O Kisi, H Sanikhani - International Journal of Climatology, 2015 - search.ebscohost.com
ABSTRACT This paper investigates the ability of five different data-driven methods, artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS) with grid partition …
O Kisi, Y Kilic - Theoretical and applied climatology, 2016 - Springer
The generalization ability of artificial neural networks (ANNs) and M5 model tree (M5Tree) in modeling reference evapotranspiration (ET 0) is investigated in this study. Daily climatic …
This paper aims to provide a spatial and temporal analysis to prediction of monthly precipitation data which are measured at irregularly spaced synoptic stations at discrete time …
X Dou, Y Yang - Advances in Meteorology, 2018 - Wiley Online Library
Remarkable progress has been made over the last decade toward characterizing the mechanisms that dominate the exchange of water vapor between the biosphere and the …
SM Hosseini Vardanjani… - Journal of Water and …, 2024 - iwaponline.com
To enhance water use efficiency in agriculture, accurately estimating plant water consumption is essential. This study examines the ability of artificial neural networks (ANN) …
Reliable runoff series is sine qua non for flood or drought analysis as well as for water resources management and planning. Since observed hydrological measurement such as …
Abstract The Food and Agriculture Organization of the United Nations (FAO) in its publication No. 56 of the Irrigation and Drainage Series presents the FAO Penman-Monteith …
Climate change and its possible impact on reference evapotranspiration are the matter of great concern for countries like India where the spatial and temporal variability in rainfall …