Advances in computational intelligence of polymer composite materials: machine learning assisted modeling, analysis and design

A Sharma, T Mukhopadhyay, SM Rangappa… - … Methods in Engineering, 2022 - Springer
The superior multi-functional properties of polymer composites have made them an ideal
choice for aerospace, automobile, marine, civil, and many other technologically demanding …

Artificial intelligence based models for stream-flow forecasting: 2000–2015

ZM Yaseen, A El-Shafie, O Jaafar, HA Afan, KN Sayl - Journal of Hydrology, 2015 - Elsevier
Summary The use of Artificial Intelligence (AI) has increased since the middle of the 20th
century as seen in its application in a wide range of engineering and science problems. The …

Stacked machine learning algorithms and bidirectional long short-term memory networks for multi-step ahead streamflow forecasting: A comparative study

F Granata, F Di Nunno, G de Marinis - Journal of Hydrology, 2022 - Elsevier
Prediction of river flow rates is an essential task for both flood protection and optimal water
resource management. The high uncertainty associated with basin characteristics …

Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions

HR Maier, A Jain, GC Dandy, KP Sudheer - Environmental modelling & …, 2010 - Elsevier
Over the past 15 years, artificial neural networks (ANNs) have been used increasingly for
prediction and forecasting in water resources and environmental engineering. However …

Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm

D Zhang, J Lin, Q Peng, D Wang, T Yang… - Journal of …, 2018 - Elsevier
Reservoirs and dams are vital human-built infrastructures that play essential roles in flood
control, hydroelectric power generation, water supply, navigation, and other functions. The …

Artificial neural networks in drought prediction in the 21st century–A scientometric analysis

A Dikshit, B Pradhan, M Santosh - Applied Soft Computing, 2022 - Elsevier
Droughts are the most spatially complex geohazard, which often lasts for years, thereby
severely impacting socio-economic sectors. One of the critical aspects of drought studies is …

Data-driven modelling: some past experiences and new approaches

DP Solomatine, A Ostfeld - Journal of hydroinformatics, 2008 - iwaponline.com
Physically based (process) models based on mathematical descriptions of water motion are
widely used in river basin management. During the last decade the so-called data-driven …

Hybrid learning algorithm of radial basis function networks for reliability analysis

D Zhang, N Zhang, N Ye, J Fang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the wide application of industrial robots in the field of precision machining, reliability
analysis of positioning accuracy becomes increasingly important for industrial robots. Since …

Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting

G Zuo, J Luo, N Wang, Y Lian, X He - Journal of Hydrology, 2020 - Elsevier
Reliable and accurate streamflow forecasting is vital for water resource management. Many
streamflow prediction studies have demonstrated the excellent prediction ability of …

Generating ensemble streamflow forecasts: A review of methods and approaches over the past 40 years

M Troin, R Arsenault, AW Wood, F Brissette, JL Martel - 2021 - Wiley Online Library
Ensemble forecasting applied to the field of hydrology is currently an established area of
research embracing a broad spectrum of operational situations. This work catalogs the …