Search Results - (( parallel identification system algorithm ) OR ( code classification rules algorithm ))

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  1. 1

    Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2014
    “…This paper presents a classification of android malware using candidate detectors generated from an unsupervised association rule of Apriori algorithm improved with particle swarm optimization to train three different supervised classifiers. …”
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    Proceeding Paper
  2. 2

    Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2015
    “…However, supervised learning technique has limitations for malware classification task. This paper presents a classification approach on android malware using candidate detectors generated from an unsupervised association rule of Apriori Algorithm. …”
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    Article
  3. 3

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

    Published 2018
    “…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
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    Article
  4. 4

    Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan C.H., Tan M.S., Chang S.-W., Yap K.S., Yap H.J., Wong S.Y.

    Published 2023
    “…This research proposed an algorithm named Genetic Algorithm Fuzzy Logic (GAFL) with Pittsburg approach for rules learning and induction in genetic fuzzy system knowledge discovery. …”
    Article
  5. 5

    Chain coding and pre processing stages of handwritten character image file by Suliman, Azizah, Sulaiman, Md. Nasir, Othman, Mohamed, O. K. Rahmat, Rahmita Wirza

    Published 2010
    “…Fuzzy Logic is used in the classification phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. …”
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    Article
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    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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    Thesis
  8. 8

    POWER QUALITY CLASSIFICATION WITH DE-NOISING SCHEME USING WAVELET TRANSFORM AND RULE- BASED METHOD by HENG KEOW, CHUAH

    Published 2012
    “…Unique features from the I", 4t h ,7th and 8thl evel details are obtained as criteria for developing a Rules-Based Algorithm for classifying disturbances that have occurred. …”
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    Thesis
  9. 9

    Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems by Gunawan, Teddy Surya, Ambikairajah, Eliathamby

    Published 2012
    “…This paper presents the parallel implementation of the gene and exon identification of DNA sequences using the previously developed modified Gabor wavelet transform on multicore systems. …”
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    Proceeding Paper
  10. 10

    Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi by Hayawi, Mustafa Jabbar

    Published 2015
    “…These effects, if not controlled, would lead to large scale oscillations that would damage system components. System identification is a prerequisite to analysis of a dynamic system. …”
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    Thesis
  11. 11

    A comparison study between integrated OBFARX-NN and OBF-NN for modeling of nonlinear systems in extended regions of operation by Zabiri, H., Ariff, M., Tufa, L.D., Ramasamy, M.

    Published 2014
    “…In this paper the combination of linear and nonlinear models in parallel for nonlinear system identification is investigated. …”
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    Article
  12. 12

    Integrated OBF-NN models for extrapolation enhancement in conventional neural networks for nonlinear systems by H., Zabiri, M., Ramasamy, Lemma D, Tufa, Maulud, Abdulhalim

    Published 2011
    “…Abstract In this paper the integration of linear and nonlinear models in parallel for nonlinear system identification is investigated. …”
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    Conference or Workshop Item
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    Wavelet network based online sequential extreme learning machine for dynamic system modeling by Mohammed Salih, Dhiadeen, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil

    Published 2013
    “…The proposed model used as system identification for nonlinear dynamic systems. …”
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    Conference or Workshop Item
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    Hybrid intelligent methods for parameter identification and load frequency control in power system by Aqeel Sakhy, Jaber

    Published 2014
    “…Where, in the first part, the coherent identification algorithm for single and multi-area power systems with disturbances is proposed. …”
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    Thesis
  17. 17

    Efficient hardware design for palm-dorsa vein image enhancement by Jusoh@Yusoff, Suhaimi Bahisham

    Published 2018
    “…Vein biometric system uses the pattern of veins in the human body as a unique identification. …”
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    Thesis
  18. 18

    Integrated OBF-NN models with enhanced extrapolation capability for nonlinear systems by H., Zabiri, M., Ramasamy, T. D. , Lemma, Maulud, Abdulhalim

    Published 2013
    “…This paper proposes a nonlinear system identification using parallel linear-plus-neural network models that provide more accurate predictions on the process behavior even on extrapolated regions. …”
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    Citation Index Journal
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    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
    “…Although researchers have made progress in speech emotion feature extraction and model identification, they have struggled to create an SER system with satisfactory recognition accuracy. …”
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    Article