TEMPERATURE AND TIME SERIES ANALYSIS USING K-MEANS CLUSTERING

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DC Field	Value	Language
dc.contributor.author	M, Rajeshwari	-
dc.contributor.author	D, Sowndhariya	-
dc.date.accessioned	2020-06-17T11:21:49Z	-
dc.date.available	2020-06-17T11:21:49Z	-
dc.date.issued	2019-12	-
dc.identifier.issn	0374-8588	-
dc.identifier.uri	http://localhost:8080/xmlui/handle/123456789/235	-
dc.description.abstract	This paper analyses the nature of the monthly maximum and minimum temperature in the Sao paulo station the temperatures recorded at division between 1979 and 2019. Sao paulo in the Southeast Region of Brazil. Analysing temperature on the monthly base January to December and quarterly base December, January and February, March to May, June to August, September to November to find out temperature status weather they have increased or decreased from month to month. the temperature and time series affect the people’s life cycle. The analysis the temperature and time series analysis at sao Paulo station using K-Means clustering analyse.	en_US
dc.language.iso	en	en_US
dc.publisher	Journal of The Gujarat Research Society	en_US
dc.subject	Temperatures	en_US
dc.subject	Time series	en_US
dc.subject	Sao paulo	en_US
dc.subject	K-Means clustering	en_US
dc.title	TEMPERATURE AND TIME SERIES ANALYSIS USING K-MEANS CLUSTERING	en_US
dc.type	Article	en_US
Appears in Collections:	International Journals

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