Search Results - (( data identification method algorithm ) OR ( java application learning algorithm ))

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    Recursive Subspace Identification Algorithm Using The Propagator Based Method by Jamaludin, Irma Wani, Abdul Wahab, Norhaliza

    Published 2017
    “…Subspace model identification (SMI) method is the effective method in identifying dynamic state space linear multivariable systems and it can be obtained directly from the input and output data. …”
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    Article
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    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…System identification is a method of determining a mathematical relation between variables and terms of a process based on observed input-output data. …”
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    Article
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    Date store management in sliding window based on-line identification algorithms by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2001
    “…Sliding window identification algorithms use information from a store of data to optimise on-line learning. …”
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    Conference or Workshop Item
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    Data mining based damage identification using imperialist competitive algorithm and artificial neural network by Gordan, Meisam, Razak, Hashim Abdul, Ismail, Zubaidah, Ghaedi, Khaled

    Published 2018
    “…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, Hishamuddin, Abd. Samad, M. F., Ahmad, Robiah, Yaacob, M. S.

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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    Article
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    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Jamaluddin, H., Samad, M. F. A., Ahmad, R., Yaacob, M. S.

    Published 2007
    “…he genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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    Article
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    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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    Conference or Workshop Item
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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    Thesis
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    Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants by M, Irfan, N, Lukman, A. A, Alfauzi, J, Jumadi

    Published 2019
    “…Information about chili pests is collected so that it becomes a database that can be used to identify disease pests using the data mining method. The use of data mining algorithms is expected to help in the identification of pests and diseases in chili plants. …”
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    Conference or Workshop Item
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    Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Muhammad Hasbollah, Hassan, Lidyana, Roslan, Muhamad Sukri, Hadi

    Published 2023
    “…A square aluminium plate experimental rig with a gradient of 30° and all edges clamped were designed and fabricated to acquire input-output vibration data experimentally. This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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    Article
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    Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure by Annisa, Jamali, Lidyana, Roslan, Muhammad Hasbollah, Hassan

    Published 2023
    “…A square aluminium plate experimental rig with a gradient of 30° and all edges clamped were designed and fabricated to acquire input-output vibration data experimentally. This input-output data was then applied in a system identification method, which used an evolutionary algorithm with a linear autoregressive with exogenous (ARX) model structure to generate a dynamic model of the system. …”
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    Article
  16. 16

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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    Article
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    Application of multivariate data analysis for rapid identification of flavonoids classes by Che Noh, Che Hafizah, Mohamed Azmin, Nor Fadhillah, Amid, Azura, Asnawi, Ani Liza

    Published 2016
    “…Therefore, this study was focused on the development of algorithm for rapid identification of flavonoids classes which are flavanone, flavone and flavonol. …”
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    Proceeding Paper
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    Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

    Published 2022
    “…Second, to develop novel techniques that combine the strengths of normalisation, feature engineering and data augmentation to address the problem of dimensionality, feature dominance and sparsity in colorectal cancer identification based on gut microbiome data, using deep neural network algorithms. …”
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    Thesis