaussian random generators by Ganesan, T., Vasant, P., Elamvazuthi, I.

    Published 2016
    “…The stochastic engines operate using the Weibull distribution, Gamma distribution, Gaussian distribution and a chaotic mechanism. …”
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    Article
  10. 10

    A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Mohd Radzi, Mohd Amran, Mailah, Nashiren Farzilah

    Published 2013
    “…The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. …”
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  11. 11

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…Then different features are derived from the segmented region using Gray Intensity Co-Occurrence Distribution Matrix (GICDM) which is processed by applying a proposed Supervised Jaya Optimized Rough Set based Feature Selection (SJORSFS) algorithm. …”
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  12. 12

    Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

    Published 2025
    “…Data vectors are generated based on the time needed, sequential and parallel candidate feature data are obtained, and the data rate is combined. After classifying the time set using the canopy with the K-means algorithm and the vector representation weighted by factors, the clustering impact is assessed using purity, precision, recall, and F value. …”
    Article
  13. 13

    Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

    Published 2015
    “…On the first level, bankruptcy and shapely value algorithm fairly distribute resources among smart grid applications. …”
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    Thesis
  14. 14

    Optimal resource allocation for NOMA wireless networks by Albogamy, Fahad R., Aiyashi, M. A., Hashim, Fazirul Hisyam, Imran Khan, Choi, Bong Jun

    Published 2022
    “…This research developed an efficient technique based on conjugate gradient to solve the problem of downlink power distribution. The major goal is to maximize the users’ maximum weighted sum rate. …”
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    Article
  15. 15

    On the Modelling of the Mobile WiMAX (IEEE 802.16e) Uplink Scheduler by Mohd Ali, Darmawaty, Dimyati, Kaharudin

    Published 2010
    “…The results of the analysis are useful in obtaining or testing approximation for individual mean waiting time especially when queues are asymmetric (where each queue may have different stochastic characteristic such as arrival rate and service time distribution) and when their number is large (more than 2 queues).…”
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    Article
  16. 16

    A krill herd behaviour inspired load balancing of tasks in cloud computing by Hasan, Raed Abdulkareem, Mohammed, Muamer N.

    Published 2017
    “…The speed, task cost, and weight of the tasks were first determined, after which, the Krill herd optimization algorithm was for the load balancing based on the measured parameters. …”
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  17. 17

    Multi-objective optimization of a three-fluid hollow fiber membrane dehumidifier for energy-efficient drying applications by Tejes, P.K.S., Naik, B. Kiran, Dasore, Abhishek, Hashim, Norhashila

    Published 2025
    “…Two conflicting objectives, energy transfer across membrane column (Emc) and vapor removal rate (υVRR), were optimized utilizing the NSGA-II algorithm and fuzzy clustering with weighted cumulative probability distribution (FC-WCPD). …”
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    Article
  18. 18

    A novel approach to data mining using simplified swarm optimization by Wahid, Noorhaniza

    Published 2011
    “…In this thesis, a novel Simplified Swarm Optimization (SSO) algorithm is proposed as a rule-based classifier and for feature selection. …”
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    Thesis
  19. 19

    Design And Analysis Of Modified-Proportional Fair Scheduler For LTELTE-Advanced by Ismail, Mohd Khairy

    Published 2016
    “…So, the mechanism applied in PF scheduler is to weight the current data rate achievable by a UE by the average rate received by a UE. …”
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  20. 20

    Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

    Published 2010
    “…These results show that,for all the arrays (2D and 3D) except 3D pole - dipole data, resilient propagation is the most efficient algorithm for training the DC resistivity data. In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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    Thesis