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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2019.8(3): 2556-2560
DOI: https://doi.org/10.20546/ijcmas.2019.803.303


Identification of the Best Model for Forecasting of Sugar Production among Linear and Non-linear Model
J. Megha*, Y.N. Havaldar, N.L. Pavithra, B.B. Jyoti and V. Kiran Kumar
University of Agriculture Sciences, Dharwad, Krishinagar, Dharwad-580005, Karnataka, India
*Corresponding author
Abstract:

The present study “Identification of the best model for forecasting of sugar production among linear and non-linear model.” emphasis on the factors affecting production of sugar in India as sugar is one of the most important commodities; produced and consumed around the world. India is the 2nd largest producer of sugar in the world next to Brazil and also largest consumer of sugar. Time series data on sugar production and sugarcane area and production was collected from the year 1990-91 to 2015-16. Linear and non-linear models were used to identify the best model for forecasting of sugar production. Among all models selected the compound model was found to be best fit with highest R2, minimum root mean square error and standard error. The cubic and linear models were also showed significantly best fit for predicting the sugar production based on sugarcane area. The cubic model was found to be best fit with highest R2, minimum mean square error and standard error. Linear model was also found to be the best fit for predicting sugar production by sugarcane production.


Keywords: Sugar Production Linear and Non-linear Model
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How to cite this article:

Megha, J., Y.N. Havaldar, N.L. Pavithra, B.B. Jyoti and Kiran Kumar, V. 2019. Identification of the Best Model for Forecasting of Sugar Production among Linear and Non-linear Model.Int.J.Curr.Microbiol.App.Sci. 8(3): 2556-2560. doi: https://doi.org/10.20546/ijcmas.2019.803.303