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Since heavy rain can beget numerous disasters, downfall vaticination is pivotal. The cast should be accurate, and it also encourages people to take preventives. For nations like India, whose frugality is largely dependent on husbandry, the delicacy of the downfall statement is veritably important. Due to the atmosphere's dynamic character, applied mathematics ways are unfit to guarantee dependable perfection for a statement about rush. Retrogression may be used in the vaticination of rush utilising machine learning approaches. The thing of this design is to make the styles and approaches used in the field of rush vaticination accessible tonos-experts while also furnishing a comparison of the colourful machine learning algorithms. [ABSTRACT FROM AUTHOR]

In this paper, bibliometric analysis of scientific literature published during the period 1996-2020 in.the field of Applied Mathematics has been presented using Scopus linked SCImago country ranking database. Further, India's contribution at global level is highlighted in particular using key bibliometric indicators namely document published, citations (external/self) and citations per document along with their annual corresponding growth to validate the findings. India is growing exponentially and contributing 2.5% to global research output with average 11.63% of annual corresponding growth. In addition, citations (external/self) and citations per document show average annual corresponding growth within ±5%. The outcomes of this study could foster new policies and the improvement in existing policies for various research activities especially for India. [ABSTRACT FROM AUTHOR]