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IJSTR >> Volume 8 - Issue 11, November 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Application Of Hybrid Model For Forecasting Prices Of Jasmine Flower In Bangalore, India

[Full Text]

 

AUTHOR(S)

Sunil, Satyanarayana, Sachin Acharya, Arun Kumar Jogi

 

KEYWORDS

SARIMA, ANN, Extreme Learning Machine, Multi –Layer Perceptron

 

ABSTRACT

The medicinal uses of Jasmine are well documented. It is used to enhance the immunity of the body, treatment of anxiety, stress, and sunstroke. The leaves are used in the treatment of mouth disease, treatment of cuts and wounds. The Jasmine plant is also the source of exotic fragrance. It is an important scent noted in perfumes and has herbal properties and hence today, Jasmine flowers are of much economic importance. Farmer’s decision making on production of Jasmine depends on future price to be realised during the period of cultivation. Hence forecasting accuracy plays a vital role in Jasmine production. A hybrid model has been considered an effective way to improve the forecast accuracy. In this paper, hybrid model of SARIMA-ANN is proposed for forecasting the prices of Jasmine flower. We also compared the performance of hybrid model with traditional SARIMA model, ELM, MLP and NNETAR (ANN). The study concluded that the hybrid model of ARIMA-ANN is more appropriate model for forecasting the prices of Jasmine flower. The best model is used to forecast prices for next 12 months.

 

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