Výsledky vyhledávání - "N L Kushwaha"

Akademický článek

Trend and change-point analyses of meteorological variables using Mann–Kendall family tests and innovative trend assessment techniques in New Bhupania command (India)

Autor: Venkatesh Gaddikeri, A. Sarangi, D. K. Singh, Malkhan Singh Jatav, Jitendra Rajput, N. L. Kushwaha

Publikováno v: Journal of Water and Climate Change, Vol 15, Iss 5, Pp 2033-2058 (2024)

Climate change (CC) significantly influences agricultural water productivity, it is advisable to consider the adapting irrigation regimes to observed changes in precipitation patterns. This study aim is to assess trends and change point analysis of w

Externí odkaz: https://doaj.org/article/7eeef95867ab47be871d58558527e942

Zobrazit plný text záznamu

Akademický článek

Forecasting monthly pan evaporation using hybrid additive regression and data-driven models in a semi-arid environment

Autor: Ahmed Elbeltagi, Mustafa Al-Mukhtar, N. L. Kushwaha, Nadhir Al-Ansari, Dinesh Kumar Vishwakarma

Publikováno v: Applied Water Science, Vol 13, Iss 2, Pp 1-18 (2022)

Abstract Exact estimation of evaporation rates is very important in a proper planning and efficient operation of water resources projects and agricultural activities. Evaporation is affected by many driving forces characterized by nonlinearity, non-s

Externí odkaz: https://doaj.org/article/aca3ef39c5a44225a5a7019358099646

Zobrazit plný text záznamu

Akademický článek

Data intelligence and hybrid metaheuristic algorithms-based estimation of reference evapotranspiration

Autor: Ahmed Elbeltagi, Ali Raza, Yongguang Hu, Nadhir Al-Ansari, N. L. Kushwaha, Aman Srivastava, Dinesh Kumar Vishwakarma, Muhammad Zubair

Publikováno v: Applied Water Science, Vol 12, Iss 7, Pp 1-18 (2022)

Abstract For developing countries, scarcity of climatic data is the biggest challenge, and model development with limited meteorological input is of critical importance. In this study, five data intelligent and hybrid metaheuristic machine learning a

Externí odkaz: https://doaj.org/article/8c92ea695e75419b84e615a4b70bfa8a

Zobrazit plný text záznamu

Akademický článek

Forecasting of SPI and Meteorological Drought Based on the Artificial Neural Network and M5P Model Tree

Autor: Chaitanya B. Pande, Nadhir Al-Ansari, N. L. Kushwaha, Aman Srivastava, Rabeea Noor, Manish Kumar, Kanak N. Moharir, Ahmed Elbeltagi

Publikováno v: Land, Vol 11, Iss 11, p 2040 (2022)

Climate change has caused droughts to increase in frequency and severity worldwide, which has attracted scientists to create drought prediction models to mitigate the impacts of droughts. One of the most important challenges in addressing droughts is

Externí odkaz: https://doaj.org/article/72d752b6b21f47be90e07f60744055d0

Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání