Search Results - (( data classification modified algorithm ) OR ( data replication using algorithm ))

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  1. 1

    Finger-Vein Biometric Identification Using Convolutional Neural Network by Syafeeza, Ahmad Radzi, Mohamed, Khalil-Hani, Rabia, Bakhteri

    Published 2016
    “…For network training, we have modified and applied the stochastic diagonal Levenberg-Marquardt algorithm, which results in a faster convergence time. …”
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    Article
  2. 2

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…A modified Apriori algorithm technique is utilized to reduce a minimal set of decision rules based on input output data set. …”
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  3. 3

    Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

    Published 2024
    “…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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    Thesis
  4. 4

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Among numerous artificial intelligence approaches, k-Nearest Neighbor algorithms, genetic algorithms, and artificial neural networks are considered as the most common and effective methods in classification problems in numerous studies. …”
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    Article
  5. 5

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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  6. 6

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…Nowadays, the use of SVM is very perspective for the big data classification. SVM provides a global solution for data classification but SVM is highly sensitive to noise data and may not be effective when the level of noise data is high. …”
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    Thesis
  7. 7

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…Thus, this study aims to adopt and modify the BFOA into Instance Selection (IS) classifier by manipulating its global search capability and high convergence rate for data classification problem. …”
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  8. 8

    Relationship based replication algorithm for data grid by Yusof, Yuhanis

    Published 2014
    “…The Relationship based Replication algorithm aims to improve the Data Grid performance by reducing the job execution time, bandwidth and storage usage.The RBR was realized using a network simulation (OptorSim) and experiment results revealed that it offers better performance than existing replication algorithms.…”
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    Monograph
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  10. 10

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…A computational approach for gene selection based on microarray data analysis has been applied in many cancer classification problems. …”
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  11. 11

    Managing Fragmented Database Using BVAGQ-AR Replication Model by Ainul Azila, Che Fauzi, Noraziah, Ahmad, Tutut, Herawan, Z., Abdullah, Gupta, Ritu

    Published 2017
    “…Problem arises when the database is packed with data, but it has lacked of knowledge. If the unreasonable data is used in database replication, it will cause waste of data storage and delay the time taken for a replication process. …”
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    Article
  12. 12

    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
    “…Data replication is one of the mechanisms to manage data since it improves data accessibility and reliability. …”
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  13. 13

    Managing MyGRANTS Fragmented Database Using Binary Vote Assignment Grid Quorum with Association Rule (BVAGQ-AR) Replication Model by Noraziah, Ahmad, Wan Maseri, Wan Mohd, Ainul Azila, Che Fauzi

    Published 2015
    “…Nevertheless, if the impractical data is used in database replication, this will cause waste of data storage and the time taken for a replication process will be delayed. …”
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    Dynamic replication algorithm in data grid: Survey by K. Madi, Mohammed, Hassan, Suhaidi

    Published 2008
    “…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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    Book Section
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    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…Two modified algorithms are proposed in this research, which are mixture of the momentum algorithm with different learning rate algorithms. …”
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    Thesis
  19. 19

    A novel deadlock detection algorithm for neighbour replication on grid environment by Noriyani, Mohd Zin

    Published 2012
    “…The use of three to five transactions is in NRG the data will be replicated into three to five sites. …”
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  20. 20

    Automated classification of blasts in acute leukemia blood samples using HMLP network by Harun, N. H., Mashor, M.Y., Abdul Nasir, A.S., Rosline, H.

    Published 2011
    “…This paper presents a study on classification of blasts in acute leukemia blood samples using artificial neural network.In acute leukemia there are two major forms that are acute myelogenous leukemia (AML) and acute lymphocytic leukemia (ALL).Six morphological features have been extracted from acute leukemia blood images and used as neural network inputs for the classification.Hybrid Multilayer Perceptron (HMLP) neural network was used to perform the classification task.The Hybrid Multilayer Perceptron(HMLP) neural network is trained using modified RPE(MRPE) training algorithm for 1474 data samples.The Hybrid Multilayer Perceptron (HMLP) neural network produces 97.04% performance accuracy.The result indicates the promising capabilities and abilities of the Hybrid Multilayer Perceptron (HMLP) neural network using modified RPE (MRPE) training algorithm for classifying and distinguishing the blasts from acute leukemia blood samples.…”
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