Issue |
MATEC Web Conf.
Volume 392, 2024
International Conference on Multidisciplinary Research and Sustainable Development (ICMED 2024)
|
|
---|---|---|
Article Number | 01154 | |
Number of page(s) | 8 | |
DOI | https://doi.org/10.1051/matecconf/202439201154 | |
Published online | 18 March 2024 |
Hybrid model for comprehensive covid-19 regional safety, risk assessment, and advanced vaccine analysis
1 Department of Computer Science and Engineering, Hyderabad institute of Technology and Management, Hyderabad
2 Department of CSE, KG Reddy College of Engineering and Technology, Chilukuru Village, Hyderabad
3 Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh, India 522502
4 Department of EEE, Institute of Aeronautical Engineering, Hyderabad
5 Rajeev Institute of Technology, Hassan
6 Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur District, Andhra Pradesh - 522302, India
7 Information Technology, Kings Engineering College, Sriperumbudur 602117, India
* Corresponding author: ilachandana@gmail.com
Advancements in transportation infrastructure, shifts in consumption tendencies, and factors like COVID-19 have raised the need and burden on freight transportation. Various firms are assessing freight transportation systems' long-term viability, speed, and robustness worldwide, requiring data and measurement instruments for freight fluidity. This research attempts to provide a hybrid model to analyze the effects of COVID-19 and the subsequent production methods for the manufacturing sector. This work introduces a new and robust integration method by combining the Ordinal Priority Model (OPM) and Fuzzy-based Distance from Average Solution (F-EDAS) for the first time. The OPM approach was used to assess and measure the adverse effects of the epidemic. Production plans were thoroughly considered utilizing the F-EDAS approach. Digitalization and on-site renewable energy are identified as the most crucial recovery methods. The multi-scenario ranking findings assist managers in making resource-allocation choices for implementing post-COVID-19 production plans.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.