Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review
F Fahimi, ZM Yaseen, A El-shafie - Theoretical and applied climatology, 2017 - Springer
Since the middle of the twentieth century, artificial intelligence (AI) models have been used
widely in engineering and science problems. Water resource variable modeling and …
widely in engineering and science problems. Water resource variable modeling and …
Enhancing short-term forecasting of daily precipitation using numerical weather prediction bias correcting with XGBoost in different regions of China
Accurate precipitation (P) short-term forecasts are important for engineering studies and
water allocation. This study evaluated a method for bias correction of the Numerical Weather …
water allocation. This study evaluated a method for bias correction of the Numerical Weather …
Machine learning algorithm-based risk assessment of riparian wetlands in Padma River Basin of Northwest Bangladesh
Wetland risk assessment is a global concern especially in developing countries like
Bangladesh. The present study explored the spatiotemporal dynamics of wetlands …
Bangladesh. The present study explored the spatiotemporal dynamics of wetlands …
Monthly evaporation forecasting using artificial neural networks and support vector machines
G Tezel, M Buyukyildiz - Theoretical and applied climatology, 2016 - Springer
Evaporation is one of the most important components of the hydrological cycle, but is
relatively difficult to estimate, due to its complexity, as it can be influenced by numerous …
relatively difficult to estimate, due to its complexity, as it can be influenced by numerous …
New formulation for forecasting streamflow: evolutionary polynomial regression vs. extreme learning machine
M Rezaie-Balf, O Kisi - Hydrology Research, 2018 - iwaponline.com
Streamflow forecasting is crucial in hydrology and hydraulic engineering since it is capable
of optimizing water resource systems or planning future expansion. This study investigated …
of optimizing water resource systems or planning future expansion. This study investigated …
Using AR, MA, and ARMA time series models to improve the performance of MARS and KNN approaches in monthly precipitation modeling under limited climatic data
S Mehdizadeh - Water Resources Management, 2020 - Springer
Precipitation is one of the most important components of the hydrologic cycle as it is required
for multi-objective applications including flood estimation, drought monitoring, watersheds …
for multi-objective applications including flood estimation, drought monitoring, watersheds …
[HTML][HTML] Assessing the impacts of climate change on precipitation through a hybrid method of machine learning and discrete wavelet transform techniques, case study …
Abstract Study region Cork City, Ireland. Study focus Reconstruction of precipitation
timeseries is gaining increasing attention for monitoring and prediction studies. To address …
timeseries is gaining increasing attention for monitoring and prediction studies. To address …
Soft computing techniques for rainfall-runoff simulation: local non–parametric paradigm vs. model classification methods
Accurate simulation of rainfall-runoff process is of great importance in hydrology and water
resources management. Rainfall–runoff modeling is a non-linear process and highly …
resources management. Rainfall–runoff modeling is a non-linear process and highly …
Precipitation pattern modeling using cross-station perception: regional investigation
Establishing robust models for predicting precipitation processes can yield a significant
aspect for many applications in water resource engineering and environmental prospective …
aspect for many applications in water resource engineering and environmental prospective …
Machine learning in bioinformatics: new technique for DNA sequencing classification
The extraction of useful information from deoxyribonucleic acid (DNA) is a major component
of bioinformatics research, and DNA sequence categorization has a variety of applications …
of bioinformatics research, and DNA sequence categorization has a variety of applications …