Publication Type:

Journal Article

Source:

International Journal of Pure and Applied Mathematics, Academic Press, Volume 118, Number 18, p.2899-2902 (2018)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85048987235&partnerID=40&md5=b2f20a17a928305d5f525c03b73a81a7

Abstract:

Incorporating the technology into the Agriculture field for triggering the growth and identifying the pest/disease in various crops is the state of art. Extreme Changes in the weather parameters during the growth phase of crops causes serious threats which tends to go in search for new adaptive measures. The main aim of this work is to predict the occurrence of the pest in cotton crop based on such weather factors using clustering techniques. A change in any of these meteorological factors fluctuates the infestation of the pest between higher and lower. The values of the weather parameters computed which cause the occurrence of these pests can be used for prediction and precautionary measures can be taken ahead. © 2017 Academic Press. All Rights Reserved.

Notes:

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Cite this Research Publication

Shanmuga Priya S. and Abinaya, M., “Feature selection using random forest technique for the prediction of pest attack in cotton crops.”, International Journal of Pure and Applied Mathematics, vol. 118, pp. 2899-2902, 2018.