Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Mst. Noorunnahar"'
Publikováno v:
Journal of Agriculture and Food Research, Vol 14, Iss , Pp 100667- (2023)
This study examines the effects of climate and non-climatic parameters on maize yield in Bangladesh from 1980 to 2020. The research used the autoregressive distributed lag-bounds (ARDL) method to determine the short run and long-run relationship betw
Externí odkaz:
https://doaj.org/article/75ce8d008aa645ac8d91db7b9bb3b8cc
Publikováno v:
PLoS ONE, Vol 18, Iss 3, p e0283452 (2023)
In this study, we attempt to anticipate annual rice production in Bangladesh (1961-2020) using both the Autoregressive Integrated Moving Average (ARIMA) and the eXtreme Gradient Boosting (XGBoost) methods and compare their respective performances. On
Externí odkaz:
https://doaj.org/article/ce5310cd3d5f445cab6b8d31e3ee5391
Autor:
Mst. Noorunnahar, Maksuda Akter Mily, Lima Khatun, Md. Ashiqur Rahman, Rayhan Ahmmed Pranto, Khandoker Saif Uddin
Publikováno v:
Asian Journal of Research in Infectious Diseases. 12:22-33
Bangladesh is facing unpredictable weather patterns, as well as a consistent rise in temperature and precipitation. Climate change has had a negative impact on physical and mental health, leading to an increase mostly in the prevalence and variation
Autor:
Mohammad Nazmol Hasan, Md Parvez Mosharaf, Khandoker Saif Uddin, Keya Rani Das, Nasrin Sultana, Mst. Noorunnahar, Darun Naim, Md. Nurul Haque Mollah
In different regions of the world, cowpea (Vigna unguiculata (L.) Walp.) is an important vegetable and an excellent source of protein. It lessens the malnutrition of the underprivileged in developing nations and has some positive effects on health, s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6a35321d44cec79ce3c81b0471ace3eb
https://doi.org/10.1101/2023.02.15.528631
https://doi.org/10.1101/2023.02.15.528631
Autor:
Md. Arafat Rahman, Mst. Noorunnahar
Publikováno v:
International Journal of Environmental Monitoring and Analysis. 1:175
This study aims to determine trends in the long-term monthly total data series using non-parametric methods like Mann-Kendall and Sen's T test. The change per unit time in a time series having a linear trend is estimated by applying a simple non-para