… the mixture design of sustainable concrete. To this end, six machine learning techniques, …
algorithm, artificial neural network, support vector machine, and regression, are applied in …

… Findings indicate that machine learning can significantly improve process efficiencies, …
machine learning and advanced storage, can contribute to a sustainable and pollution-free future. …

… To show the effectiveness of the proposed machine learning method, the results of this
research were compared with the other learning techniques. Specifically, several comparisons …

… Overall, this study highlights the importance of sustainability-oriented perspectives in energy
policy development and the potential role of AI and machine learning in policy formulation. …

… study are: (1) to develop accurate machine learning prediction models (DT, AR, SVM) for
durability characteristics estimation of BCC to promote the sustainable utilization of SCMs in the …

… various applications that incorporate machine learning and deep learning techniques. Figure
… is based on sustainable energy sources, the usage of machine learning and deep learning …

… -scaling groups, Amazon Machine Image, EC2 … machine learning based approach to
implement horizontal elasticity for containerized application to maintain the system sustainability. …

… sustainable energy systems by presenting a novel multidimensional framework for integrating
AI and machine learning … the energy sector for a sustainable future, including process flow, …

… During this study, it was noted that there is incremental application of machine learning
techniques to develop PdM applications. Integrating PdM and machine learning in some …

… : “smart cities” or “sustainable urban development” and all … sustainable urban development.
The search in the major research databases revealed that the popularity of machine learning …