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Abul Kashem

Die folgende Bibliografie enthält alle in dieser Datenbank indizierten Veröffentlichungen, die mit diesem Namen als Autor, Herausgeber oder anderweitig Beitragenden verbunden sind.

  1. Islam, Md Mahamodul / Das, Pobithra / Rahman, Md Mahbubur / Naz, Fasiha / Kashem, Abul / Nishat, Mosaraf Hosan / Tabassum, Nujhat (2024): Prediction of compressive strength of high-performance concrete using optimization machine learning approaches with SHAP analysis. In: Journal of Building Pathology and Rehabilitation, v. 9, n. 2 (29 Mai 2024).

    https://doi.org/10.1007/s41024-024-00445-z

  2. Das, Pobithra / Kashem, Abul / Islam, Mominul / Ahmed, Asif / Aminul Haque, M. / Khan, Mehran (2024): Alkali-activated binder concrete strength prediction using hybrid-deep learning along with shapely additive explanations and uncertainty analysis. In: Construction and Building Materials, v. 435 (Juli 2024).

    https://doi.org/10.1016/j.conbuildmat.2024.136711

  3. Kashem, Abul / Karim, Rezaul / Malo, Somir Chandra / Das, Pobithra / Datta, Shuvo Dip / Alharthai, Mohammad (2024): Hybrid data-driven approaches to predicting the compressive strength of ultra-high-performance concrete using SHAP and PDP analyses. In: Case Studies in Construction Materials, v. 20 (Juli 2024).

    https://doi.org/10.1016/j.cscm.2024.e02991

  4. Kashem, Abul / Karim, Rezaul / Das, Pobithra / Datta, Shuvo Dip / Alharthai, Mohammad (2024): Compressive strength prediction of sustainable concrete incorporating rice husk ash (RHA) using hybrid machine learning algorithms and parametric analyses. In: Case Studies in Construction Materials, v. 20 (Juli 2024).

    https://doi.org/10.1016/j.cscm.2024.e03030

  5. Das, Pobithra / Kashem, Abul / Hasan, Imrul / Islam, Mominul (2024): A comparative study of machine learning models for construction costs prediction with natural gradient boosting algorithm and SHAP analysis. In: Asian Journal of Civil Engineering, v. 25, n. 4 (Februar 2024).

    https://doi.org/10.1007/s42107-023-00980-z

  6. Das, Pobithra / Kashem, Abul (2024): Hybrid machine learning approach to prediction of the compressive and flexural strengths of UHPC and parametric analysis with shapley additive explanations. In: Case Studies in Construction Materials, v. 20 (Juli 2024).

    https://doi.org/10.1016/j.cscm.2023.e02723

  7. Karim, Rezaul / Islam, Md. Hamidul / Datta, Shuvo Dip / Kashem, Abul (2024): Synergistic effects of supplementary cementitious materials and compressive strength prediction of concrete using machine learning algorithms with SHAP and PDP analyses. In: Case Studies in Construction Materials, v. 20 (Juli 2024).

    https://doi.org/10.1016/j.cscm.2023.e02828

  8. Islam, Naimul / Kashem, Abul / Das, Pobithra / Ali, Md. Nimar / Paul, Sourov (2023): Prediction of high-performance concrete compressive strength using deep learning techniques. In: Asian Journal of Civil Engineering, v. 25, n. 1 (Juli 2023).

    https://doi.org/10.1007/s42107-023-00778-z

  9. Paul, Sourov / Das, Pobithra / Kashem, Abul / Islam, Naimul (2023): Sustainable of rice husk ash concrete compressive strength prediction utilizing artificial intelligence techniques. In: Asian Journal of Civil Engineering, v. 25, n. 2 (Oktober 2023).

    https://doi.org/10.1007/s42107-023-00847-3

  10. Kashem, Abul / Das, Pobithra (2023): Compressive strength prediction of high-strength concrete using hybrid machine learning approaches by incorporating SHAP analysis. In: Asian Journal of Civil Engineering, v. 24, n. 8 (Juni 2023).

    https://doi.org/10.1007/s42107-023-00707-0

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