AIMC Topic: Support Vector Machine

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Anomaly Detection in Satellite Telemetry Data Using a Sparse Feature-Based Method.

Sensors (Basel, Switzerland)
Anomaly detection based on telemetry data is a major issue in satellite health monitoring which can identify unusual or unexpected events, helping to avoid serious accidents and ensure the safety and reliability of operations. In recent years, sparse...

Modeling resilient modulus of subgrade soils using LSSVM optimized with swarm intelligence algorithms.

Scientific reports
Resilient modulus (Mr) of subgrade soils is one of the crucial inputs in pavement structural design methods. However, the spatial variability of soil properties and the nature of test protocols, the laboratory determination of Mr has become inexpedie...

Novel Internet of Things based approach toward diabetes prediction using deep learning models.

Frontiers in public health
The integration of the Internet of Things with machine learning in different disciplines has benefited from recent technological advancements. In medical IoT, the fusion of these two disciplines can be extremely beneficial as it allows the creation o...

Prediction of the Age and Gender Based on Human Face Images Based on Deep Learning Algorithm.

Computational and mathematical methods in medicine
In recent times, nutrition recommendation system has gained increasing attention due to their need for healthy living. Current studies on the food domain deal with a recommendation system that focuses on independent users and their health problems bu...

Research on a Machine Learning-Based Method for Assessing the Safety State of Historic Buildings.

Computational intelligence and neuroscience
Historic and protected buildings are increasingly valued due to their valuable historical and cultural value. The assessment of the safety state of historic buildings has received more attention. Emerging machine learning algorithms, with their excel...

Myocardial Function Prediction After Coronary Artery Bypass Grafting Using MRI Radiomic Features and Machine Learning Algorithms.

Journal of digital imaging
The main aim of the present study was to predict myocardial function improvement in cardiac MR (LGE-CMR) images in patients after coronary artery bypass grafting (CABG) using radiomics and machine learning algorithms. Altogether, 43 patients who had ...

Intelligent Diagnosis Based on Double-Optimized Artificial Hydrocarbon Networks for Mechanical Faults of In-Wheel Motor.

Sensors (Basel, Switzerland)
To avoid the potential safety hazards of electric vehicles caused by the mechanical fault deterioration of the in-wheel motor (IWM), this paper proposes an intelligent diagnosis based on double-optimized artificial hydrocarbon networks (AHNs) to iden...

Automatic Stones Classification through a CNN-Based Approach.

Sensors (Basel, Switzerland)
This paper presents an automatic recognition system for classifying stones belonging to different Calabrian quarries (Southern Italy). The tool for stone recognition has been developed in the SILPI project (acronym of ""), financed by POR Calabria FE...

Rolling Bearing Fault Diagnosis Based on WGWOA-VMD-SVM.

Sensors (Basel, Switzerland)
A rolling bearing fault diagnosis method based on whale gray wolf optimization algorithm-variational mode decomposition-support vector machine (WGWOA-VMD-SVM) was proposed to solve the unclear fault characterization of rolling bearing vibration signa...

A Novel Forecasting Approach by the GA-SVR-GRNN Hybrid Deep Learning Algorithm for Oil Future Prices.

Computational intelligence and neuroscience
It is hard to forecasting oil future prices accurately, which is affected by some nonlinear, nonstationary, and other chaotic characteristics. Then, a novel GA-SVR-GRNN hybrid deep learning algorithm is put forward for forecasting oil future price. F...