AIMC Topic: Support Vector Machine

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Comparing linear and non-linear data-driven approaches in monthly river flow prediction, based on the models SARIMA, LSSVM, ANFIS, and GMDH.

Environmental science and pollution research international Nov 13, 2021
River flow variations directly affect the hydro-climatological, environmental, and ecological characteristics of a region. Therefore, an accurate prediction of river flow can critically be important for water managers and planners. The present study ...
Support Vector Machine Hydrology Rivers Linear Models Least-Squares Analysis
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Rapid identification of ore minerals using multi-scale dilated convolutional attention network associated with portable Raman spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Nov 13, 2021
Electron portable Raman spectroscopy tools for ore mineral identification are widely used in raw ore analysis and mineral process engineering. This paper demonstrates an extremely fast and accurate method for identifying unknown ore mineral samples b...
Support Vector Machine Minerals Machine Learning Spectrum Analysis, Raman Neural Networks, Computer
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Is skipping the definition of primary and secondary models possible? Prediction of Escherichia coli O157 growth by machine learning.

Journal of microbiological methods Nov 12, 2021
To predict bacterial population behavior in food, statistical models with specific function form have been applied in the field of predictive microbiology. Modelers need to consider the linear or non-linear relationship between the response and expla...
Support Vector Machine Food Microbiology Humans Population Growth Escherichia coli O157 Bacterial Load
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Fault Diagnosis of Permanent Magnet DC Motors Based on Multi-Segment Feature Extraction.

Sensors (Basel, Switzerland) Nov 11, 2021
For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. Only using the signal features of current in a single segment is not conducive to fault diagnosis for PMDCMs. In this work, mult...
Magnets Algorithms Support Vector Machine
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A Machine Learning Approach to Predictive Modelling of Student Performance.

F1000Research Nov 11, 2021
- Many factors affect student performance such as the individual's background, habits, absenteeism and social activities. Using these factors, corrective actions can be determined to improve their performance. This study looks into the effects of th...
Machine Learning Data Mining Humans Students Support Vector Machine Bayes Theorem
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Employing phylogenetic tree shape statistics to resolve the underlying host population structure.

BMC bioinformatics Nov 10, 2021
BACKGROUND: Host population structure is a key determinant of pathogen and infectious disease transmission patterns. Pathogen phylogenetic trees are useful tools to reveal the population structure underlying an epidemic. Determining whether a populat...
Machine Learning Algorithms ROC Curve Phylogeny Support Vector Machine
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A new ML-based approach to enhance student engagement in online environment.

PloS one Nov 10, 2021
The educational research is increasingly emphasizing the potential of student engagement and its impact on performance, retention and persistence. This construct has emerged as an important paradigm in the higher education field for many decades. How...
Electronic Mail Feedback, Psychological Students Education, Distance Videoconferencing Universities Problem-Based Learning Humans Support Vector Machine Text Messaging Neural Networks, Computer Problem Solving Motivation
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Survival prediction among heart patients using machine learning techniques.

Mathematical biosciences and engineering : MBE Nov 9, 2021
Cardiovascular diseases are regarded as the most common reason for worldwide deaths. As per World Health Organization, nearly 17.9 million people die of heart-related diseases each year. The high shares of cardiovascular-related diseases in total wor...
Humans Logistic Models Neural Networks, Computer Machine Learning Support Vector Machine Algorithms
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Performance comparison of deep learning and machine learning methods in determining wetland water areas using EuroSAT dataset.

Environmental science and pollution research international Nov 8, 2021
Wetlands are critical to the ecology because they maintain biodiversity and provide home for a variety of species. Researching, mapping, and conservation of wetlands is a challenging and time-consuming process. Because they produce temporal and geogr...
Support Vector Machine Deep Learning Neural Networks, Computer Wetlands Water Machine Learning
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Recognition study of denatured biological tissues based on multi-scale rescaled range permutation entropy.

Mathematical biosciences and engineering : MBE Nov 8, 2021
The recognition of denatured biological tissue is an indispensable part in the process of high intensity focused ultrasound treatment. As a nonlinear method, multi-scale permutation entropy (MPE) is widely used in the recognition of denatured biologi...
Algorithms Support Vector Machine Computer Simulation Entropy
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