A development in the approach of assessing the sensitivity of road networks to environmental hazards using functional machine learning algorithm and fractal methods-Reference-Cited by-同舟云学术

A development in the approach of assessing the sensitivity of road networks to environmental hazards using functional machine learning algorithm and fractal methods

Published:2023-09-01 Issue: Volume: Page:
ISSN:1387-585X
Container-title:Environment, Development and Sustainability
language:en
Short-container-title:Environ Dev Sustain

Author:

Nayyeri Hadi^ORCID,Xu Lei,Ahmadi Dehrashid Atefeh^ORCID,Mohammadi Khanghah Payam

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Economics and Econometrics,Geography, Planning and Development

Link

https://link.springer.com/content/pdf/10.1007/s10668-023-03800-1.pdf

Reference72 articles.

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3. Adnan, R. M., Dai, H.-L., Kuriqi, A., Kisi, O., & Zounemat-Kermani, M. (2023a). Improving drought modeling based on new heuristic machine learning methods. Ain Shams Engineering Journal, 14(10), 102168. https://doi.org/10.1016/j.asej.2023.102168

4. Adnan, R. M., Dai, H.-L., Mostafa, R. R., Islam, A. R. M. T., Kisi, O., Elbeltagi, A., & Zounemat-Kermani, M. (2023b). Application of novel binary optimized machine learning models for monthly streamflow prediction. Applied Water Science, 13(5), 110. https://doi.org/10.1007/s13201-023-01913-6

5. Adnan, R. M., Mostafa, R. R., Dai, H.-L., Heddam, S., Kuriqi, A., & Kisi, O. (2023c). Pan evaporation estimation by relevance vector machine tuned with new metaheuristic algorithms using limited climatic data. Engineering Applications of Computational Fluid Mechanics, 17(1), 2192258. https://doi.org/10.1080/19942060.2023.2192258

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