Search Results - (( java application mining algorithm ) OR ( variable training content algorithm ))

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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    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
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  5. 5
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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  6. 6
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  7. 7
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  8. 8
    Daily streamflow forecasting using simplified rule-based fuzzy logic system

    Daily streamflow forecasting using simplified rule-based fuzzy logic system by Mohd Shafiek, Yaacob, Dr., Hishamuddin, Jamaluddin, Sobri, Harun

    Published 2011
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  9. 9
    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization

    Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization by Lee, Jesee Kar Ming

    Published 2022
    “…The ANN model topology is designed using selection from the best training algorithm, transfer function, number of training runs (1000-5000), number of hidden layers (1-3) and nodes (5-15). …”
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  10. 10
    Sediment model for natural and man-made channels using general regression neural network

    Sediment model for natural and man-made channels using general regression neural network by Junaidah, Ariffin, Nurashikin, Ahmad Kamal, Muhamad Syahreen, Sa’adon, Mohd Nasir, Taib, Suhaimi, Abdul-Talib, Aminuddin, Abd-Ghani, Nor Azazi, Zakaria, Ahmad Shukri, Yahaya

    Published 2011
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  11. 11
    Revolutionizing video analytics: a review of action recognition using 3D

    Revolutionizing video analytics: a review of action recognition using 3D by Jeddah, Yunusa Mohammed, Hassan Abdalla Hashim, Aisha, Khalifa, Othman Omran, Ibrahim, Adamu Abubakar

    Published 2024
    “…Findings show that integrating 3D video with action recognition algorithms augments accuracy and detail while challenges in video action recognition such as long video features capturing, temporal context maintenance, computational costs management, variability handling, inadequate training data, domain adaptation, and benchmarking methods are addressed. …”
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  12. 12
    Classification model for chlorophyll content using CNN and aerial images

    Classification model for chlorophyll content using CNN and aerial images by Wagimin, Mohd Nazuan, Ismail, Mohammad Hafiz, Mohd Fauzi, Shukor Sanim, Seng, Chuah Tse, Abd Latif, Zulkiflee, Muharam, Farrah Melissa, Mohd Zaki, Nurul Ain

    Published 2024
    “…Chlorophyll content is usually used as a quantitative measurement of plant health. …”
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  13. 13
    A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions

    A multivariate modeling for analysis of factors controlling the particle size and viscosity in palm kernel oil esters-based nanoemulsions by Rezaee, Malahat, Basri, Mahiran, Raja Abdul Rahman, Raja Noor Zaliha, Salleh, Abu Bakar, Chaibakhsh, Naz, Masoumi, Hamid Reza Fard

    Published 2014
    “…The effect of four independent variables namely water content, oil and surfactant (O/S) ratio, mixing rate and mixing time were considered as inputs of the network trained. …”
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  14. 14
    Predicting the optimum compositions of a parenteral nanoemulsion system loaded with azithromycin antibiotic utilizing the artificial neural network model

    Predicting the optimum compositions of a parenteral nanoemulsion system loaded with azithromycin antibiotic utilizing the artificial neural network model by S. Daood, Ghaidaa, Basri, Hamidon, Stanslas, Johnson, Fard Masoumi, Hamid Reza, Basri, Mahiran

    Published 2015
    “…To achieve the optimum topologies, the ANN was trained by Incremental Back-Propagation (IBP), Batch Back-Propagation (BBP), Quick Propagation (QP), and Levenberg–Marquardt (LM) algorithms for testing data set. …”
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  15. 15
    Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust

    Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

    Published 2022
    “…The experimental data has been divided into the training set and testing set in the proportion of 85 (for training) and 15 (for testing) respectively. …”
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  16. 16
    Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust

    Experimental analysis and data-driven machine learning modelling of the minimum ignition temperature (MIT) of aluminium dust by Arshad, U., Taqvi, S.A.A., Buang, A.

    Published 2022
    “…The experimental data has been divided into the training set and testing set in the proportion of 85 (for training) and 15 (for testing) respectively. …”
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  17. 17
    Fatigue Life Assessment of Polymer-Matrix Composites Under Variable Amplitude Loading Using Neural Networks

    Fatigue Life Assessment of Polymer-Matrix Composites Under Variable Amplitude Loading Using Neural Networks by Hidayat, Mas Irfan Purbawanto Hidayat

    Published 2009
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  18. 18
    Recommendation System Model For Decision Making in the E-Commerce Application

    Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

    Published 2024
    thesis::doctoral thesis
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  19. 19
    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms

    An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

    Published 2015
    “…It is concluded that the resultant hybrid techniques can perform well if the variables provided to normalization by neighborhood model (MF and CF) do not have big differences in order for the hybrid normalization model to outperform every algorithm in comparison.…”
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  20. 20
    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail

    Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

    Published 2015
    “…Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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