AIMC Topic: Support Vector Machine

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Hybrid Random Forest and Support Vector Machine Modeling for HVAC Fault Detection and Diagnosis.

Sensors (Basel, Switzerland)
The malfunctioning of the heating, ventilating, and air conditioning (HVAC) system is considered to be one of the main challenges in modern buildings. Due to the complexity of the building management system (BMS) with operational data input from a la...

Improving robustness of a deep learning-based lung-nodule classification model of CT images with respect to image noise.

Physics in medicine and biology
. Robustness is an important aspect to consider, when developing methods for medical image analysis. This study investigated robustness properties of deep neural networks (DNNs) for a lung nodule classification problem based on CT images and proposed...

Comparison of partial least square, artificial neural network, and support vector regressions for real-time monitoring of CHO cell culture processes using in situ near-infrared spectroscopy.

Biotechnology and bioengineering
The biopharmaceutical industry must guarantee the efficiency and biosafety of biological medicines, which are quite sensitive to cell culture process variability. Real-time monitoring procedures based on vibrational spectroscopy such as near-infrared...

Septicemic Melioidosis Detection Using Support Vector Machine with Five Immune Cell Types.

Disease markers
Melioidosis, caused by (), predominantly occurs in the tropical regions. Of various types of melioidosis, septicemic melioidosis is the most lethal one with a mortality rate of 40%. Early detection of the disease is paramount for the better chances ...

What makes a good prediction? Feature importance and beginning to open the black box of machine learning in genetics.

Human genetics
Genetic data have become increasingly complex within the past decade, leading researchers to pursue increasingly complex questions, such as those involving epistatic interactions and protein prediction. Traditional methods are ill-suited to answer th...

UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning.

International journal of molecular sciences
Umami ingredients have been identified as important factors in food seasoning and production. Traditional experimental methods for characterizing peptides exhibiting umami sensory properties (umami peptides) are time-consuming, laborious, and costly....

Interpreting support vector machines applied in laser-induced breakdown spectroscopy.

Analytica chimica acta
Laser-induced breakdown spectroscopy is often combined with a multivariate black box model-such as support vector machines (SVMs)-to obtain desirable quantitative or qualitative results. This approach carries obvious risks when practiced in high-stak...

An Intelligence Method for Recognizing Multiple Defects in Rail.

Sensors (Basel, Switzerland)
Ultrasonic guided waves are sensitive to many different types of defects and have been studied for defect recognition in rail. However, most fault recognition algorithms need to extract features from the time domain, frequency domain, or time-frequen...

A high-resolution trajectory data driven method for real-time evaluation of traffic safety.

Accident; analysis and prevention
Real-time safety evaluation is essential for developing proactive safety management strategy and improving the overall traffic safety. This paper proposes a method for real-time evaluation of road safety, in which traffic states and conflicts are com...