Search Results - (( java implementation mining algorithm ) OR ( parameter estimation age 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
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    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
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  4. 4
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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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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  6. 6
    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. …”
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  7. 7
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  8. 8
    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
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  9. 9
    Age Estimation of Cellulose Paper Insulation in Power Transformers Using ANN

    Age Estimation of Cellulose Paper Insulation in Power Transformers Using ANN by Navamany J.S., Ghosh P.S.

    Published 2023
    Conference Paper
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  10. 10
    State-of-Charge Estimation of Li-Ion Battery in Electric Vehicles: A Deep Neural Network Approach

    State-of-Charge Estimation of Li-Ion Battery in Electric Vehicles: A Deep Neural Network Approach by How D.N.T., Hannan M.A., Lipu M.S.H., Sahari K.S.M., Ker P.J., Muttaqi K.M.

    Published 2023
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  11. 11
    Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd Hamdan

    Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd... by Sharifah Nabilah , Syed Mohd Hamdan

    Published 2024
    “…All the age groups, except for 0–2 years and 3–6 years, exhibited reliable sex estimation with a high accuracy percentage (≥75%) when tested using DFA and BLR. …”
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  12. 12
    Reproducing kernel Hilbert space method for cox proportional hazard model

    Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

    Published 2016
    “…This algorithm is used to determine the vector i a that enables us to find the optimal parameters of ƒ(x)which is simplified as F(x)= ∑aᵢK(x,xᵢ) . …”
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  13. 13
    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus

    Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

    Published 2016
    “…The significant variables determined by maximum likelihood method were then estimated using the BLR method. The BLR approach via Gibbs sampler and the random walk metropolis algorithm suggests that family history of diabetes, waist circumference and the body mass index are the significant risk factors associated with the type 2 diabetes mellitus. …”
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  14. 14
    Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier : A scoping review

    Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier : A scoping review by Norhasmira, Mohammad, Rohana, Ahmad, Arofi, Kurniawan, Mohd Yusmiaidil, Putera Mohd Yusof

    Published 2022
    “…Results: The potential application of artificial intelligence technology in forensic odontology can be categorized into four: (1) human bite marks, (2) sex determination, (3) age estimation, and (4) dental comparison. This powerful tool can solve humanity's problems by giving an adequate number of datasets, the appropriate implementation of algorithm architecture, and the proper assignment of hyperparameters that enable the model to perform the prediction at a very high level of performance. …”
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  15. 15
    Class binarization with self-adaptive algorithm to improve human activity recognition

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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  16. 16
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
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  17. 17
    Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil

    Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

    Published 2021
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  18. 18
    Artificial Neural Network: The Alternative Method to Obtain the Dimension of Ankle Bone Parameters

    Artificial Neural Network: The Alternative Method to Obtain the Dimension of Ankle Bone Parameters by R., Daud, Mas Ayu, Hassan, Salwani, Mohd Salleh, Siti Haryani, Tomadi, Mohammed Rafiq, Abdul Kadir, Raghavendran, Hanumantharao Balaji, Tunku, Kamarul

    Published 2017
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  19. 19
    Mathematical modeling of brain tumor cell growth for passive, active and oxygen transport mechanism with microgravity condition / Norfarizan Mohd Said

    Mathematical modeling of brain tumor cell growth for passive, active and oxygen transport mechanism with microgravity condition / Norfarizan Mohd Said by Mohd Said, Norfarizan

    Published 2018
    “…The image processing technique known as Enhanced Distance Active Contour (EDAC) are utilized in edge detection of the MRI images to get the parameter estimations for comparison with the model simulations. …”
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