Zobrazeno 1 - 4
of 4
pro vyhledávání: '"G. H. Harish Nayak"'
Autor:
G. H. Harish Nayak, Md Wasi Alam, K. N. Singh, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, Chandan Kumar Deb
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-26 (2024)
Abstract Accurately predicting agricultural commodity prices is crucial for India's economy. Traditional parametric models struggle with stringent assumptions, while machine learning (ML) approaches, though data-driven, lack automatic feature extract
Externí odkaz:
https://doaj.org/article/3c3f82bed9ae413d868a2b0d8830f1de
Publikováno v:
Journal of Experimental Agriculture International. 45:16-23
The current study was carried out to analyze the trend and forecast in area, production and productivity of mango crop in Karnataka. It was determined by using the secondary data of area, production and productivity of mango for the period of 18 year
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ecc7c1b31387fb95ea128b8fda6a8991
https://doi.org/10.9734/jeai/2023/v45i52116
https://doi.org/10.9734/jeai/2023/v45i52116
Autor:
G. H. Harish Nayak, A. Varalakshmi, M. G. Manjunath, G. Avinash, null Veershetty, Moumita Baishya
Publikováno v:
Journal of Experimental Agriculture International. 45:28-35
Coffee is a significant commodity crop worldwide, and Karnataka, an Indian state with coffee-growing regions such as Chikkamagaluru, Kodagu, and Hassan, is a major producer. Chikkamagaluru, also known as the Coffee Land of Karnataka, is the primary l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::611c6cdd07e2c432fdb1fbafe9ec8271
https://doi.org/10.9734/jeai/2023/v45i42113
https://doi.org/10.9734/jeai/2023/v45i42113
Autor:
G. H. Harish Nayak, A. Varalakshmi, M. G. Manjunath, null Veershetty, G. Avinash, Moumita Baishya
Publikováno v:
Journal of Experimental Agriculture International. 45:36-48
Precise estimation of rainfall is a crucial and challenging task in environmental science. It involves the use of advanced and powerful models to forecast non-linear and dynamic changes in rainfall. Deep learning, a recently developed method for hand
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cde0b5251cffbd346fa808232a926eea
https://doi.org/10.9734/jeai/2023/v45i42114
https://doi.org/10.9734/jeai/2023/v45i42114