Artificial intelligence for suspended sediment load prediction: a review
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 …
ventures, watershed management, toxins estimation, soil disintegration, floods, and so on. In …
Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms
Floods and droughts are environmental phenomena that occur in Peninsular Malaysia due
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …
Suspended sediment load prediction modelling based on artificial intelligence methods: The tropical region as a case study
The impact of the suspended sediment load (SSL) on environmental health, agricultural
operations, and water resources planning, is significant. The deposit of SSL restricts the …
operations, and water resources planning, is significant. The deposit of SSL restricts the …
Predicting suspended sediment load in Peninsular Malaysia using support vector machine and deep learning algorithms
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 …
potable water sources, river water quality, irrigation activities, and dam or reservoir …
Comparison of Bayesian, k-Nearest Neighbor and Gaussian process regression methods for quantifying uncertainty of suspended sediment concentration prediction
Suspended sediment transport in river system is a complex process influenced by many
factors that their interactions lead to nonlinear and high scatter of concentration-discharge …
factors that their interactions lead to nonlinear and high scatter of concentration-discharge …
Universum based Lagrangian twin bounded support vector machine to classify EEG signals
B Kumar, D Gupta - Computer methods and programs in biomedicine, 2021 - Elsevier
Background and objective The detection of brain-related problems and neurological
disorders like epilepsy, sleep disorder, and so on is done by using electroencephalogram …
disorders like epilepsy, sleep disorder, and so on is done by using electroencephalogram …
Random vector functional link with ε-insensitive Huber loss function for biomedical data classification
BB Hazarika, D Gupta - Computer methods and programs in biomedicine, 2022 - Elsevier
Background and objective Biomedical data classification has been a trending topic among
researchers during the last decade. Biomedical datasets may contain several features …
researchers during the last decade. Biomedical datasets may contain several features …
Epilepsy attacks recognition based on 1D octal pattern, wavelet transform and EEG signals
Electroencephalogram (EEG) signals have been generally utilized for diagnostic systems.
Nowadays artificial intelligence-based systems have been proposed to classify EEG signals …
Nowadays artificial intelligence-based systems have been proposed to classify EEG signals …
Wavelet kernel least square twin support vector regression for wind speed prediction
Wind energy is a powerful yet freely available renewable energy. It is crucial to predict the
wind speed (WS) accurately to make a precise prediction of wind power at wind power …
wind speed (WS) accurately to make a precise prediction of wind power at wind power …
Kernel-target alignment based fuzzy Lagrangian twin bounded support vector machine
To improve the generalization performance, we develop a new technique for handling the
impacts of outliers using Lagrangian twin bounded SVM (TBSVM) with kernel fuzzy …
impacts of outliers using Lagrangian twin bounded SVM (TBSVM) with kernel fuzzy …