AIMC Topic: Support Vector Machine

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: A Deep Learning-Based Data-Driven Analytics Scheme for Energy Theft Detection.

Sensors (Basel, Switzerland)
Integrating information and communication technology (ICT) and energy grid infrastructures introduces smart grids (SG) to simplify energy generation, transmission, and distribution. The ICT is embedded in selected parts of the grid network, which par...

A Decision Tree Model for Analysis and Judgment of Lower Limb Movement Comfort Level.

International journal of environmental research and public health
To address the problem of ambiguity and one-sidedness in the evaluation of comprehensive comfort perceptions during lower limb exercise, this paper deconstructs the comfort perception into two dimensions: psychological comfort and physiological comfo...

Detection of Peripheral Malarial Parasites in Blood Smears Using Deep Learning Models.

Computational intelligence and neuroscience
Due to the plasmodium parasite, malaria is transmitted mostly through red blood cells. Manually counting blood cells is extremely time consuming and tedious. In a recommendation for the advanced technology stage and analysis of malarial disease, the ...

Churn prediction in telecommunication industry using kernel Support Vector Machines.

PloS one
In this age of fierce competitions, customer retention is one of the most important tasks for many companies. Many previous works proposed models to predict customer churn based on various machine learning techniques. In this study, we proposed an ad...

Least square support vector machine-based variational mode decomposition: a new hybrid model for daily river water temperature modeling.

Environmental science and pollution research international
Machines learning models have recently been proposed for predicting rivers water temperature (T) using only air temperature (T). The proposed models relied on a nonlinear relationship between the T and T and they have proven to be robust modelling to...

Detecting Cyberattacks on Electrical Storage Systems through Neural Network Based Anomaly Detection Algorithm.

Sensors (Basel, Switzerland)
Distributed Energy Resources (DERs) are growing in importance Power Systems. Battery Electrical Storage Systems (BESS) represent fundamental tools in order to balance the unpredictable power production of some Renewable Energy Sources (RES). Neverthe...

Olive oil classification with Laser-induced fluorescence (LIF) spectra using 1-dimensional convolutional neural network and dual convolution structure model.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Laser-induced fluorescence (LIF) spectroscopy is widely used for the analysis and classification of olive oil. This paper proposes the classification of LIF data using a specific 1-dimensional convolutional neural network (1D-CNN) model, which does n...

Identification of DNA N4-methylcytosine sites based on multi-source features and gradient boosting decision tree.

Analytical biochemistry
N4-methylcytosine (4 mC) is an important and common methylation which widely exists in prokaryotes. It plays a crucial role in correcting DNA replication errors and protecting host DNA against degradation by restrictive enzymes. Hence, the accurate i...

A Stock Selection Model of Image Classification Method Based on Convolutional Neural Network.

Computational intelligence and neuroscience
With the development of artificial intelligence technology, an increasing number of researchers try to apply different machine learning and deep learning methods to quantitative trading fields to obtain more stable and efficient trading models. As a ...