journal article·2026-07-22Open access

Effectiveness Evaluation of Emergency Communication Networks Based on Combined Weighting—Cloud Model—TOPSIS Method

Xiangchen Wang, Wei Zhu, Zhenyi Ke, Chenzhe Zhong

Applied Sciences· Volume 16· Issue 14

Abstract

Emergency communication support is a critical prerequisite for effective disaster response. To address the problems of one-sided indicator weighting and the uncertain quantification of qualitative indicators in emergency communication network evaluation, this study proposes a combined weighting–cloud model–TOPSIS framework. First, an evaluation indicator system is constructed from four dimensions: transmission performance, coverage capability, service quality, and survivability. Second, an FAHP–entropy combined weighting strategy is used to integrate expert knowledge and data-driven information. Third, a backward cloud generator is introduced to quantify qualitative indicators while preserving both fuzziness and randomness; triangular fuzzy numbers and relative preference relations are further used to convert cloud outputs into comparable scalar values. Finally, TOPSIS is applied to rank alternative emergency communication plans. A flood rescue case study and additional sensitivity tests show that the ranking of the three plans remains stable under perturbations of weights, input data, and indicator inclusion. This paper also provides the raw input data, expert scoring details, simulation assumptions, and a comparison with other MCDA methods to improve reproducibility.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Multi-Criteria Decision Making · Flood Risk Assessment and Management · Facility Location and Emergency Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Information and Communication, National University of Defense Technology, Wuhan 430035, China

References (22)

Show source-provided references
1. Rabahi, F.Z., Boudjit, S., and Benarous, L. (2023, January 23–26). UAV-Assisted Mesh Network for Emergency Communication in Disaster Areas. Proceedings of the International Symposium on Networks, Computers and Communications (ISNCC), Doha, Qatar.10.1109/ISNCC58260.2023.10323653 ↗
2. A four-quadrant mobility model-based routing protocol for post-earthquake emergency communication network10.1186/s13638-021-02017-y ↗
3. Online Positioning of a Drone-Mounted Base Station in Emergency Scenarios10.1109/TVT.2023.3329960 ↗
4. Wang, X., Li, D., Zhang, X., and Cao, Y. (2018). MCDM-ECP: Multi Criteria Decision Making Method for Emergency Communication Protocol in Disaster Area Wireless Network. Appl. Sci., 8.10.3390/app8071165 ↗
5. Hwang, C.L., and Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications, Springer.10.1007/978-3-642-48318-9 ↗
6. A state-of the-art survey of TOPSIS applications10.1016/j.eswa.2012.05.056 ↗
7. Chen, S.J., and Hwang, C.L. (1992). Fuzzy Multiple Attribute Decision Making: Methods and Applications, Springer.10.1007/978-3-642-46768-4 ↗
8. Extensions of the TOPSIS for group decision-making under fuzzy environment10.1016/S0165-0114(97)00377-1 ↗
9. A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method10.1016/j.eswa.2009.03.039 ↗
10. Extension of the TOPSIS method for decision-making problems with interval data
11. Membership Clouds and Membership Cloud Generators
12. A new cognitive model: Cloud model10.1002/int.20340 ↗
13. Generic normal cloud model10.1016/j.ins.2014.04.051 ↗
14. Multi-criteria group decision-making with cloud model and TOPSIS for alternative selection under uncertainty10.1007/s00500-022-07189-3 ↗
15. Gaussian cloud and TOPSIS based power supply quality evaluation method10.1016/j.egyr.2022.10.093 ↗
16. 6G service-oriented space-air-ground integrated network: A survey10.1016/j.cja.2021.12.013 ↗
17. A survey on space-air-ground-sea integrated network security in 6G10.1109/COMST.2021.3131332 ↗
18. Service-oriented network resource orchestration in space-air-ground integrated network10.1109/TVT.2023.3301676 ↗
19. Kourtis, M.A., Xilouris, G., Batistatos, M., Kourtis, A., and Markakis, A. (2023, January 9–12). Emergency communications leveraging decentralized swarm computing. Proceedings of the Cyber-Physical Systems and Internet of Things Week 2023 (CPS-IoT Week Workshops ’23), San Antonio, TX, USA.10.1145/3576914.3588019 ↗
20. An adaptive and distributed network selection mechanism for 5G networks10.1016/j.comnet.2021.107943 ↗
21. Zhang, T., Liu, H., Zhou, Y., Lopez-Benitez, M., Lim, E., Ma, F., and Yu, L. (2021, January 27–29). A network selection optimization algorithm based on AHP and TOPSIS in heterogeneous network environment. Proceedings of the 2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT), Sanya, China.10.1109/CECIT53797.2021.00025 ↗
22. I-MEREC-T: Improved MEREC-TOPSIS scheme for optimal network selection in 5G heterogeneous network for IoT10.1016/j.iot.2023.100748 ↗