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

  1. Singh, Neha / Sharma, R. L. / Yadav, Kundan: Sustainable Solutions: Exploring Supplementary Cementitious Materials in Construction. In: Iranian Journal of Science and Technology, Transactions of Civil Engineering.

    https://doi.org/10.1007/s40996-024-01585-5

  2. Gupta, Laxmi / Sharma, R. L. (2023): ODDTCN energy modeling: a meta-heuristic-aided energy performance designing and consumption forecasting in existing building environment. In: Asian Journal of Civil Engineering, v. 25, n. 2 (Oktober 2023).

    https://doi.org/10.1007/s42107-023-00907-8

  3. Yadav, Kundan / Sharma, R. L. (2023): Comparative study of biochar and charcoal and their application in the construction industry. In: Asian Journal of Civil Engineering, v. 25, n. 2 (Oktober 2023).

    https://doi.org/10.1007/s42107-023-00835-7

  4. Gulghane, Akshay / Sharma, R. L. / Borkar, Prashant (2023): A formal evaluation of KNN and decision tree algorithms for waste generation prediction in residential projects: a comparative approach. In: Asian Journal of Civil Engineering, v. 25, n. 1 (Juli 2023).

    https://doi.org/10.1007/s42107-023-00772-5

  5. Singh, Neha / Sharma, R. L. / Yadav, Kundan (2023): Sustainable development by carbon emission reduction and its quantification: an overview of current methods and best practices. In: Asian Journal of Civil Engineering, v. 24, n. 8 (Juni 2023).

    https://doi.org/10.1007/s42107-023-00732-z

  6. Gulghane, Akshay / Sharma, R. L. / Borkar, Prashant (2023): Performance analysis of machine learning-based prediction models for residential building construction waste. In: Asian Journal of Civil Engineering, v. 24, n. 8 (Juni 2023).

    https://doi.org/10.1007/s42107-023-00708-z

  7. Gulghane, Akshay / Sharma, R. L. / Borkar, Prashant (2023): Quantification analysis and prediction model for residential building construction waste using machine learning technique. In: Asian Journal of Civil Engineering, v. 24, n. 6 (April 2023).

    https://doi.org/10.1007/s42107-023-00580-x

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