Abstract
Noise pollution is escalating at an alarming rate as a one of the critical outcomes of urbanization. This led to harmful effect on the health of human being as it can cause annoyance, hypertension, heart disease, and sleep disturbances. Despite all measures to control noise pollution that have been taken in Mumbai so far, those are prone to vulnerabilities. The differences in these vulnerability-inducing causes arise a need for an effective analysis. The motive of this paper is to have data mining to come to aid to create a model that provides the heterogeneity of the data by grouping similar objects together to find the noise pollution regions in the Mumbai state with respect to different factors.
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Agarwal, A., Chaudhary, P., Majumdar, R., Chowdhary, S.K., Srivastava, A. (2020). Identification of Noise Pollution Prone Regions in Mumbai Using Expectation-Maximization Clustering Technique. In: Mandal, J., Bhattacharya, D. (eds) Emerging Technology in Modelling and Graphics. Advances in Intelligent Systems and Computing, vol 937. Springer, Singapore. https://doi.org/10.1007/978-981-13-7403-6_1
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DOI: https://doi.org/10.1007/978-981-13-7403-6_1
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