Search Results - (( code classification rules algorithm ) OR ( parallel identification method 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
  6. 6

    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
  7. 7
  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

    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
    “…A residuals-based sequential identification algorithm using parallel integration of linear Orthornormal basis filters (OBF) and a nonlinear feedforward (MLP) NN model is used and applied to the nonlinear Van de Vusse reactor. …”
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    Conference or Workshop Item
  10. 10

    Hybrid intelligent methods for parameter identification and load frequency control in power system by Aqeel Sakhy, Jaber

    Published 2014
    “…For example, the classical methods for parameter identification (LSE and MLE), the classical methods for LFC (PI, PD and PID) and the intelligent methods (fuzzy logic, neural network, genetic algorithm, and PSO). …”
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    Thesis
  11. 11
  12. 12

    Computationally efficient sequential learning algorithms for direct link resource-allocating networks by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2005
    “…The new algorithms, which also incorporate a pruning strategy to control network growth, are evaluated on three different system identification benchmark problems and shown to outperform existing methods both in terms of training error convergence and computational efficiency.…”
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    Article
  13. 13

    OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

    Published 2011
    “…In this thesis, a new optimization GA-based algorithm that emanates from modification of conventional GA to reduce the iterations number and the duration time, namely, semi-parallel operation genetic algorithm (SPOGA) is proposed. …”
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    Thesis
  14. 14

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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    Article
  15. 15

    Grid-based simultaneous localization and mapping using Rao-blackwellized particle filter with neural network for mini robots / Norhidayah Mohamad Yatim by Mohamad Yatim, Norhidayah

    Published 2018
    “…OG map representation does not need for landmark identification but described occupancy of an area. In this research, to enable mini robots to operate in various environment, OG map with SLAM or grid-based SLAM algorithm was developed. …”
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    Thesis
  16. 16

    Human gait recognition and classification using similarity index for various conditions by Makhdoomi, Nahid A., Gunawan, Teddy Surya, Habaebi, Mohamed Hadi

    Published 2013
    “…Our aim is to implement the traditional gait recognition algorithm and to show the variation in gait recognition when subject is observed parallel to camera under three conditions- walking normal, carrying a bag and wearing a coat. …”
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    Proceeding Paper
  17. 17

    Human gait recognition and classification using similarity index for various conditions by Makhdoomi, Nahid A., Gunawan, Teddy Surya, Habaebi, Mohamed Hadi

    Published 2013
    “…Our aim is to implement the traditional gait recognition algorithm and to show the variation in gait recognition when subject is observed parallel to camera under three conditions- walking normal, carrying a bag and wearing a coat. …”
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    Article
  18. 18

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, Norshuhani, Oxley, Alan, Abu Bakar, Zainab

    Published 2012
    “…Named Entity Recognition (NER) is the identification of words in text that correspond to a pre-defined taxonomy such as person, organization, location, date, time, etc.This article focuses on the person (PER), organization (ORG) and location (LOC) entities for a Malay journalistic corpus of terrorism.A projection algorithm, using the Dice Coefficient function and bigram scoring method with domain-specific rules, is suggested to map the NE information from the English corpus to the Malay corpus of terrorism.The English corpus is the translated version of the Malay corpus.Hence, these two corpora are treated as parallel corpora. …”
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    Article
  19. 19

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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    Article
  20. 20

    Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

    Published 2013
    “…Hence, these two corpora are treated as parallel corpora. The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping. …”
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    Article