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  1. 1
    Energy-efficient base station transmission design for green 5G massive MIMO and hybrid networks

    Energy-efficient base station transmission design for green 5G massive MIMO and hybrid networks by Khodamoradi, Vahid

    Published 2021
    “…Then, a new corresponding iterative EE optimization algorithm is proposed based on the BSTPA model to further improve the system’s EE. …”
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  2. 2
    Reactive memory model for ant colony optimization and its application to TSP

    Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2014
    “…The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model.Based on the results, Max-Min Ant System has been chosen as the base for the modification.The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.…”
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  3. 3
    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks

    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    Published 2013
    “…However, mobility in WiMAX system is still an issue when a mobile station (MS) moves and its connection is handed over between base stations (BSs). …”
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  4. 4
    Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks

    Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks by Al-Humairi, Ali Zuhair Abdulameer

    Published 2009
    “…This thesis also proposes a centralized scheduling algorithm that can avoid the collision by constructing routing path with multi-slot single transceiver system for WiMAX mesh networks. …”
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  5. 5
    Adaptive resource allocation algorithms with QoS support in OFDMA-based WiMAX networks

    Adaptive resource allocation algorithms with QoS support in OFDMA-based WiMAX networks by Alsahag, Ali Mohamemed Mansor

    Published 2014
    “…This thesis presents four main contributions for QoS provisioning which are robust, scalable, and can be successfully executed in WiMAX system. The first and second contributions are two slot resource allocation algorithms for OFDMA downlink (DL) scheduling, namely Weighted-rate Adaptive Slot Allocation (WASA) and Feedback Delay-based Slot Allocation (FDSA). …”
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  6. 6
    Adaptive and optimized radio resource allocation algorithms for OFDMA based networks

    Adaptive and optimized radio resource allocation algorithms for OFDMA based networks by Saadat, Md. Nazmus

    Published 2015
    “…Thus, in this thesis, an adaptive and optimized radio resource allocation algorithm (AORAA) with cross-layer mechanism is proposed. …”
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  7. 7
    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network

    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

    Published 2010
    “…In addition, the proposed algorithm improved the system throughput up to 68% in the multi-transceiver system and 28% in the single-transceiver system.…”
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  8. 8
    Analysis of optimizers on AlexNet architecture for face biometric authentication system

    Analysis of optimizers on AlexNet architecture for face biometric authentication system by Mat Ariff, Noor Azwana, Ismail, Amelia Ritahani, Abdul Aziz, Normaziah, Amir Hussin, Amir 'Aatieff

    Published 2022
    “…The experiment shows AdaMax performs well when compared to the other optimizers on the proposed dataset.…”
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  9. 9
    Digital beamforming implementation of switch-beam smart antenna system by using integrated digital signal processor and field-programmable gate array

    Digital beamforming implementation of switch-beam smart antenna system by using integrated digital signal processor and field-programmable gate array by Vakilian, Vida

    Published 2008
    “…Also, for more antenna radiation pattern optimization, the sidelobe cancellation is performed base on the chebyshev algorithm. …”
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  10. 10
    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture

    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

    Published 2010
    “…A new detection algorithm based on QR decomposition, denoted as LC-QR, is proposed. …”
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  11. 11
    Antenna design using left-handed materials

    Antenna design using left-handed materials by Abd. Rahman, Tharek, Abdolee, Reza

    Published 2008
    “…In addition, the system performs sidelobe cancellation base on the chebyshev algorithm to optimize the antenna radiation pattern. …”
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  12. 12
    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios

    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

    Published 2015
    “…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. …”
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  13. 13
    Antenna design using left-handed materials

    Antenna design using left-handed materials by Abd. Rahman, Tharek, Ngah, Razali, Ahmad, Mohd. Riduan, Abdolee, Reza, Leow, Chee Yen, I. A. Omer, Abdusamea, Osman Elsayed, Waiel Elsayed, Yusuf, Yusuf Ali, Pon, Lai Ly

    Published 2008
    “…In addition, the system performs sidelobe cancellation base on the chebyshev algorithm to optimize the antenna radiation pattern. …”
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  14. 14
    A smart spectrum access technique for dynamic multi-hop routing in cognitive radio-based disaster response networks

    A smart spectrum access technique for dynamic multi-hop routing in cognitive radio-based disaster response networks by Khaled F. I, Alaqad

    Published 2022
    “…The multi-hop route selection is executed using the Hybrid Spiral Penguin Optimization (HSPO) algorithm based on the decision made by the DE-D2PG. …”
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  15. 15
    Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches

    Reactive max-min ant system: An experimental analysis of the combination with K-OPT local searches by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

    Published 2015
    “…The exploration versus exploitation dilemma rises in ACO search.Reactive max-min ant system algorithm is a recent proposition to automate the exploration and exploitation.It memorizes the search regions in terms of reactive heuristics to be harnessed after restart, which is to avoid the arbitrary exploration later.This paper examined the assumption that local heuristics are useless when combined with local search especially when it applied for combinatorial optimization problems with rugged fitness landscape.Results showed that coupling reactive heuristics with k-Opt local search algorithms produces higher quality solutions and more robust search than max-min ant system algorithm.Well-known combinatorial optimization problems are used in experiments, i.e. traveling salesman and quadratic assignment problems. …”
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  16. 16
    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem

    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

    Published 2021
    “…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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  17. 17
    Maximum 2-satisfiability in radial basis function neural network

    Maximum 2-satisfiability in radial basis function neural network by Shehab Abdulhabib Alzaeemi, Saratha Sathasivam, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor

    Published 2020
    “…In this study, the effectiveness of RBFNN-MAX2SAT can be estimated by evaluating the proposed models with testing data sets. …”
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  18. 18
    Fractal coding of bio-metric image for face authentication

    Fractal coding of bio-metric image for face authentication by Ahadullah, Md

    Published 2021
    “…However, the existing strategy, which comprises two major phases and is based on the partition iterated function system, can be altered. …”
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  19. 19
    A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru

    A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru by Rahmad Ramadhan, Laska, Anne Mudya, Yolanda

    Published 2024
    “…Data preprocessing plays a crucial role in enhancing the performance of machine learning algorithms for classification tasks. …”
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  20. 20
    Data normalization techniques in swarm-based forecasting models for energy commodity spot price

    Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

    Published 2014
    “…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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