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    International Journal of Data Mining, Modelling and Management

    International Journal of Data Mining, Modelling and Management

    JournalISSN 1759-1163eISSN 1759-1171中科院 计算机科学 4区

    年发文量

    研究主题

    论文(359)

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    1Predicting Stock Prices Using State-of-art Machine Learning Models with Enhanced Feature Representation and Momentum Indicator Selection
    Haoyu Wang,Dejun Xie, Yujian Liu
    2026
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    2Differential Gene Expression Analysis Across Phloem Parenchyma and Companion Cell in Arabidopsis Thaliana Leaf
    Reema Joshi, Prayakhi Emee Dutta, Rosy Sarmah
    2026
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    3Twin-attention Based Masked Swin Transformer for Anomaly Detection
    Anilkumar Vishwanath Brahmane, Dipak Devchand Bage, Satpalsing Devising Rajput, Ritu Dudhmal, Dhanraj Somling Jadhav, Vijay Arun Kotkar
    2026
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    4Predicting Building Fitness Ranks Using a Hybrid Evaluation Method on Earthquake Damage Data
    Moram Vishnu Vardhana Rao, Aparna Chaparala, Kusuma Kumari Katakam, G.Apparao Naidu, N. D. S. S. Kiran Relangi, Radhika Sajja
    2026
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    5Recognition of Critical Built-up Areas Located on High-hill Slope Regions Using Decision Tree Technique.
    B. G. Kodge

    In mountainous places, structures are being built for residential or commercial uses without the necessary safety precautions. Every year, landslides, torrential downpours, severe snowfall, earthquakes, volcanic eruptions, and floods cause buildings to collapse. The bulk of them are found in high-hill slope areas with loose soil types, close to river flows and other sorts of water sources. Therefore, these incidents have claimed thousands of lives. This paper deals with the process of automatic identification of critical buildings (residential/commercial) located in mountainous area which are on high-hill-slope, close to river flows, having loose soil type and high variations in land elevation contours. This study uses the primary data like, built-up/residential area and water body areas which are extracted from sample land use and land cover (LULC) using image classification techniques, and another important data like slope map and land elevation contour maps which are generated from digital elevation model (DEM). In addition, the supplementary data like, river maps, soil maps and other base maps, are also collected. All the data are integrated and taken into consideration for the identification and extraction of critical residential/build-up areas using spatial data mining technique.

    2026
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    高被引作者

    作者引用发文
    V. Ravi833
    Domenico Ursino705
    Jens Christian Hühn621
    Eyke Hüllermeier621
    Vassilios S. Verykios541
    Alexandros Karakasidis541
    Vassilios K. Mitrogiannis541
    Kuntal Maji491
    Maciej Piasecki482
    Ashraf El-Sisi451

    高产作者

    作者引用发文
    Domenico Ursino705
    Mohamed Batouche293
    Thangavel K123
    Pasquale De Meo413
    V. Ravi833
    Giovanni Quattrone413
    Alfredo Cuzzocrea253
    Mohamed Khireddine Kholladi243
    Woraphon Yamaka02
    Shamik Sural312

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