Search Results - (( pattern using spatial algorithm ) OR ( java application optimization algorithm ))

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  1. 1

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

    Published 2011
    “…It is because spatial data mining algorithms have to consider not only objects of interest itself but also neighbours of the objects in order to extract useful and interesting patterns. …”
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    Conference or Workshop Item
  2. 2

    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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    Article
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    Clustering Spatial Data Using a Kernel-Based Algorithm by Awan, A. Majid, Md. Sap, Mohd. Noor

    Published 2005
    “…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data. …”
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  5. 5

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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  6. 6

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
  7. 7

    Finding spatio-temporal patterns in climate data using clustering by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data.…”
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  8. 8

    EEG EYE STATE IDENTIFICATION BASED ON STATISTICAL FEATURES AND COMMON SPATIAL PATTERN by WANG, CHIA WOON

    Published 2019
    “…Hence, eyes closed state and eyes open state are selected as the area of research. Besides, common spatial pattern (CSP) is the well-known method for classification algorithm in the BCI field. …”
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    Final Year Project
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    Hybrid Spatial-Artificial Intelligence Approach for Renewable Energy Sources Sites Identification and Integration in Sarawak State by Far Chen, Jong

    Published 2022
    “…It is followed by identifying RES sites using spatial data and Multi-Criteria Decision Making-Analytical Hierarchy Process (MCDM-AHP) algorithm. …”
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    Thesis
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    Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal by Khatereh Darvish ghanbar, Tohid Yousefi Rezaii, Ali Farzamnia, Ismail Saad

    Published 2021
    “…Common spatial pattern (CSP) is shown to be an effective pre-processing algorithm in order to discriminate different classes of motor-based EEG signals by obtaining suitable spatial filters. …”
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    Article
  14. 14

    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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    Thesis
  15. 15

    Geomorphometric analysis of landform pattern using topographic position and ASTER GDEM by Lay, Usman Salihu, Jibrin, Gambo, Tijani, Ibrahim, Pradhan, Biswajeet

    Published 2017
    “…Maximum Elevation Deviation was selected to measure the spatial landscape pattern at the maximum (3000) scale of the absolute DEV value within the scale (DEVmax), and finally, high-pass filter algorithm was used to identify the extreme topography (ridges/valleys). …”
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  16. 16

    Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis by Kabir Ahmad, Farzana, Kamaruddin, Siti Sakira, Yusof, Yuhanis, Yusoff, Nooraini

    Published 2021
    “…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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    Monograph
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    A spatial decision support system framework for optimization of cropping pattern and water resources allocation at pasargard plains, fars province, Iran by Ghasemi, Mohammad Mehdi

    Published 2014
    “…The proposed GA-based optimization model—namely Piece-Wise Genetic Algorithm (PWGA)—was capable of proposing optimal cropping patterns, deficit irrigation rules, and conjunctive use decisions for each farm, and to tackle the large number of decision variables involved. …”
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    Thesis
  19. 19

    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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    Article
  20. 20

    Rain streak removal using emboss and spatial-temporal depth filtering technique in video keyframes by Shariah, Sawsan Kamel

    Published 2012
    “…Each drop when falling in high speed will create a streak motion blurred illusion based on the background intensity that reflects the environment creating higher intensity pattern in an image. In this thesis rain streak have been captured and isolated from the background scene by using an embossed filter algorithm designed to highlight the transparent rain streaks that cause the blur and distortion of the video, while the removing algorithm is based on a simple algorithm that correlates spatio-temporal and depth of an image into one technique. …”
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    Thesis