Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bhagabat P. Parida"'
Publikováno v:
Earth, Vol 4, Iss 2, Pp 398-441 (2023)
Futuristic rainfall projections are used in scale and various climate impact assessments. However, the influence of climate variability on spatial distribution patterns and characteristics of rainfall at the local level, especially in semi-arid catch
Externí odkaz:
https://doaj.org/article/98c1d384d0f7451aafab26c3e4511dff
Publikováno v:
Heliyon, Vol 9, Iss 2, Pp e13700- (2023)
Fatalities due to road accidents remain a major challenge worldwide. In the recent years, Malawi, one of the developing African countries with a total population of about 19 million has also been witnessing a very high fatality rate [of about 31 cras
Externí odkaz:
https://doaj.org/article/fd94002fafdb49c49ccef49dc5d7b581
Publikováno v:
Journal of Road Safety, Vol 31, Iss 3, Pp 48-56 (2020)
Road fatalities remain a major public health concern as over 1.3 million people across the world die in road accidents annually, and another 20-50 million sustain injuries. Malawi, with vehicle ownership about 437,416, has not been an exception to th
Externí odkaz:
https://doaj.org/article/cce3866083804d71a51f0b0e95669404
Publikováno v:
Remote Sensing, Vol 13, Iss 13, p 2427 (2021)
Land use/land cover (LULC) changes have been observed in the Gaborone dam catchment since the 1980s. A comprehensive analysis of future LULC changes is therefore necessary for the purposes of future land use and water resource planning and management
Externí odkaz:
https://doaj.org/article/01f34297efce4e9d89da00f60ae44f71
Publikováno v:
Earth; Volume 4; Issue 2; Pages: 398-441
Futuristic rainfall projections are used in scale and various climate impact assessments. However, the influence of climate variability on spatial distribution patterns and characteristics of rainfall at the local level, especially in semi-arid catch
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::783e229db99867b4e4a770672cf94893
Autor:
Yashon O. Ouma, Ditiro B. Moalafhi, George Anderson, Boipuso Nkwae, Phillimon Odirile, Bhagabat P. Parida, Jiaguo Qi
Publikováno v:
Sustainability; Volume 14; Issue 22; Pages: 14934
To predict the variability of dam water levels, parametric Multivariate Linear Regression (MLR), stochastic Vector AutoRegressive (VAR), Random Forest Regression (RFR) and Multilayer Perceptron (MLP) Artificial Neural Network (ANN) models were compar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac6769dcde7f51ebdddfb899473186a0