Search Results - (( spatial information 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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  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
    A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science

    A review of the inter-correlation of climate change, air pollution and urban sustainability using novel machine learning algorithms and spatial information science by Balogun, A.-L., Tella, A., Baloo, L., Adebisi, N.

    Published 2021
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  5. 5
    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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    Conference or Workshop Item
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  6. 6
    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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  7. 7
    GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms

    GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms by Tella, A., Balogun, A.-L.

    Published 2021
    “…Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). …”
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  8. 8
    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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  9. 9
    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification

    Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification by Prathama, Y.B.H., Shapiai, M.I., Aris, S.A.M., Ibrahim, Z., Jaafar, J., Fauzi, H.

    Published 2017
    “…A spatial filtering algorithm called Common Spatial Pattern (CSP) was developed and known to have excellent performance, especially in motor imagery for BCI application. …”
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  10. 10
    Hyperspectral anomaly detection leveraging spatial attention and right-shifted spectral energy

    Hyperspectral anomaly detection leveraging spatial attention and right-shifted spectral energy by Ruhan, A., Gao, Quanxue, Zhang, Xiaoni, Feng, Wenwen, Ali, Siti Khadijah

    Published 2025
    “…The algorithm integrates spatial and spectral information, utilizing graph neural networks to identify nonlinear relationships within the image, thereby enhancing anomaly detection precision. …”
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  11. 11
    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar

    Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar by Mohd Shahar, Hanani

    Published 2020
    “…The information of building features especially in the urban area is very important to support urban management and development. …”
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  12. 12
    A review on spatial technologies for enhancing malaria control: concepts, tools, and challenges

    A review on spatial technologies for enhancing malaria control: concepts, tools, and challenges by Rayner Alfred, Joe Henry Obit

    Published 2021
    “…The discussion is categorized into four categories: a) Application of Spatial Technologies, b) Applications of Machine Learning Algorithms, c) Applying Multiple Sources of Data, and d) Applications of Smartphone Technologies. …”
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  13. 13
    Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network

    Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

    Published 2022
    “…Firstly, according to the discreteness of multispectral EEG image features, two-scale convolution kernels were used to calculate and learn useful channel and frequency band feature information in multispectral image data. …”
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  14. 14
    SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS

    SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS by Abujayyab, Sohaib K. M., S. Ahamad, Mohd Sanusi, Yahya, Ahmad Shukri, Abdul Aziz, Hamidi

    Published 2016
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  15. 15
    Testing the minimal bounded space method on vision-based drone navigation / Yap Seng Kuang

    Testing the minimal bounded space method on vision-based drone navigation / Yap Seng Kuang by Yap , Seng Kuang

    Published 2021
    “…There is no imaging involved, but the laser sensor does record depth information. The spatial openings are derived by analyzing occlusion information from the environment, which is available from the depth information. …”
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  16. 16
    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Based on cross-validation analysis, the score-based algorithm outperformed the constraint-based algorithms in the structural learning. …”
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  17. 17
    Real-time human activity recognition using external and internal spatial features

    Real-time human activity recognition using external and internal spatial features by Htike@Muhammad Yusof, Zaw Zaw, Egerton, Simon, Kuang, Ye Chow

    Published 2010
    “…We employ a spatio-temporal representation of human activities by combining trajectory information and invariant spatial information of the subjects. …”
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    Proceeding Paper
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  18. 18
    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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  19. 19
    Particle swarm optimization with deep learning for human action recognition

    Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

    Published 2021
    “…To extract the appearance based and structural information, each frame of the action sequences is evaluated for spatial features. …”
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  20. 20
    A hybrid spiking neural network model for multivariate data classification and visualization.

    A hybrid spiking neural network model for multivariate data classification and visualization. by Ming, Leong Yii, Teh, Chee Siong, Chen, Chwen Jen

    Published 2011
    “…SOM is one of the most prominent unsupervised learning algorithms. Recently, many extensions for SOM have been proposed for temporal processing. …”
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