An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research …
Despite the massive diversity in the modeling requirements for practical hydrological
applications, there remains a need to develop more reliable and intelligent expert systems …
applications, there remains a need to develop more reliable and intelligent expert systems …
A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting
Y Wang, H Xu, M Song, F Zhang, Y Li, S Zhou, L Zhang - Applied Energy, 2023 - Elsevier
Wind speed forecasting plays an important role in the stable operation of wind energy power
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
systems. However, accurate and reliable wind speed forecasting faces four challenges: how …
Emerging evolutionary algorithm integrated with kernel principal component analysis for modeling the performance of a water treatment plant
Providing a robust and reliable model is essential for hydro-environmental and public health
engineering perspectives, including water treatment plants (WTPs). The current research …
engineering perspectives, including water treatment plants (WTPs). The current research …
Comparison of different methodologies for rainfall–runoff modeling: machine learning vs conceptual approach
Accurate short-term rainfall–runoff prediction is essential for flood mitigation and safety of
hydraulic structures and infrastructures. This study investigates the capability of four …
hydraulic structures and infrastructures. This study investigates the capability of four …
Short-term traffic volume prediction using GA-BP based on wavelet denoising and phase space reconstruction
Y Peng, W Xiang - Physica A: Statistical Mechanics and its Applications, 2020 - Elsevier
Accurate traffic volume prediction can help traffic managers to control traffic well, and can
also provide convenient travel routes for passengers. In order to better describe the non …
also provide convenient travel routes for passengers. In order to better describe the non …
State-of-the-art development of two-waves artificial intelligence modeling techniques for river streamflow forecasting
Streamflow forecasting is the most well studied hydrological science but still portray
numerous unknown knowledge. The conventional physical-based model is unable to yield a …
numerous unknown knowledge. The conventional physical-based model is unable to yield a …
Non-linear input variable selection approach integrated with non-tuned data intelligence model for streamflow pattern simulation
Streamflow modeling is considered as an essential component for water resources planning
and management. There are numerous challenges related to streamflow prediction that are …
and management. There are numerous challenges related to streamflow prediction that are …
Complementary data-intelligence model for river flow simulation
Despite of diverse progressions in hydrological modeling techniques, the necessity of a
robust, accurate, reliable, and trusted expert system for real-time stream flow prediction still …
robust, accurate, reliable, and trusted expert system for real-time stream flow prediction still …
Regional flood frequency analysis through some machine learning models in semi-arid regions
P Allahbakhshian-Farsani, M Vafakhah… - Water Resources …, 2020 - Springer
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 …
[PDF][PDF] Improving novel extreme learning machine using PCA algorithms for multi-parametric modeling of the municipal wastewater treatment plant
abstract In order to develop a tool for modeling the efficiency of municipal wastewater
treatment plants (MWWTP), a reliable prediction tool is essential. In this research, two …
treatment plants (MWWTP), a reliable prediction tool is essential. In this research, two …