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 …

Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm

Y Tikhamarine, D Souag-Gamane, AN Ahmed, O Kisi… - Journal of …, 2020 - Elsevier
Monthly streamflow forecasting is required for short-and long-term water resources
management especially in extreme events such as flood and drought. Therefore, there is …

Recent ecological transitions in China: Greening, browning and influential factors

Y Lü, L Zhang, X Feng, Y Zeng, B Fu, X Yao, J Li… - Scientific reports, 2015 - nature.com
Ecological conservation and restoration are necessary to mitigate environmental
degradation problems. China has taken great efforts in such actions. To understand the …

Quantification and assessment of changes in ecosystem service in the Three-River Headwaters Region, China as a result of climate variability and land cover change

C Jiang, D Li, D Wang, L Zhang - Ecological Indicators, 2016 - Elsevier
Rapid and periodic assessment of the impact of land cover change and climate variability on
ecosystem services at regional levels is essential to understanding services and …

Daily suspended sediment concentration forecast in the upper reach of Yellow River using a comprehensive integrated deep learning model

J Fan, X Liu, W Li - Journal of Hydrology, 2023 - Elsevier
The precise prediction of suspended sediment concentration (SSC) is of great importance
for river reservoir construction planning, water resource management, and ecological …

[HTML][HTML] Hourly electricity price forecasting with NARMAX

C McHugh, S Coleman, D Kerr - Machine Learning with Applications, 2022 - Elsevier
Electricity price prediction through statistical and machine learning techniques captures
market trends and would be a useful tool for energy traders to observe price fluctuations and …

[PDF][PDF] Recent advancements & methodologies in system identification: A review

IM Yassin, MN Taib, R Adnan - Scientific Research Journal, 2013 - academia.edu
System Identification (SI) is a discipline in control engineering concerned with inferring
mathematical models from dynamic systems based on its input/output observations. Rich …

Ecosystem change assessment in the Three-river Headwater Region, China: Patterns, causes, and implications

C Jiang, L Zhang - Ecological Engineering, 2016 - Elsevier
Abstract The Three-River Headwater Region (TRHR) is the source of the Yangtze River,
Yellow River, and Lancang River, which is significant to fresh water resources in China and …

[HTML][HTML] Hydrological predictions for small ungauged watersheds in the Sudanian zone of the Volta basin in West Africa

B Ibrahim, D Wisser, B Barry, T Fowe… - Journal of Hydrology …, 2015 - Elsevier
Study region Hydrological observation networks in the West African region are not dense
and reliable. Furthermore, the few available discharge data often present significant gaps …

[PDF][PDF] Binary particle swarm optimization structure selection of nonlinear autoregressive moving average with exogenous inputs (NARMAX) model of a flexible robot …

IM Yassin, A Zabidi… - International …, 2016 - pdfs.semanticscholar.org
The Nonlinear Auto-Regressive Moving Average with Exogenous Inputs (NARMAX) model
is a powerful, efficient and unified representation of a variety of nonlinear models. The …