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Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review
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 …
A comparative survey between cascade correlation neural network (CCNN) and feedforward neural network (FFNN) machine learning models for forecasting …
Suspended sediment concentration prediction is critical for the design of reservoirs, dams,
rivers ecosystems, various operations of aquatic resource structure, environmental safety …
rivers ecosystems, various operations of aquatic resource structure, environmental safety …
Application of several data-driven techniques for predicting groundwater level
In this study, several data-driven techniques including system identification, time series, and
adaptive neuro-fuzzy inference system (ANFIS) models were applied to predict groundwater …
adaptive neuro-fuzzy inference system (ANFIS) models were applied to predict groundwater …
M Vafakhah, S Mohammad Hasani Loor… - Arabian Journal of …, 2020 - Springer
Flood is one of the important destructive natural disasters in the world. Therefore, preparing
flood susceptibility map is necessary for flood management and mitigation in a region. This …
flood susceptibility map is necessary for flood management and mitigation in a region. This …
[HTML][HTML] Adaptive ensemble models for medium-term forecasting of water inflow when planning electricity generation under climate change
Medium-term forecasting of water inflow is of great importance for small hydroelectric power
plants operating in remote power supply areas and having a small reservoir. Improving the …
plants operating in remote power supply areas and having a small reservoir. Improving the …
Regional flood frequency analysis through some machine learning models in semi-arid regions
The machine learning models (MLMs), including support vector regression (SVR),
multivariate adaptive regression spline (MARS), boosted regression trees (BRT), and …
multivariate adaptive regression spline (MARS), boosted regression trees (BRT), and …
Regional flood frequency analysis using support vector regression in arid and semi-arid regions of Iran
E Sharifi Garmdareh, M Vafakhah… - Hydrological sciences …, 2018 - Taylor & Francis
Regional flood frequency analysis (RFFA) was carried out on data for 55 hydrometric
stations in Namak Lake basin, Iran, for the period 1992–2012. Flood discharge of specific …
stations in Namak Lake basin, Iran, for the period 1992–2012. Flood discharge of specific …
Enhancing streamflow forecasting using the augmenting ensemble procedure coupled machine learning models: case study of Aswan High Dam
The potential of the most recent pre-processing tool, namely, complete ensemble empirical
mode decomposition with adaptive noise (CEEMDAN), is examined for providing AI models …
mode decomposition with adaptive noise (CEEMDAN), is examined for providing AI models …
Optimization of wavelet-ANFIS and wavelet-ANN hybrid models by Taguchi method for groundwater level forecasting
In the recent years, artificial intelligence techniques have been widely developed for
modeling hydrologic processes. Determining the best structures of these models such as …
modeling hydrologic processes. Determining the best structures of these models such as …