An overview on twin support vector regression

H Huang, X Wei, Y Zhou - Neurocomputing, 2022 - Elsevier
Twin support vector regression (TSVR) is a useful extension of traditional support vector
regression (SVR). As a new regression model, the basic idea of TSVR is generating a pair of …

Artificial intelligence for suspended sediment load prediction: a review

D Gupta, BB Hazarika, M Berlin, UM Sharma… - Environmental earth …, 2021 - Springer
The estimation of sediment yield concentration is crucial for the development of stream
ventures, watershed management, toxins estimation, soil disintegration, floods, and so on. In …

Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization

RM Adnan, RR Mostafa, O Kisi, ZM Yaseen… - Knowledge-Based …, 2021 - Elsevier
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 …

Groundwater level prediction using an improved ELM model integrated with hybrid particle swarm optimisation and grey wolf optimisation

S Samantaray, A Sahoo - Groundwater for Sustainable Development, 2024 - Elsevier
Groundwater, the world's most abundant source of freshwater, is rapidly depleting in many
regions due to a variety of factors. Groundwater resources (GWR) play a crucial role in daily …

Modelling and forecasting of COVID-19 spread using wavelet-coupled random vector functional link networks

BB Hazarika, D Gupta - Applied Soft Computing, 2020 - Elsevier
Researchers around the world are applying various prediction models for COVID-19 to
make informed decisions and impose appropriate control measures. Because of a high …

Density-weighted support vector machines for binary class imbalance learning

BB Hazarika, D Gupta - Neural Computing and Applications, 2021 - Springer
In real-world binary classification problems, the entirety of samples belonging to each class
varies. These types of problems where the majority class is notably bigger than the minority …

Sensor data-driven structural damage detection based on deep convolutional neural networks and continuous wavelet transform

Z Chen, Y Wang, J Wu, C Deng, K Hu - Applied Intelligence, 2021 - Springer
Structural damage detection is of very importance to improve reliability and safety of civil
structures. A novel sensor data-driven structural damage detection method is proposed in …

Predicting suspended sediment load in Peninsular Malaysia using support vector machine and deep learning algorithms

Y Essam, YF Huang, AH Birima, AN Ahmed… - Scientific reports, 2022 - nature.com
High loads of suspended sediments in rivers are known to cause detrimental effects to
potable water sources, river water quality, irrigation activities, and dam or reservoir …

[HTML][HTML] Quantitative forecasting of bed sediment load in river engineering: an investigation into machine learning methodologies for complex phenomena

M Fuladipanah, HM Azamathulla, O Kisi… - Water …, 2024 - iwaponline.com
The intricate calculation of bed sediment load (BSL), which is influenced by hydraulic,
hydrological, and sedimentary factors, is vital for informed decision-making in water …