Search Results - (( structural estimation learning algorithm ) OR ( java application mining 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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    Thesis
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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
    Evaluation of Convolutional Neural Network based on Dental Images for Age Estimation

    Evaluation of Convolutional Neural Network based on Dental Images for Age Estimation by Alkaabi S., Yussof S., Al-Mulla S.

    Published 2023
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  8. 8
    A case study on quality of sleep and health using Bayesian networks

    A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

    Published 2012
    “…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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  9. 9
    An intelligent framework for modelling and active vibration control of flexible structures

    An intelligent framework for modelling and active vibration control of flexible structures by Mohd. Hashim, Siti Zaiton

    Published 2004
    “…The simulation algorithm and interactive environment thus developed and validated form suitable test and verification platforms for the development of AVC strategies for flexible structures as well as for learning and research purposes.…”
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  10. 10
    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network

    Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

    Published 2024
    “…It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. …”
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  11. 11
    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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  12. 12
    Using electromechanical impedance and extreme learning machine to detect and locate damage in structures

    Using electromechanical impedance and extreme learning machine to detect and locate damage in structures by Djemana, Mohamed, Hrairi, Meftah, Al Jeroudi, Yazan

    Published 2017
    “…In this paper, an extreme learning machine (ELM) based algorithm is developed for estimating the damage location by using piezoelectric sensors data. …”
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  13. 13
    Deep convolutional neural networks for forensic age estimation: A review

    Deep convolutional neural networks for forensic age estimation: A review by Alkaabi S., Yussof S., Al-Khateeb H., Ahmadi-Assalemi G., Epiphaniou G.

    Published 2023
    “…Various biological features such as the face, bones, skeletal and dental structures can be utilised to estimate age. This article will cover how modern technology has developed to provide new methods and algorithms to digitalise this process for the medical community and beyond. …”
    Book Chapter
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  14. 14
    Unsupervised monocular depth estimation with multi-scale structural similarity powered loss function / Ali Kohan

    Unsupervised monocular depth estimation with multi-scale structural similarity powered loss function / Ali Kohan by Ali, Kohan

    Published 2020
    “…Depth Estimation refers to a set of techniques and algorithms that aim to obtain a representation of spatial information of a scene. …”
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  15. 15
    Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks

    Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks by Mahzan, Shahruddin, J. Staszewski, Wieslaw, Worden, Keith

    Published 2010
    “…The study demonstrates that both approaches are capable of good impact location estimates in this complex structure.…”
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  16. 16
    Single image integrated deblurring algorithm in non-uniform environment

    Single image integrated deblurring algorithm in non-uniform environment by Rechard Lee, Celine Wong

    Published 2025
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  17. 17
    DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management

    DeMI interface tool for profit estimation and waste conversion technology recommendations in enhancing municipal solid waste management by Ali, R.A., Nik Ibrahim, N.N.L., Ghani, W.A.W.A.K., Sani, N.S., Lam, H.L.

    Published 2024
    “…The M5P algorithm, adept at profit estimation, establishes correlations between MSW weight and profitability, while the J48 algorithm offers recommendations for suitable waste conversion technologies based on profit potential. …”
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  18. 18
    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification

    New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

    Published 2009
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    Monograph
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  19. 19
    Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich

    Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich by Bathich, Ammar

    Published 2019
    “…New multi-criterion handover decision parameters are proposed in typical/dense femtocells in macrocells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. …”
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  20. 20
    Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications

    Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

    Published 2025
    “…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
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