Artificial Intelligence for Sustainability: An Overview
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49979-1_1
Reference21 articles.
1. Agrawal, A., Gans, J., & Goldfarb, A. (2017, February 7). What to expect from artificial intelligence. Sloan Management Review. https://sloanreview.mit.edu/article/what-to-expect-from-artificial-intelligence/
2. Ahmed, I., Jeon, G., & Piccialli, F. (2022). From artificial intelligence to explainable artificial intelligence in industry 4.0: A survey on what, how, and where. IEEE Transactions on Industrial Informatics, 18(8), 5031–5042. https://doi.org/10.1109/TII.2022.3146552
3. Albayrak Ünal, Ö., Erkayman, B., & Usanmaz, B. (2023). Applications of artificial intelligence in inventory management: A systematic review of the literature. Archives of Computational Methods in Engineering, 30, 2605–2625. https://doi.org/10.1007/s11831-022-09879-5
4. Brynjolfsson, E., Rock, D., & Syverson, C. (2019). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. In A. Agrawal, J. Gans, & A. Goldfarb (Eds.), The economics of artificial intelligence: An agenda (pp. 23–57). University of Chicago Press.
5. Dargan, S., Kumar, M., Ayyagari, M. R., & Kumar, G. (2020). A survey of deep learning and its applications: A new paradigm to machine learning. Archives of Computational Methods in Engineering, 27(4), 1071–1092. https://doi.org/10.1007/s11831-019-09344-w
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