Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions
H Tao, ZS Al-Khafaji, C Qi… - Engineering …, 2021 - Taylor & Francis
River sedimentation is an important indicator for ecological and geomorphological
assessments of soil erosion within any watershed region. Sediment transport in a river basin …
assessments of soil erosion within any watershed region. Sediment transport in a river basin …
An efficient data driven-based model for prediction of the total sediment load in rivers
Sediment load in fluvial systems is one of the critical factors shaping the river
geomorphological and hydraulic characteristics. A detailed understanding of the total …
geomorphological and hydraulic characteristics. A detailed understanding of the total …
Uncertainty analysis of water quality index (WQI) for groundwater quality evaluation: Application of Monte-Carlo method for weight allocation
Abstract Water Quality Index (WQI) have been recently used for evaluating water resources
quality. This index is developed to assist the water resources management and their …
quality. This index is developed to assist the water resources management and their …
Multi hours ahead prediction of surface ozone gas concentration: robust artificial intelligence approach
Forecasting the Ozone concentration is a substantial process in many important
environmental issues such air pollution management, risk assessment, public health, and …
environmental issues such air pollution management, risk assessment, public health, and …
[HTML][HTML] Reference evapotranspiration estimation in hyper-arid regions via D-vine copula based-quantile regression and comparison with empirical approaches and …
Study region Two hyper-arid regions (Atbara and Kassala stations) in Sudan. Study focus
The study aims to evaluate the potential of the D-vine Copula-based quantile regression …
The study aims to evaluate the potential of the D-vine Copula-based quantile regression …
Short to long-term forecasting of river flows by heuristic optimization algorithms hybridized with ANFIS
Accurate forecast of short-term to long-term streamflow prediction is of great importance for
water resources management. However, with the advent of novel hybrid machine learning …
water resources management. However, with the advent of novel hybrid machine learning …
On the complexities of sediment load modeling using integrative machine learning: Application of the great river of Loíza in Puerto Rico
M Zounemat-Kermani, A Mahdavi-Meymand… - Journal of …, 2020 - Elsevier
Sediment transportation in water bodies may cause many problems for the water resources
projects and damage the environment. Hence, modeling sediment load components …
projects and damage the environment. Hence, modeling sediment load components …
Pan evaporation estimation and derivation of explicit optimized equations by novel hybrid meta-heuristic ANN based methods in different climates of Iran
Pan evaporation (E p) estimation is important in scheduling and computing irrigation water
requirement. This study evaluated the ability of novel meta-heuristic optimization algorithms …
requirement. This study evaluated the ability of novel meta-heuristic optimization algorithms …
Comparative analysis of soft computing techniques RBF, MLP, and ANFIS with MLR and MNLR for predicting grade-control scour hole geometry
The main aims and contributions of the present paper are to use new soft computing
methods for the simulation of scour geometry (depth/height and locations) in a comparative …
methods for the simulation of scour geometry (depth/height and locations) in a comparative …
Derivation of optimized equations for estimation of dispersion coefficient in natural streams using hybridized ANN with PSO and CSO algorithms
In this paper, a new hybrid model is developed to improve the accuracy in the prediction of
the longitudinal dispersion coefficient () and the derivation of novel optimized explicit …
the longitudinal dispersion coefficient () and the derivation of novel optimized explicit …