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  1. 1
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…Finally, the proposed CS hybrid variants such as; HACPSO, HACPSO-BP, HACPSO-LM, CSBP, CSLM, CSERN, and CSLMERN are evaluated and compared with conventional Back propagation Neural Network (BPNN), Artificial Bee Colony Neural Network (ABCNN), Artificial Bee Colony Back propagation algorithm (ABC-BP), and Artificial Bee Colony Levenberg-Marquardt algorithm (ABC-LM). …”
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  2. 2
    OTS: an optimal tasks scheduling algorithm based on QoS in cloud computing network

    OTS: an optimal tasks scheduling algorithm based on QoS in cloud computing network by Alhakimi, Mohammed Ameen, Latip, Rohaya

    Published 2019
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  3. 3
    A particle swarm optimization and min-max­-based workflow scheduling algorithm with QoS satisfaction for service-­oriented grids

    A particle swarm optimization and min-max­-based workflow scheduling algorithm with QoS satisfaction for service-­oriented grids by Ambursa, Faruku Umar, Latip, Rohaya, Abdullah, Azizol, K. Subramaniam, Shamala

    Published 2017
    “…The algorithm selects the best scheduling solutions based on the proposed constraint-handling strategy. …”
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  4. 4
    An optimal tasks scheduling algorithm based on QoS in cloud computing network

    An optimal tasks scheduling algorithm based on QoS in cloud computing network by Alhakimi, Mohammed Ameen Mohammed Abdo

    Published 2017
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  5. 5
    Fair bandwidth assignment in hierarchical scheduling for mobile WiMAX system

    Fair bandwidth assignment in hierarchical scheduling for mobile WiMAX system by Alsahag, Ali Mohammed Mansoor, Mohd Ali, Borhanuddin, Noordin, Nor Kamariah, Mohamad, Hafizal

    Published 2011
    “…In this paper, we propose a fair bandwidth assignment algorithm that allocates the bandwidth among different services classes based on a hierarchical scheduler. …”
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  6. 6
    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. …”
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  7. 7
    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
    “…It reduces the number of handovers by 29.7% and 26.9%, respectively, compared to the conventional RSSI based handover algorithm and the previous worked, mobility improved handover (MIHO) algorithm. …”
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  8. 8
    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin

    Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin by Alsahag, Ali Mohammed, Mohd Ali, Borhanuddin, Noordin, Nor Kamariah, Mohamad, Hafizal

    Published 2014
    “…One example of such a network is called WiMAX which is driven by WiMAX Forum based on IEEE 802.16 Wireless MAN standard. …”
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  9. 9
    Cross-layer design using multi-channel system in WiMAX mesh networks

    Cross-layer design using multi-channel system in WiMAX mesh networks by Al-Hemyari, Ali, Ng, Chee Kyun, Noordin, Nor Kamariah, Ismail, Alyani, Khatun, Sabira, Jamuar, Sudhanshu Shekhar

    Published 2008
    “…The WiMAX mesh networks based on IEEE 802.16 standard is a key topology for the next generation wireless networking. …”
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  10. 10
    A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments

    A comparative evaluation of heuristic and metaheuristic job scheduling algorithms for optimized resource management in cloud environments by Haque, Najmul, Zafril Rizal, M. Azmi, Murad, Saydul Akbar

    Published 2026
    “…This study provides a comprehensive analysis and comparison of six prevalent scheduling algorithms, namely FCFS, SJF, LJF, EDF, Max-Min, and PSO, under varying cloudlet loads of 200,400,600,800, and 1000. …”
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  11. 11
    Max degree around (MDA) algorithm: a smart and efficient approximate algorithm for Vertex cover and independent set problems

    Max degree around (MDA) algorithm: a smart and efficient approximate algorithm for Vertex cover and independent set problems by Fayaz, Muhammad, Arshad, S, Shah, A.S, Shah, Asadullah

    Published 2016
    “…Hence, these approaches regularly fail to provide optimal results on specific graph instances. These problems motivated to propose Max Degres Around (MDA) approximation algorithm for the MVC problem. …”
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  12. 12
    Enhanced ABD-LSSVM for energy fuel price prediction

    Enhanced ABD-LSSVM for energy fuel price prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2013
    “…The purposes of enhancement are to enrich the searching behavior of the bees in the search space and prevent premature convergence.Such an approach is used to improve the performance of the original ABC in optimizing the embedded hyper-parameters of Least Squares Support Vector Machines(LSSVM).Later on, a procedure is put forward to serve as a prediction tool to solve prediction task.To evaluate the efficiency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN).From the experiment that was conducted, the proposed eABC-LSSVM shows encouraging results in optimizing parameters of interest by producing higher prediction accuracy for employed time series data.…”
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  13. 13
    Enhanced ABC-LSSVM For Energy Fuel Price Prediction

    Enhanced ABC-LSSVM For Energy Fuel Price Prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

    Published 2014
    “…Later on, a procedure is put forward to serve as a prediction tool to solve prediction task. To evaluate the effi ciency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). …”
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  14. 14
    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
    “…WiMAX (Worldwide Interoperability for Microwave Access) based wireless mesh network (WMN) aims to provide broadband wireless last-mile access. …”
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  15. 15
    Improving QoS Of WiMAX By ondemand bandwidth allocation based on PMP mode

    Improving QoS Of WiMAX By ondemand bandwidth allocation based on PMP mode by Sun, Zhen Tao, Gani, Abdullah, Sun, Xiu Ying, Liu, Ning

    Published 2011
    “…In order to improve the QoS of WiMAX demand, the total capacity of WiMAX system must be optimized. …”
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  16. 16
    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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  17. 17
    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
    “…FADRR is fully dynamic with fuzzy logic based approach and adaptive deadline-based scheme for various service class traffics in the base station (BS). …”
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  18. 18
    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches

    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches by Mohd Pauzi, Nur Fazlinda

    Published 2015
    “…The performance of the ABC algorithm was evaluated through three different onlooker approaches i.e. method 3+0+0 (three onlooker bees are dedicated to the best employee bee), method 2+1+0 (two onlooker bees are dedicated to the best employee bee and one onlooker bee is dedicated to second best employee bee) and method 1+1+1 (one onlooker bee is dedicated to each employee bee). …”
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  19. 19
    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC)

    Leaf lesion classification (LLC) algorithm based on artificial bee colony (ABC) by Ahmad, Faudziah, Ku-Mahamud, Ku Ruhana, Sainin, Mohd Shamrie, Airuddin, Ahmad

    Published 2015
    “…The algorithm involved three main steps, filtration, recognition and detection.Artificial Bee Colony, Fuzzy Logic, Otsu and Geometry formula were incorporated to achieve the goal.Ninety-four leaf images were used in this algorithm combination experiment.The study was conducted in four phases, filtration, recognition, detection and evaluation.Comparison was made with four other algorithms, Otsu, Canny, Robert and Sobel. …”
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  20. 20
    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
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