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  1. 1

    Performance analysis of ZigBeePRO network using shortest path algorithm for Distributed Renewable Generation by Islam, Syed Zahurul, Othman, Mohammad Lutfi, Islam, Syed Zahidul

    Published 2021
    “…In this paper, we have analysed the performance of the ZigBeePRO network by applying the shortest path algorithm while delivering energy data from the solar DRG to the SG. …”
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    Article
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    An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms by Ullah, Arif

    Published 2021
    “…The proposed HBAC showed an improved accuracy rate in task distribution and reduced the makespan of VM in a cloud data center. …”
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    Thesis
  4. 4

    Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

    Published 2018
    “…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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    Article
  5. 5

    Improved tree routing protocol in zigbee networks by Al-Harbawi, Mostafa Kamil Abdulhusain

    Published 2010
    “…Many application scenarios require connectivity between WSN’s nodes to transmit the collected data to a sink node. ZigBee is an industrial standard for wireless ad hoc networks based on IEEE 802.15.4. …”
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    Thesis
  6. 6

    Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

    Published 2024
    “…Since it is unrealistic to have a NIRS dataset that can represent unforeseen future changes, an algorithm that can adapt existing data for new samples is worth to be investigated. …”
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    Article
  7. 7

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

    Published 2013
    “…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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    Article
  8. 8

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

    Published 2014
    “…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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    Article
  9. 9

    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

    Published 2023
    “…The GA�RC algorithm showed a periodic reliability percentage of 55.65%, whereas the GA algorithm exhibited the lowest periodic reliability percentage of 23.5%. …”
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    Final Year Project / Dissertation / Thesis
  10. 10

    Data discovery algorithm for scientific data grid environment by Abdullah, Azizol, Othman, Mohamed, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Othman, Abu Talib

    Published 2005
    “…By using this model, we study various discovery algorithms for locating data sets in a data grid system. …”
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    Article
  11. 11

    Binary Vote Assignment on Cloud Quorum Algorithm for Fragmented MyGRANTS Database Replication by Noraziah, Ahmad, Ainul Azila, Che Fauzi, Herawan, Tutut, Zailani, Abdullah

    Published 2015
    “…This paper proposed a new algorithm namely Binary Vote Assignment on Cloud Quorum (BVACQ) in order to handle fragmented database replication in distributed environment. …”
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    Article
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    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

    Published 2018
    “…It still takes a long time to compute the topic distribution of the data. …”
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    Article
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    Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification by Mohammad Zubir, W.M.A., Abdul Aziz, I., Jaafar, J., Hasan, M.H.

    Published 2018
    “…It still takes a long time to compute the topic distribution of the data. …”
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    Article
  15. 15

    A novel binary vote assignment grid quorum algorithm for distributed database fragmentation by Ainul Azila, Che Fauzi, Noraziah, Ahmad, Noriyani, Mohd Zin

    Published 2011
    “…This paper propose a new algorithm namely Binary Vote Assignment on Grid Quorum (BVAGQ) in order to handle data replication and transaction management. …”
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    Conference or Workshop Item
  16. 16

    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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    Article
  17. 17

    Improved genetic algorithm for scheduling divisible data grid application by Kaid, Monir Abdullah Abduh, Othman, Mohamed, Ibrahim, Hamidah, K. Subramaniam, Shamala

    Published 2007
    “…Data Grid technology promises geographically distributed scientists to access and share physically distributed resources such as computing resources, networks, storages, and most importantly data collections for large scale data intensive problems. …”
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    Conference or Workshop Item
  18. 18

    Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad by Saima Gulzar, Ahmad

    Published 2017
    “…Eventually, the workflow is executed. The second algorithm is a variation in first algorithm in which data parallelism is introduced in each partition. …”
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    Thesis
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    Estimation Of Weibull Parameters Using Simulated Annealing As Applied In Financial Data by Hamza, Abubakar

    Published 2023
    “…However, the selection of the most suitable estimators is still a challenging task. The present study proposes a simulated annealing algorithm (SA) in estimating the parameters of Weibull distribution with application to modified internal rate of return data (MIRR).The objective is to examine the investment potential of the shari’ah compliance companies of the Malaysia property sector (MPS). …”
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    Thesis
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    Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

    Published 2022
    “…The validation of the proposed method is conducted by using a confusion matrix with a composition of 80% training data and 20% test data. …”
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    Proceeding Paper