Zobrazeno 1 - 6
of 6
pro vyhledávání: '"P. S., Maya Gopal"'
Publikováno v:
International Journal of Agricultural and Environmental Information Systems. 11:48-66
This article reviews various aspects of research concerning the background and state-of-the-art of big data in agriculture. This article focuses on data generation, storage, analysis and visualization in big data. In every phase, technical challenges
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::195c4a079149f08af6d77d773d8bd256
https://doi.org/10.4018/ijaeis.2020010103
https://doi.org/10.4018/ijaeis.2020010103
Autor:
P. S., Maya Gopal1 (AUTHOR) mayagopal.ps2016@vitstudent.ac.in, R., Bhargavi1 (AUTHOR)
Publikováno v:
Applied Artificial Intelligence. 2019, Vol. 33 Issue 7, p621-642. 22p.
Autor:
R. Bhargavi, P S Maya Gopal
Publikováno v:
Applied Artificial Intelligence. 33:621-642
The rapid innovations and liberalized market economy in agriculture demand accuracy in Crop Yield Prediction (CYP). In accurate prediction, machine learning (ML) algorithms and the selected feature...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0594107c0f6336214ef1e953a55b149
https://doi.org/10.1080/08839514.2019.1592343
https://doi.org/10.1080/08839514.2019.1592343
Autor:
R. Bhargavi, P. S. Maya Gopal
Publikováno v:
Applied Engineering in Agriculture. 35:9-14
In agriculture, crop yield prediction is critical. Crop yield depends on various features which can be categorized as geographical, climatic, and biological. Geographical features consist of cultivable land in hectares, canal length to cover the cult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8909c0fd63da82ebb5001f509011ab71
https://doi.org/10.13031/aea.12938
https://doi.org/10.13031/aea.12938
Autor:
P S Maya Gopal, R. Bhargavi
Publikováno v:
Computers and Electronics in Agriculture. 165:104968
Crop yield prediction is one of the challenging task in agricultural domain. Extensive research in agricultural domain has been carried out to predict better crop yield using the machine learning algorithm Artificial Neural Network (ANN) and statisti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3cf6c996a7945ea1e21f26848d645fd5
https://doi.org/10.1016/j.compag.2019.104968
https://doi.org/10.1016/j.compag.2019.104968
Autor:
S, Maya Gopal P, R, Bhargavi
Publikováno v:
International Journal of Agricultural and Environmental Information Systems; July 2019, Vol. 10 Issue: 3 p54-71, 18p