Search Results - (( ((pattern mining) OR (pattern using)) algorithm ) OR ( pattern warping algorithms ))

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  1. 1

    Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms by Tiong, Leslie C.O., Ngo, David C.L., Lee, Yunli

    Published 2013
    “…Forex prediction has become a challenging task in the Forex market since the late 1970s due to uncertainty movement of exchange rates.In this paper, we utilised linear regression equation to analyse the historical data and discover the trends patterns in Forex.These trends patterns are modeled and learned by Artificial Neural Network algorithm, and Dynamic Time Warping algorithm is used to predict the near future trends.Our experiment result shows a satisfactory result using the proposed approach.…”
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  2. 2

    Prediction of forex trend movement using linear regression line, two-stage of multi-layer perceptron and dynamic time warping algorithms by Tiong, Leslie Ching Ow *, Ngo, David Chek Ling *, Lee, Yunli *

    Published 2016
    “…Thus, this motivates us to investigate possibility of repeated trend patterns from historical Forex data. This paper aims to investigate the repeated trend patterns as features from historical Forex data, which proposes new combination techniques - Linear Regression Line, two-stage of Multi-Layer Perceptron and Dynamic Time Warping algorithms in order to improve the performance of prediction significantly, thus achieving greater accuracy.…”
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  3. 3

    Prediction of Forex trend movement using linear regression line, two-stage of multi-layer perceptron and dynamic time warping algorithms by Leslie, Tiong Ching Ow, David, Chek Ling Ngo, Lee, Yunli

    Published 2016
    “…Thus, this motivates us to investigate possi­bility of repeated trend patterns from historical Forex data. This paper aims to investigate the repeated trend patterns as features from historical Forex data, which proposes new combination techniques - Linear Regression Line, two-stage of Multi-Layer Perceptron and Dynamic Time Warping algorithms in order to improve the performance of prediction significantly, thus achiev­ing greater accuracy…”
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  4. 4

    Financial time series predicting using machine learning algorithms by Tiong, Leslie Ching Ow *

    Published 2013
    “…Subsequently, Dynamic Time Warping (DTW) algorithm is utilised through brute force to predict the trend movement. …”
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  5. 5

    Modifying iEclat algorithm for infrequent patterns mining by Julaily Aida, J., Mustafa, M.

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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  6. 6

    Modifying iEclat algo ithm for infrequent patterns mining by Julaily Aida, Jusoh, Mustafa, Man

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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  7. 7

    Robust speech recognition using fusion techniques and adaptive filtering by Syed Mohamed, Syed Abdul Rahman Al-Haddad, Abdul Samad, Salina, Hussain, Aini, Ishak, Khairul Anuar, Noor, Ali O. Abid

    Published 2009
    “…The study proposes an algorithm for noise cancellation by using recursive least square (RLS) and pattern recognition by using fusion method of Dynamic Time Warping (DTW) and Hidden Markov Model (HMM). …”
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  8. 8

    Animal voice recognition for identification (ID) detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2011
    “…While the voice pattern classification will be done by using DTW algorithm. …”
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  9. 9

    Dog voice identification (ID) for detection system by Yeo, Che Yong, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Ng, Chee Kyun

    Published 2012
    “…While the voice pattern classification will be done by using DTW algorithm. …”
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  10. 10

    Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset by Julaily Aida, Jusoh, Wan Aezwani, Wan Abu Bakar, Mustafa, Man

    Published 2018
    “…Pattern mining refers to a subfield of data mining that uncovers interesting, unexpected, and useful patterns from transaction databases. …”
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  11. 11

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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  12. 12

    Efficient prime-based method for interactive mining of frequent patterns. by Mohammad Hossein, Nadimi Shahraki, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2011
    “…During the mining process, the mining algorithm reduces the number of candidate patterns and comparisons by using a new candidate set called candidate head set and several efficient pruning techniques. …”
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  13. 13
  14. 14

    A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2009
    “…Frequent pattern mining is one of the active research themes in data mining. …”
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  15. 15

    Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

    Published 2005
    “…The mined frequent patterns are then used in generating association rules. …”
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  16. 16

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Dhany, Saputra

    Published 2008
    “…Sequential pattern mining is a new branch of data, mining science that solves inter-transaction pattern mining problems. …”
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  17. 17

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
    “…Sequential pattern mining is a new branch of data, mining science that solves inter-transaction pattern mining problems. …”
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  18. 18

    Sequential pattern mining using PrefixSpan with pseudoprojection and separator database by Saputra, D., Rambli, D.R.A., Foong, Oi Mean

    Published 2008
    “…Sequential pattern mining is a new branch of data mining science that solves inter-transaction pattern mining problems. …”
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  19. 19

    Local DTW coefficients and pitch feature for back-propagation NN digits recognition by Sudirman, R., Salleh, Shahruddin Hussain, Salleh, Sh-Hussain

    Published 2006
    “…The speech recognition is performed using the back-propagation neural network (BPNN) algorithm to enhance the recognition performance. …”
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  20. 20

    Using unique-prime-factorization theorem to mine frequent patterns without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2011
    “…An interest solution is to design an approach that without generating candidate is able to mine frequent patterns. Results: An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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