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  1. 1
    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
    “…The improved Spatial-AI algorithm showed approximately 15% better compared to ordinary TSP-GA in all four cases.…”
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  2. 2
    Improving pipelined time stepping algorithm for distributed memory multicomputers

    Improving pipelined time stepping algorithm for distributed memory multicomputers by Ng, Kok Fu, Norhashidah Hj. Mohd. Ali

    Published 2010
    “…Our goal is to reduce the inter-time step communications while providing adequate information for the next time step to converge. Numerical result confirms that the improved algorithm is faster than the original pipelined algorithm and sequential time stepping algorithm with spatial parallelisation alone. …”
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  3. 3
    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
    “…We also present a distributed version of the prediction algorithm for a special case. An adaptive sampling strategy is presented for mobile sensing agents to find the most informative locations in taking future measurements in order to minimize the prediction error and the uncertainty in hyperparameters simultaneously. …”
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  4. 4
    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
    “…We also present a distributed version of the prediction algorithm for a special case. An adaptive sampling strategy is presented for mobile sensing agents to find the most informative locations in taking future measurements in order to minimize the prediction error and the uncertainty in hyperparameters simultaneously. …”
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  5. 5
    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
    “…We also present a distributed version of the prediction algorithm for a special case. An adaptive sampling strategy is presented for mobile sensing agents to find the most informative locations in taking future measurements in order to minimize the prediction error and the uncertainty in hyperparameters simultaneously. …”
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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
    “…We also present a distributed version of the prediction algorithm for a special case. An adaptive sampling strategy is presented for mobile sensing agents to find the most informative locations in taking future measurements in order to minimize the prediction error and the uncertainty in hyperparameters simultaneously. …”
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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
    “…We also present a distributed version of the prediction algorithm for a special case. An adaptive sampling strategy is presented for mobile sensing agents to find the most informative locations in taking future measurements in order to minimize the prediction error and the uncertainty in hyperparameters simultaneously. …”
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  8. 8
    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting

    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…The unsupervised solution using time series clustering algorithms is capable to extract valuable information and identify structure in complex and massive datasets as spatial time series. …”
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  9. 9
    Comparative spatial analysis of enteric fever and leptospirosis in Kelantan, Malaysia using e-notifikasi surveillance database, 2016 – 2022

    Comparative spatial analysis of enteric fever and leptospirosis in Kelantan, Malaysia using e-notifikasi surveillance database, 2016 – 2022 by Hatta, Hazlienor Mohd

    Published 2023
    “…Spatial dependence between enteric fever and leptospirosis cases within two to ten kilometres distance was also demonstrated. …”
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  10. 10
    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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  11. 11
    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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  12. 12
    Recognition of Cylindrical and Conical Features Using Edge Boundary Classification

    Recognition of Cylindrical and Conical Features Using Edge Boundary Classification by Ismail, N., Abu Bakar, N., Juri, A.H.

    Published 2005
    “…The technique uses the spatial addressability information of solid models that identifies the solid and void ‘sides’ of a boundary entity. …”
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  13. 13
    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
    “…In this way, information is delivered to DBMS hence ensuring incoming workload information is very crucial for the purpose of determining the smooth works of PostgreSQL DBMS.…”
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  14. 14
    Rain streaks removal using total variation and sparse coding based on case based reasoning approach

    Rain streaks removal using total variation and sparse coding based on case based reasoning approach by Shorman S.M., Salam R.A., Sakinah Ali Pitchay

    Published 2024
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  15. 15
    Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis

    Spatial Data Mining Model For Landfill Sites Suitability Mapping Based On Neural Networks And Multivariate Analysis by Abujayyab, Sohaib K. M.

    Published 2017
    “…A case study on landfill site selection in four northern states of Malaysia was conducted to demonstrate the validity of the new SDM model. …”
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  16. 16
    Red tide detection using remotely sensed data: A case study of Sabah, Malaysia

    Red tide detection using remotely sensed data: A case study of Sabah, Malaysia by Asmala Ahmad, Noorazuan Hashim, Laili Nordin

    Published 2009
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  17. 17
    MMS : mobile monitoring system using electrical capacitance tomography (ECT)

    MMS : mobile monitoring system using electrical capacitance tomography (ECT) by Abdul Rahim, Ruzairi, Chan, Kok Seong

    Published 2008
    “…Electrical capacitance tomography system is useful for obtain information about the spatial distribution of a mixture of dielectric materials inside a vessel. …”
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  18. 18
    Red tide detection using remotely sensed data: A case study of Sabah, Malaysia

    Red tide detection using remotely sensed data: A case study of Sabah, Malaysia by Asmala, A., Noorazuan, H., Nordin , L.

    Published 2009
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  19. 19
    An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning

    An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning by Islam, Md Kamrul

    Published 2019
    “…These results prove the superiority of BOCEDS algorithm over the existing clustering algorithms. …”
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  20. 20
    A Novel Path Prediction Strategy for Tracking Intelligent Travelers

    A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

    Published 2009
    “…The system takes the advantage of the past trajectory information to compensate for the missing information during disconnections. …”
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