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  1. 1
    An extended ID3 decision tree algorithm for spatial data

    An extended ID3 decision tree algorithm for spatial data by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2011
    “…As in the ID3 algorithm that use information gain in the attribute selection, the proposed algorithm uses the spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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  2. 2
    Classification model for hotspot occurrences using spatial decision tree algorithm

    Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…As the ID3 algorithm that uses information gain in the attribute selection, the proposed algorithm uses spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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  3. 3
    Extended spatial decision tree algorithm for classifying hotspot occurrence

    Extended spatial decision tree algorithm for classifying hotspot occurrence by Sitanggang, Imas Sukaesih

    Published 2013
    “…The proposed algorithm uses spatial information gain to choose the best splitting layer from a set of explanatory layers. …”
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  4. 4
    Tracking student performance in introductory programming by means of machine learning

    Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

    Published 2023
    Conference Paper
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  5. 5
    Hybrid Spatial-Artificial Intelligence Approach for Renewable Energy Sources Sites Identification and Integration in Sarawak State

    Hybrid Spatial-Artificial Intelligence Approach for Renewable Energy Sources Sites Identification and Integration in Sarawak State by Far Chen, Jong

    Published 2022
    “…From this, the spatial criteria scheme data is produced. …”
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  6. 6
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…From a Bayesian perspective, we design a sequential prediction algorithm to exactly compute the predictive inference of the random field. …”
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  7. 7
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…From a Bayesian perspective, we design a sequential prediction algorithm to exactly compute the predictive inference of the random field. …”
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  8. 8
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…From a Bayesian perspective, we design a sequential prediction algorithm to exactly compute the predictive inference of the random field. …”
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  9. 9
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…From a Bayesian perspective, we design a sequential prediction algorithm to exactly compute the predictive inference of the random field. …”
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  10. 10
    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields

    Efficient Bayesian spatial prediction with mobile sensor networks using Gaussian Markov random fields by Xu, Y., Choi, J., Dass, S., Maiti, T.

    Published 2013
    “…From a Bayesian perspective, we design a sequential prediction algorithm to exactly compute the predictive inference of the random field. …”
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  11. 11
    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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  12. 12
    An artificial intelligence approach to monitor student performance and devise preventive measures

    An artificial intelligence approach to monitor student performance and devise preventive measures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…We developed a set of prediction models with distinct machine learning algorithms. Decision tree triumph over other models and thus is further transformed into easily explicable format. …”
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  13. 13
    Modeling and querying alternative paths in Kuantan

    Modeling and querying alternative paths in Kuantan by Mohamad Salleh, Mazlina

    Published 2007
    “…Spatial databases are prominently used in Geographic Information System (GIS) application like digital map application. …”
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  14. 14
    TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms

    TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms by Marina, Patrick, Mah, Yau Seng, Putuhena, Frederik Josep, Wang, Yin Chai, Onni Suhaiza, Selaman

    Published 2016
    “…These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.…”
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  15. 15
    Reservoir water release dynamic decision model based on spatial temporal pattern

    Reservoir water release dynamic decision model based on spatial temporal pattern by Suriyati, Abdul Mokhtar

    Published 2016
    “…The modified Sliding Window algorithm was used to construct the rainfall temporal pattern, while the spatial information was established by simulating the mapped rainfall and reservoir water level pattern. …”
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  16. 16
    Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing

    Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing by Hamedianfar, Alireza

    Published 2015
    “…The proposed OBIA rule sets were automatically organized from the C4.5 algorithm to form a decision tree structure that explores a wide range of spectral, spatial, and textural attributes. …”
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  17. 17
    Enhanced privacy protection from location dependent attacks in location based services using spatial cloaking

    Enhanced privacy protection from location dependent attacks in location based services using spatial cloaking by Saravanan, Perumal Shanthi, Balasundaram, Sadhu Ramakrishnan

    Published 2020
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  18. 18
    Workload performance evaluation of large spatial database for DSS based disaster management

    Workload performance evaluation of large spatial database for DSS based disaster management by Rohman, Muhammad Syaifur

    Published 2017
    “…Therefore, the general objective of this research is to evaluate and predict workload performance of spatial DBMS associated with PostgreSQL which is different from MySQL. …”
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  19. 19
    Enhanced Privacy Protection Against Location-Dependent Attacks in Location Based Services Using Spatial Cloaking

    Enhanced Privacy Protection Against Location-Dependent Attacks in Location Based Services Using Spatial Cloaking by Saravanan, Perumal Shanthi, Balasundaram, Sadhu Ramakrishnan

    Published 2020
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  20. 20
    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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