Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Proposal of Machine Learning Algorithm for the Construction and Demolition Waste Prediction Rate
The construction field in India is growing rapidly due to urbanization, industrialization, modernization and population expansion. This expansion results in significant construction and demolition (C&D) waste produced when structures are constructed, renovated, repaired or demolished.
Artificial Intelligence (AI) and Machine Learning (ML) plays an important role in solving this problem by turning C&D waste into construction materials, thereby promoting a circular and sustainable economy.AI optimizes the entire process of turning waste into construction materials, from collection and classification to material processing and construction. Advanced analytics and ML algorithms are leveraged to effectively manage waste, reduce environmental impact and promote sustainability. This article proposes a process for developing ML algorithms to analyze C&D waste generation rates and explores future trends in this field. Integrating AI into waste management in the construction field promises a greener and more efficient future.
A methodology for implementation of various Machine Learning model like support vector machines (SVM), K-nearest neighbors (KNN), random forests (RF), artificial neural networks (ANN), and linear regression (LR) etc., are given in the form of an algorithm.
As waste C&D increases rapidly, waste management becomes necessary so information about waste generation is needed. In this article, different methods applied to predict C&D waste by applying AI will be explained.
Proposal of Machine Learning Algorithm for the Construction and Demolition Waste Prediction Rate
The construction field in India is growing rapidly due to urbanization, industrialization, modernization and population expansion. This expansion results in significant construction and demolition (C&D) waste produced when structures are constructed, renovated, repaired or demolished.
Artificial Intelligence (AI) and Machine Learning (ML) plays an important role in solving this problem by turning C&D waste into construction materials, thereby promoting a circular and sustainable economy.AI optimizes the entire process of turning waste into construction materials, from collection and classification to material processing and construction. Advanced analytics and ML algorithms are leveraged to effectively manage waste, reduce environmental impact and promote sustainability. This article proposes a process for developing ML algorithms to analyze C&D waste generation rates and explores future trends in this field. Integrating AI into waste management in the construction field promises a greener and more efficient future.
A methodology for implementation of various Machine Learning model like support vector machines (SVM), K-nearest neighbors (KNN), random forests (RF), artificial neural networks (ANN), and linear regression (LR) etc., are given in the form of an algorithm.
As waste C&D increases rapidly, waste management becomes necessary so information about waste generation is needed. In this article, different methods applied to predict C&D waste by applying AI will be explained.
Proposal of Machine Learning Algorithm for the Construction and Demolition Waste Prediction Rate
Sustain. Civil Infrastruct.
Choudhary, Lokesh (Herausgeber:in) / Sahu, Vaishali (Herausgeber:in) / Garg, Aman (Herausgeber:in) / Arpitha, L. M. (Autor:in) / Kumar, R. Anil (Autor:in) / Fathima, Zoya (Autor:in) / Yeshaswini, R. (Autor:in) / Dhanyashree, G. (Autor:in)
International Conference on Technological Innovation in Multidisciplinary Engineering and Sciences ; 2024 ; Gurgaon, India
25.02.2025
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
| ArXiv | 2024
Construction and Demolition Waste
| Springer Verlag | 2019
Construction and Demolition Waste
| British Library Online Contents | 2000