Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …
sustainability of water resources. The literature has shown great potential for nature-inspired …
Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization
Accurate runoff estimation is crucial for optimal reservoir operation and irrigation purposes.
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
In this study, a novel hybrid method is proposed for monthly runoff prediction in Mangla …
Long lead-time daily and monthly streamflow forecasting using machine learning methods
Long lead-time streamflow forecasting is of great significance for water resources planning
and management in both the short and long terms. Despite of some studies using machine …
and management in both the short and long terms. Despite of some studies using machine …
SVM parameter optimization using grid search and genetic algorithm to improve classification performance
I Syarif, A Prugel-Bennett… - … Computing Electronics and …, 2016 - telkomnika.uad.ac.id
Abstract Machine Learning algorithms have been widely used to solve various kinds of data
classification problems. Classification problem especially for high dimensional datasets …
classification problems. Classification problem especially for high dimensional datasets …
Daily streamflow prediction using optimally pruned extreme learning machine
RM Adnan, Z Liang, S Trajkovic… - Journal of …, 2019 - Elsevier
Daily streamflow prediction is important for flood warning, navigation, sediment control,
reservoir operations and environmental protection. The current paper examines the …
reservoir operations and environmental protection. The current paper examines the …
Support vector regression optimized by meta-heuristic algorithms for daily streamflow prediction
Accurate and reliable prediction of streamflow is vital to the optimization of water resources
management, reservoir flood operations, catchment, and urban water management. In this …
management, reservoir flood operations, catchment, and urban water management. In this …
Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference
Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a …
Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a …
Reference evapotranspiration prediction using hybridized fuzzy model with firefly algorithm: Regional case study in Burkina Faso
Abstract Reference Evapotranspiration (ETo) is one of the major components of the
hydrological cycle that is very essential in water resources planning, irrigation and drainage …
hydrological cycle that is very essential in water resources planning, irrigation and drainage …
A comparative study of MLR, KNN, ANN and ANFIS models with wavelet transform in monthly stream flow prediction
A Khazaee Poul, M Shourian, H Ebrahimi - Water Resources Management, 2019 - Springer
Reliable and precise prediction of the rivers flow is a major concern in hydrologic and water
resources analysis. In this study, multi-linear regression (MLR) as a statistical method …
resources analysis. In this study, multi-linear regression (MLR) as a statistical method …
A novel hybrid model for forecasting crude oil price based on time series decomposition
H Abdollahi - Applied energy, 2020 - Elsevier
Oil price forecasting has received a prodigious attention by scholars and policymakers due
to its significant effect on various economic sectors and markets. Incentivized by this issue …
to its significant effect on various economic sectors and markets. Incentivized by this issue …