[HTML][HTML] A basic review of fuzzy logic applications in hydrology and water resources
In recent years, fuzzy logic has emerged as a powerful technique in the analysis of
hydrologic components and decision making in water resources. Problems related to …
hydrologic components and decision making in water resources. Problems related to …
Downscaling SMAP radiometer soil moisture over the CONUS using an ensemble learning method
Soil moisture plays a critical role in improving the weather and climate forecast and
understanding terrestrial ecosystem processes. It is a key hydrologic variable in agricultural …
understanding terrestrial ecosystem processes. It is a key hydrologic variable in agricultural …
Evaluation of the suitability of NCEP/NCAR, ERA-Interim and, ERA5 reanalysis data sets for statistical downscaling in the Eastern Black Sea Basin, Turkey
Climate community frequently uses gridded reanalysis data sets in their climate change
impact studies. However, these studies for a region yield more realistic results depending on …
impact studies. However, these studies for a region yield more realistic results depending on …
Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river
This study aimed to develop novel flood forecasting models using artificial neural network
(ANN) algorithms. The models were assessed and validated for the case study of an alluvial …
(ANN) algorithms. The models were assessed and validated for the case study of an alluvial …
A CMIP6-ensemble-based evaluation of precipitation and temperature projections
Understanding climate change's effects on dam basins is very important for water resource
management because of their important role in providing essential functions such as water …
management because of their important role in providing essential functions such as water …
Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system
Rainfall Prediction in Indonesia is very important for agricultural sector. However, obtaining
an accurate prediction is difficult as there are too many input parameters including the world …
an accurate prediction is difficult as there are too many input parameters including the world …
A Hybrid Fuzzy Wavelet Neural Network Model with Self‐Adapted Fuzzy c‐Means Clustering and Genetic Algorithm for Water Quality Prediction in Rivers
M Huang, D Tian, H Liu, C Zhang, X Yi, J Cai… - …, 2018 - Wiley Online Library
Water quality prediction is the basis of water environmental planning, evaluation, and
management. In this work, a novel intelligent prediction model based on the fuzzy wavelet …
management. In this work, a novel intelligent prediction model based on the fuzzy wavelet …
[HTML][HTML] Using Fuzzy Logic to Analyse Weather Conditions
Effective weather analysis is a very important scientific, social, and economic issue, because
weather directly affects our lives and has a significant impact on various sectors, including …
weather directly affects our lives and has a significant impact on various sectors, including …
Atmospheric weather prediction using various machine learning techniques: a survey
L Naveen, HS Mohan - 2019 3rd International Conference on …, 2019 - ieeexplore.ieee.org
Generally, weather is comprised of numerous parameters including rainfall, precipitation,
wind speed, etc. Environmental weather forecast is a testing errand for researchers and it …
wind speed, etc. Environmental weather forecast is a testing errand for researchers and it …
A real-time forecasting model for the spatial distribution of typhoon rainfall
GF Lin, BC Jhong - Journal of Hydrology, 2015 - Elsevier
Accurate forecasts of hourly rainfall are necessary for early warning systems during
typhoons. In this paper, a typhoon rainfall forecasting model is proposed to yield 1-to 6-h …
typhoons. In this paper, a typhoon rainfall forecasting model is proposed to yield 1-to 6-h …