AIMC Topic: Support Vector Machine

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Ensemble learning from ensemble docking: revisiting the optimum ensemble size problem.

Scientific reports
Despite considerable advances obtained by applying machine learning approaches in protein-ligand affinity predictions, the incorporation of receptor flexibility has remained an important bottleneck. While ensemble docking has been used widely as a so...

Using a Selective Ensemble Support Vector Machine to Fuse Multimodal Features for Human Action Recognition.

Computational intelligence and neuroscience
The traditional human action recognition (HAR) method is based on RGB video. Recently, with the introduction of Microsoft Kinect and other consumer class depth cameras, HAR based on RGB-D (RGB-Depth) has drawn increasing attention from scholars and i...

Random Forest Regressor-Based Approach for Detecting Fault Location and Duration in Power Systems.

Sensors (Basel, Switzerland)
Power system failures or outages due to short-circuits or "faults" can result in long service interruptions leading to significant socio-economic consequences. It is critical for electrical utilities to quickly ascertain fault characteristics, includ...

Random vector functional link with ε-insensitive Huber loss function for biomedical data classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Biomedical data classification has been a trending topic among researchers during the last decade. Biomedical datasets may contain several features noises. Hence, the conventional machine learning model cannot efficiently ha...

Dynamic training of a novelty classifier algorithm for real-time detection of early seizure onset.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To develop an adaptive framework for seizure detection in real-time that is practical to use in the Epilepsy Monitoring Unit (EMU) as a warning signal, and whose output helps characterize epileptiform activity.

Water Quality Indicator Interval Prediction in Wastewater Treatment Process Based on the Improved BES-LSSVM Algorithm.

Sensors (Basel, Switzerland)
This paper proposes a novel interval prediction method for effluent water quality indicators (including biochemical oxygen demand (BOD) and ammonia nitrogen (NH3-N)), which are key performance indices in the water quality monitoring and control of a ...

Landscape Perception Identification and Classification Based on Electroencephalogram (EEG) Features.

International journal of environmental research and public health
This paper puts forward a new method of landscape recognition and evaluation by using aerial video and EEG technology. In this study, seven typical landscape types (forest, wetland, grassland, desert, water, farmland, and city) were selected. Differe...

DEGnext: classification of differentially expressed genes from RNA-seq data using a convolutional neural network with transfer learning.

BMC bioinformatics
BACKGROUND: A limitation of traditional differential expression analysis on small datasets involves the possibility of false positives and false negatives due to sample variation. Considering the recent advances in deep learning (DL) based models, we...

Improving generalisation capability of artificial intelligence-based solar radiation estimator models using a bio-inspired optimisation algorithm and multi-model approach.

Environmental science and pollution research international
One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of the main sources of clean and renewable energy. In this study, daily Rs values at seven meteorologica...

Intelligent Fault Diagnosis Framework for Modular Multilevel Converters in HVDC Transmission.

Sensors (Basel, Switzerland)
Open circuit failure mode in insulated-gate bipolar transistors (IGBT) is one of the most common faults in modular multilevel converters (MMCs). Several techniques for MMC fault diagnosis based on threshold parameters have been proposed, but very few...