Abstract Stone dust induced risk and vulnerability in the developing nations is very thought-provoking and therefore is necessary to address scientifically to manage it. Identifying vulnerable areas using the robust method is preliminary and essential steps. The present study has intended to delineate Human health vulnerability models (HHVMs) using machine learning algorithms and justify whether ensemble prediction can provide improved results in stone quarry and crushing dominated Middle catchment of Dwarka river basin. Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), Reduced Error Pruning (REP) Tree, Gaussian Process algorithms and ensemble prediction have been applied for HHV modelling. Total 6.9 to 7.37% in cluster 1, 9.11 to 9.6% in cluster 2, 19.63 to 26.79% and 5.34 to 12.85% areas in cluster 3 and 4 is found into very high human health vulnerable class as per the five applied models. REPTree model is found consistent for predicting vulnerability in case of all the clusters followed by GP model. As per the result of RMSE, the RF model is appeared as the most consistent model followed by REPTree. Some of the ensemble prediction models are potential for yielding improved result than individual algorithm.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Modelling human health vulnerability using different machine learning algorithms in stone quarrying and crushing areas of Dwarka river Basin, Eastern India


    Beteiligte:
    Mandal, Indrajit (Autor:in) / Pal, Swades (Autor:in)

    Erschienen in:

    Advances in Space Research ; 66 , 6 ; 1351-1371


    Erscheinungsdatum :

    2020-05-22


    Format / Umfang :

    21 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    The motor ships "Dumra" and "Dwarka"

    Engineering Index Backfile | 1923


    Suggestions for minimizing accidents in quarrying and crushing

    Leh, H.R. | Engineering Index Backfile | 1929



    Stone crushing device for geological exploration

    LIU YIHUI / YANG SHENGWEI | Europäisches Patentamt | 2021

    Freier Zugriff

    Ship special for stone crushing and provided with multiple sets of gravity type stone crushing equipment

    WANG NAN / SUN QINGSONG / SHAO MIN | Europäisches Patentamt | 2023

    Freier Zugriff