Fuzzy clustering using Hybrid CSO-PSO search based on Community mobility during COVID 19 lockdown

2Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Recently COVID-19 virus had made a potential threat to humanity. The effect of mobility habits might be considerably high in the spread of disease. This work analyzes the mobility patterns in selected districts of Tamilnadu and applies Fuzzy C-Means clustering based hybrid variant of cuckoo search combined with best features from particle swarm optimisation. Google Community Mobility reports are taken for the experimental purpose and 26 districts in Tamilnadu are considered. The decision regarding the restricted movement of people can be made from the results. The correlation between human mobility during and after lockdown to the disease spread is analysed. The results are evaluated using internal indices like Silhouette and DB index. The regions are classified into high, medium and low risk regions with relevance to the human mobility.

Cite

CITATION STYLE

APA

Parvathavarthini, S., R V, N., Chowdry B, S., & Siva Prakash, K. (2021). Fuzzy clustering using Hybrid CSO-PSO search based on Community mobility during COVID 19 lockdown. In Proceedings - 5th International Conference on Computing Methodologies and Communication, ICCMC 2021 (pp. 1515–1519). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICCMC51019.2021.9418026

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free